ArteraAI Prostate
Device Facts
| Record ID | DEN240068 |
|---|---|
| Device Name | ArteraAI Prostate |
| Applicant | Artera, Inc. |
| Product Code | SFH · Pathology |
| Decision Date | Jul 31, 2025 |
| Decision | DENG |
| Submission Type | Direct |
| Regulation | 21 CFR 864.3755 |
| Device Class | Class 2 |
| Attributes | AI/ML, Software as a Medical Device, PCCP |
AI Performance
| Output | Acceptance | Observed | Dev DS | Test DS |
|---|---|---|---|---|
| 10-year risk of distant metastasis (DM) | Not explicitly stated as a single threshold; performance supported by statistical significance of risk category differences compared to overall risk. | High risk category: 28.1% (95% CI: 19.4%-37.5%); Intermediate risk category: 6.6% (95% CI: 3.6%-10.8%); Low risk category: 3.3% (95% CI: 1.8%-5.6%); Overall risk: 8.1% (95% CI: 6.1%-10.4%). | Training dataset: N=10,091 patients from multiple, multi-center, prospective randomized controlled clinical trials (Canary-PASS, RTOG-0126, RTOG-0415, RTOG-0521, RTOG-9202, RTOG-9408, RTOG-9413, RTOG-9902, RTOG-9910, STAMPEDE, and Contemporary Biopsy Cohort A). | Pivotal clinical performance study: N=886 patients with non-metastatic prostate cancer diagnosed since 2005 across three US sites. |
| 10-year risk of prostate cancer specific mortality (PCSM) | Not explicitly stated as a single threshold; performance supported by statistical significance of risk category differences compared to overall risk. | High risk category: 10.2% (95% CI: 4.7%-18.2%); Intermediate risk category: 1.1% (95% CI: 0.2%-3.7%); Low risk category: 0.6% (95% CI: 0.1%-2.0%); Overall risk: 2.3% (95% CI: 1.2%-3.8%). | Training dataset: N=10,091 patients from multiple, multi-center, prospective randomized controlled clinical trials (Canary-PASS, RTOG-0126, RTOG-0415, RTOG-0521, RTOG-9202, RTOG-9408, RTOG-9413, RTOG-9902, RTOG-9910, STAMPEDE, and Contemporary Biopsy Cohort A). | Pivotal clinical performance study: N=886 patients with non-metastatic prostate cancer diagnosed since 2005 across three US sites. |
Indications for Use
ArteraAI Prostate is a software only device intended to analyze scanned histopathology whole slide images (WSIs) from treatment-naïve prostate core needle biopsies prepared from formalin fixed paraffin-embedded (FFPE) tissue and stained using Hematoxylin & Eosin (H&E) stains. ArteraAI Prostate provides 10-year risks of distant metastasis and prostate cancer specific mortality and is intended to assist physicians with prognostic risk-based decisions along with other clinicopathological factors in non-metastatic prostate cancer patients. ArteraAI Prostate is intended for males 55 years of age or older without clinically or pathologically defined metastases, and who are candidates for curative intent management (surgery, radiation therapy with or without systemic therapy, or active surveillance). ArteraAI Prostate is intended to utilize WSIs acquired from an FDA-cleared interoperable scanner with which ArteraAI Prostate has been authorized for use or a 510(k)-cleared scanner that has been assessed in accordance with the Predetermined Change Control Plan (PCCP) for qualifying additional interoperable scanners.
Device Story
Software-only device; analyzes scanned histopathology whole slide images (WSIs) of H&E-stained FFPE prostate core needle biopsies; utilizes algorithm to provide 10-year risk estimates for distant metastasis and prostate cancer-specific mortality; used by physicians to assist in prognostic risk-based management decisions for non-metastatic prostate cancer patients; operates on WSIs from FDA-cleared interoperable scanners; output supports clinical decision-making alongside standard clinicopathological factors; benefits patients by providing prognostic information to guide curative intent management strategies.
Clinical Evidence
Retrospective clinical study of 886 patients (age 55+, T1-T4, Gleason 6-10). Primary endpoints: 10-year risk of DM and PCSM. Results: High-risk category showed 28.1% 10-year DM risk (vs 8.1% overall) and 10.2% PCSM risk (vs 2.3% overall). Low-risk category showed 3.3% 10-year DM risk and 0.6% PCSM risk. Subgroup analyses validated performance across African American/non-African American cohorts and various treatment regimens (active surveillance, radiation, prostatectomy).
Technological Characteristics
Software-only device; deep learning-based algorithm; utilizes WSIs (40x magnification, 0.25 µm/pixel) from FDA-cleared scanners. Operates via cloud-based platform (Web Portal/Back-End). Locked algorithm (not continuous learning). Cybersecurity controls include threat modeling, SBOM, and risk management per FD&C Act Section 524B.
Indications for Use
Indicated for males 55+ years old with non-metastatic prostate cancer, who are candidates for curative intent management (surgery, radiation, or active surveillance), to provide 10-year risk estimates for distant metastasis and prostate cancer-specific mortality.
Regulatory Classification
Identification
ArteraAI Prostate is a software only device intended to analyze scanned histopathology whole slide images (WSIs) from treatment-naïve prostate core needle biopsies prepared from formalin fixed paraffin-embedded (FFPE) tissue and stained using Hematoxylin & Eosin (H&E) stains. It provides 10-year risks of distant metastasis and prostate cancer specific mortality and is intended to assist physicians with prognostic risk-based decisions along with other clinicopathological factors in non-metastatic prostate cancer patients (males 55 years of age or older).
Special Controls
In combination with the general controls of the FD&C Act, the software algorithm device analyzing digital images for cancer prognosis is subject to the following special controls: (1) The labeling must include the following: (i) Information on the device input(s) (e.g., scanned whole slide images, scanners); (ii) Information about the specimen type (e.g., Hematoxylin & Eosin-stained core needle biopsy, cytology specimen); (iii) Information on the device output(s) and information necessary to interpret the outputs (e.g., risk estimates for recurrence); (iv) A description of intended users and any recommended training necessary for safe use of the device; (v) Limiting statements that indicate: (A) That users should use the device in conjunction with a complete standard of care evaluation; (B) A description of situations in which the device may fail or may not operate at its expected performance level (e.g., poor image quality or for certain subpopulations), including any limitations in the dataset used to train, test, and tune the algorithm during device development (if applicable); and (C) That the data acquired using the device should only be interpreted by the types of users indicated in the intended use statement. (2) Design verification and validation must include: (i) A description of any datasets used to train, tune, or test the algorithm. The training dataset must include cases representing different variables representative of the conditions likely to be encountered when used as intended (e.g., multiple sites, patient demographics, clinical parameters, challenging diagnostic cases, internal signals and cutoffs); (ii) Device performance data demonstrating appropriate precision and reproducibility of the device along with the following information from the studies: the origin of the digital images, operators (if applicable), location of the study site(s), and digital images corresponding to challenging cases; and (iii) Clinical data demonstrating clinical performance of the device for its intended use, using a dataset representative of the intended use population. The clinical validation dataset must be independent of the data used in the development of the device and must document relevant details, including the origin of the study slides and images, location of the study site(s), and any challenging diagnoses. This clinical data must also include sub-group analysis of relevant population groups.
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Submission Summary (Full Text)
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FDA U.S. FOOD & DRUG ADMINISTRATION
# EVALUATION OF AUTOMATIC CLASS III DESIGNATION FOR ArteraAI Prostate DECISION SUMMARY
## I Background Information:
A De Novo Number
DEN240068
B Applicant
Artera Inc.
C Proprietary and Established Names
ArteraAI Prostate
D Regulatory Information
| Product Code(s) | Classification | Regulation Section | Panel |
| --- | --- | --- | --- |
| SFH | Class II | 21 CFR 864.3755
Software algorithm
device analyzing
digital images for
cancer prognosis | 88 – PATHOLOGY |
## II Submission/Device Overview:
A Purpose for Submission:
De Novo request for evaluation of automatic class III designation for ArteraAI Prostate.
B Measurand:
Scanned whole slide images (WSI) of Hematoxylin & Eosin (H&E)-stained prostate needle core biopsies.
Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993-0002
www.fda.gov
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C Type of Test:
Evaluation of scanned WSIs of H&E-stained prostate needle biopsies by Artificial Intelligence/Machine Learning (AI/ML) based algorithm to provide cancer associated prognostic 10-year risk estimates of distant metastasis (DM) and prostate cancer specific mortality (PCSM).
III Indications for Use:
A. Indication(s) for Use:
ArteraAI Prostate is a software only device intended to analyze scanned histopathology whole slide images (WSIs) from treatment-naïve prostate core needle biopsies prepared from formalin fixed paraffin-embedded (FFPE) tissue and stained using Hematoxylin & Eosin (H&E) stains. ArteraAI Prostate provides 10-year risks of distant metastasis and prostate cancer specific mortality and is intended to assist physicians with prognostic risk-based decisions along with other clinicopathological factors in non-metastatic prostate cancer patients.
ArteraAI Prostate is intended for males 55 years of age or older without clinically or pathologically defined metastases, and who are candidates for curative intent management (surgery, radiation therapy with or without systemic therapy, or active surveillance).
ArteraAI Prostate is intended to utilize WSIs acquired from an FDA-cleared interoperable scanner with which ArteraAI Prostate has been authorized for use or a 510(k)-cleared scanner that has been assessed in accordance with the Predetermined Change Control Plan (PCCP) for qualifying additional interoperable scanners.
B Special Conditions for Use Statement(s):
Rx - For Prescription Use Only
Warnings
1. The ArteraAI Prostate should be used in conjunction with a complete standard of care evaluation.
2. The ArteraAI Prostate patient report is to be utilized by trained physicians after being released by the pathology laboratory user.
3. The ArteraAI Prostate results correctness is based on the quality requirements of the slide images and appropriate whole slide imaging scanner usage.
4. Ensure proper traceability of the scanned images to the patient using an anonymized patient ID.
Please refer to the labeling for a complete list of warnings and precautions.
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# C Special Instrument Requirements:
Philips Ultra Fast Scanner (DEN160056)
# IV Device/System Characteristics:
# A Device Description:
ArteraAI Prostate is a software only device that utilizes deep learning algorithms developed with WSI of H&E-stained prostate needle biopsies to assess risk of distant metastasis and prostate cancer specific mortality. The software performs an algorithmic assessment of features extracted from WSIs using self-supervised learning. ArteraAI Prostate consists of one algorithm, comprised of multiple building block models that intake image data to calculate ArteraAI raw scores. These raw scores are used to estimate risk categories (High, Intermediate, Low) for 10-year risk of DM and PCSM. The algorithm is locked; it is not a continuous learning (continual machine learning model) algorithm.
ArteraAI Prostate includes the ArteraAI Platform (which includes the sub-components ArteraAI Web Portal and ArteraAI Back-End) and ArteraAI Prostate (which includes the sub-components ArteraAI Image Converter and the ArteraAI AI Engine). The ArteraAI Prostate interacts with the ArteraAI Platform. The functions of the above components are provided in the Table 1 below.
Table 1. ArteraAI Prostate Sub-Components Overview
| Sub-Component | Description |
| --- | --- |
| ArteraAI Platform | |
| ArteraAI Web Portal | Allows users to interact with the platform to perform the following functions: 1. Select the test to be performed. 2. Input data. 3. Pass data to the Back-End component. 4. Receive report generated for the given patient ID. 5. Manage records from the previously executed tests. 6. Access instructions for use and labeling information. The sub-component does not modify the data or take any action other than transmitting it to the back end. |
| ArteraAI Back-End | Manages the task execution of other components and performs the following functions: 1. Send and retrieve data associated with a given ID to/from the database. 2. Start Image Converter jobs and pass the location of slide images to the Image Converter. |
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| Sub-Component | Description |
| --- | --- |
| ArteraAI Platform | |
| | 3. Start AI jobs and pass location of slide images to the AI Engine.
4. Compile PDF reports.
5. Manage user authentication.
The sub-component does not modify the data or take any action other than transmitting it to the AI Engine and Image Converter and populate the PDF report with results from the AI Engine. |
| ArteraAI Prostate | |
| ArteraAI Image Converter | Converts images to a format usable by the AI Engine (iSyntax to TIFF). |
| ArteraAI AI Engine | Includes the AI/ML algorithm and performs the evaluation of WSIs that are uploaded and provides the device output as described in the intended use. |
**Device Input:**
The only input to the device is WSIs of H&E-stained prostate needle biopsy. WSIs are generated from the FDA cleared Philips Ultra Fast Scanner with below Settings:
Magnification: 40x
Resolution: 0.25 µm/pixel
Compression: Proprietary of Philips
File format: iSyntax, Philips proprietary file format with either RAW or iSyntax compression.
All WSIs from prostate cancer biopsy slides with the same highest Gleason grade determined by the pathologist are uploaded to the ArteraAI web portal which are then analyzed by the ArteraAI Prostate device. The ArteraAI Prostate device initially calculates a raw score for a patient. Then two cutoffs C1 and C2 are applied to the raw score for determination of the ArteraAI Prostate risk categories:
Raw Score > C2, then category=High
C1<Raw Score ≤C2, then category=Intermediate
Raw Score ≤C1, then category=Low
The highest ArteraAI Prostate risk category is provided in the patient report.
**Device Output:**
The test output is a patient specific report, which includes the following:
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10-year ArteraAI Prostate Categorical Risk for Distant Metastasis (High, Intermediate, Low)
- Individual 10-year risk for Distant Metastasis (Low and Intermediate)
10-year ArteraAI Prostate Categorical Risk for Prostate Cancer Specific Mortality (PCSM) (High, Intermediate, Low)
The ArteraAI Prostate patient report is intended to be interpreted by the physician to aid in understanding the risk of DM or PCSM in the prostate cancer patient. The results are provided to support risk-based decisions within the recommended professional guidelines.
# B Principle of Operation
ArteraAI Prostate is intended to be operated within a pathology laboratory with digital scanning capabilities. The ArteraAI Prostate workflow is depicted in Figure 1 below.
Figure 1. ArteraAI Prostate Workflow
The slide review and image selection procedure for uploading to the ArteraAI web portal is as follows:
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1. ArteraAI Prostate is performed on WSI images of prostate core biopsy specimen after a patient's diagnosis of prostate cancer per standard of care. A qualified pathologist must have already determined that prostate cancer is present in the patient prostate core biopsy specimen. ArteraAI Prostate is intended for use only with slide images that contain non-metastatic prostate cancer. If there is no prostate cancer in any of the biopsy cores, ArteraAI Prostate should not be used.
2. The pathologist will identify the WSI(s) of the biopsy specimen containing the highest Gleason score. The WSIs are obtained using the FDA-cleared Philips Ultra Fast scanner at 40x magnification in accordance with the scanner's Instructions for Use.
3. The WSIs are reviewed to verify that the image is not blurry, no defects are present and the whole tissue region is included in the image. Additional image and other related quality control steps are performed per the ArteraAI Prostate Instructions for Use.
4. The WSI(s) and a unique patient identifier are entered as data inputs to the ArteraAI web portal that is then transferred to Artera's back-end infrastructure. The patient identifier is intended to provide end-to-end traceability while protecting patient health information privacy.
5. During the WSI transfer process, a web worker (thread) which is a web browser feature, is used to manage the upload of the WSI to parallelize the data transfer. This allows the image and other data upload to proceed in the background, allowing the operator to continue interacting with the system without interruption.
6. ArteraAI Prostate uses the uploaded WSI(s) as input. Additional clinical data, if entered into the web portal, are not used as an input to ArteraAI Prostate but are only for the purposes of including this information in the ArteraAI Prostate Test Report.
7. ArteraAI Prostate produces a test report that summarizes the ArteraAI Prostate results and transfers the test report to the pathology laboratory via the ArteraAI web portal.
8. The pathologist will confirm the presence of cancer within the uploaded WSI, review and approve the report in accordance with the local laboratory procedures and release the test report to the requesting clinician.
## C. ArteraAI Prostate Prognostic Model Development
The AI algorithm used in the ArteraAI Prostate was developed using deep learning machine learning algorithms trained on WSIs of H&E- stained prostate needle biopsy slides from multiple, multi-center, prospective randomized controlled clinical trials and clinical studies to assess 10-year risk of DM and PCSM. As indicated in the Table 2 below the datasets included a representative spectrum of cases with diagnostic variability including a range of Gleason scores, tumor stages. The model was trained on the data summarized in Table 2 below using the ground truth of actual metastasis or prostate cancer specific mortality events experienced by the patients in the trials from which the data is extracted. There were 1,133 distant metastasis events and 931 prostate cancer specific mortality events in the dataset used to train the model. Additional information about training dataset is presented in Table 2 below:
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Table 2. Characteristics of Training Dataset
| Study Name | | | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Variables | TotalN=100091 | Canary-PASSN=9711 | RTOGI,0126N=11101 | RTOG-0415N=7141 | RTOG-0521N=3511 | RTOG-9202N=12511 | RTOG-9408N=17211 | RTOG-9413N=9461 | RTOG-9902N=3351 | RTOG-9910N=9811 | STAMPEDEN=15891 | ContemporaryBiopsyCohort AN=401 |
| Treatment PerProtocol1 | | | | | | | | | | | | |
| AS3 | 971(9.7%) | 971(100%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(-) |
| RT4-only | 2,697(27%) | 0(0%) | 1,110(100%) | 714(100%) | 0(0%) | 0(0%) | 873(51%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(-) |
| RT + ST-ADT5 | 2,898(29%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 619(49%) | 848(49%) | 946(100%) | 0(0%) | 485(49%) | 0(0%) | 0(-) |
| RT + IT-ADT6 | 496(5.0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 496(51%) | 0(0%) | 0(-) |
| RT + LT-ADT7 | 974(9.8%) | 0(0%) | 0(0%) | 0(0%) | 170(48%) | 632(51%) | 0(0%) | 0(0%) | 172(51%) | 0(0%) | 0(0%) | 0(-) |
| RT + LT-ADT +Chemo | 344(3.5%) | 0(0%) | 0(0%) | 0(0%) | 181(52%) | 0(0%) | 0(0%) | 0(0%) | 163(49%) | 0(0%) | 0(0%) | 0(-) |
| ADT +/- RT | 791(7.9%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 791(50%) | 0(-) |
| ADT + Chemo +/-ZA8 | 237(2.4%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 237(15%) | 0(-) |
| ADT + Abs9 +/-Enza10 | 561(5.6%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 0(0%) | 561(35%) | 0(-) |
| Missing | 40 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 40 |
| Age at time of biopsy/randomization | | | | | | | | | | | | |
| Median (Q1 - Q3) | 69(64 - 73) | 63(58 - 67) | 71(65 - 74) | 68(62 - 73) | 66(59 - 72) | 70(66 - 74) | 71(66 - 74) | 70(65 - 74) | 66(60 - 71) | 71(65 - 74) | 68(63 - 72) | 64(58 - 68) |
| Min - Max | 33 - 91 | 39 - 81 | 33 - 87 | 45 - 84 | 48 - 83 | 43 - 88 | 47 - 91 | 44 - 87 | 42 - 81 | 46 - 88 | 41 - 86 | 46 - 74 |
| Race | | | | | | | | | | | | |
| African American | 1,316(13%) | 68 (7.0%) | 115 (10%) | 107(15%) | 34 (9.7%) | 153(12%) | 334(19%) | 236(25%) | 92 (27%) | 166(17%) | 0(0%) | 11 (28%) |
| White | 6,777(68%) | 866(89%) | 960(86%) | 584(82%) | 306(87%) | 1,065(85%) | 1,314(76%) | 653(69%) | 230(69%) | 774(79%) | 0(0%) | 25 (63%) |
| Other | 285(2.8%) | 37 (3.8%) | 21 (1.9%) | 15 (2.1%) | 8 (2.3%) | 27 (2.2%) | 70 (4.1%) | 51 (5.4%) | 12 (3.6%) | 40 (4.1%) | 0(0%) | 4 (10%) |
| Unknown | 1,631(16%) | 0(0%) | 14 (1.3%) | 8 (1.1%) | 3 (0.9%) | 6 (0.5%) | 3 (0.2%) | 6 (0.6%) | 1 (0.3%) | 1 (0.1%) | 1,589(100%) | 0(0%) |
| PSA (ug/mL) at time of biopsy/randomization | | | | | | | | | | | | |
| Median (Q1 - Q3) | 10.4 (6.1 - 22.2) | 5.0 (3.9 - 6.6) | 7.6 (5.4 - 10.6) | 5.5 (4.4 - 7.1) | 15.7 (7.3 - 37.7) | 20.1 (11.0 - 39.7) | 8.1 (5.8 - 11.7) | 23.4 (12.6 - 36.0) | 22.9 (9.5 - 40.7) | 10.9 (6.8 - 15.0) | 40.0 (15.9 - 80.3) | 6.2 (4.7 - 10.9) |
| Min - Max | 0.1 - 2,870.0 | 0.3 - 19.5 | 0.1 - 19.9 | 0.1 - 10.0 | 0.7 - 145.0 | 0.1 - 250.0 | 0.1 - 20.0 | 2.1 - 97.6 | 1.8 - 96.4 | 0.6 - 72.9 | 0.6 - 2,870.0 | 2.6 - 61.9 |
| Missing | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0 | 0 |
| Tumor Stage | | | | | | | | | | | | |
| T1-T2a | 5,267(53%) | 964(99%) | 952(86%) | 671(94%) | 117 (33%) | 0(0%) | 1,385(80%) | 210(22%) | 126(38%) | 800(82%) | 8(0.5%) | 34 (85%) |
| T2b-c | 1,971(20%) | 7 (0.7%) | 158(14%) | 43 (6.0%) | 134(38%) | 565(45%) | 336(20%) | 398(42%) | 101(30%) | 123(13%) | 101(6.4%) | 5 (13%) |
| T3a | 442(4.4%) | 0(0%) | 0(0%) | 0(0%) | 45 (13%) | 184(15%) | 0(0%) | 138(15%) | 50 (15%) | 25 (2.5%) | 0(0%) | 0(0%) |
| T3b-T4 | 2,307(23%) | 0(0%) | 0(0%) | 0(0%) | 55 (16%) | 502(40%) | 0(0%) | 200(21%) | 58 (17%) | 33 (3.4%) | 1,458(93%) | 1 (2.5%) |
| Missing | 22 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 22 | 0 |
| Gleason Grade Group | | | | | | | | | | | | |
| 1 | 3,866(39%) | 894(92%) | 169(15%) | 713(100%) | 0(0%) | 472(40%) | 1,049(62%) | 255(27%) | 0(0%) | 273(28%) | 29(1.8%) | 12 (30%) |
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| 2 | 2,147(22%) | 77 (7.9%) | 676(61%) | 0 (0%) | 34 (9.7%) | 242(21%) | 309(18%) | 254(27%) | 55 (16%) | 371(38%) | 118(7.4%) | 11 (28%) |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 2/3 | 52 (0.5%) | 0 (0%) | 1 (<0.1%) | 0 (0%) | 1 (0.3%) | 25 (2.1%) | 10 (0.6%) | 11 (1.2%) | 0 (0%) | 4 (0.4%) | 0 (0%) | 0 (0%) |
| 3 | 1,188(12%) | 0 (0%) | 264(24%) | 0 (0%) | 22 (6.3%) | 132 (11%) | 155(9.2%) | 155(16%) | 56 (17%) | 224(23%) | 175 (11%) | 5 (13%) |
| 4 | 1,169(12%) | 0 (0%) | 0 (0%) | 0 (0%) | 110 (31%) | 157(13%) | 114(6.8%) | 161(17%) | 115 (34%) | 77 (7.8%) | 429(27%) | 6 (15%) |
| 5 | 1,459(15%) | 0 (0%) | 0 (0%) | 0 (0%) | 184(52%) | 141(12%) | 45 (2.7%) | 109(12%) | 109(33%) | 32 (3.3%) | 833(53%) | 6 (15%) |
| Missing | 128 | 0 | 0 | 1 | 0 | 82 | 39 | 1 | 0 | 0 | 5 | 0 |
| NCCN risk group | | | | | | | | | | | | |
| Low | 2,091(21%) | 828(85%) | 0 (0%) | 670(94%) | 0 (0%) | 0 (0%) | 577(34%) | 0 (0%) | 0 (0%) | 6 (0.6%) | 0 (0%) | 10 (25%) |
| Intermediate | 3,381(34%) | 143(15%) | 1,110(100%) | 40 (5.6%) | 1 (0.3%) | 233(19%) | 946(56%) | 154(16%) | 1 (0.3%) | 717(74%) | 19 (1.2%) | 17 (43%) |
| High | 4,469(45%) | 0 (0%) | 0 (0%) | 0 (0%) | 350(100%) | 1,001(81%) | 159(9.5%) | 792(84%) | 334(100%) | 250(26%) | 1,570(99%) | 13 (33%) |
| Missing | 68 | 0 | 0 | 4 | 0 | 17 | 39 | 0 | 0 | 8 | 0 | 0 |
| Distant Metastasis | | | | | | | | | | | | |
| No | 8,836(89%) | 966(99%) | 1,017(92%) | 709(99%) | 281(80%) | 982(78%) | 1,580(92%) | 753(80%) | 292(87%) | 933(95%) | 1,323(83%) | 0 (-) |
| Yes | 1,133(11%) | 5 (0.5%) | 93 (8.4%) | 5 (0.7%) | 70 (20%) | 269(22%) | 141(8.2%) | 193(20%) | 43 (13%) | 48 (4.9%) | 266(17%) | 0 (-) |
| Missing | 40 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 40 |
| Cancer-Specific Mortality | | | | | | | | | | | | |
| No | 8,067(90%) | 0 (-) | 1,050(95%) | 711(100%) | 305(87%) | 996(80%) | 1,604(93%) | 776(82%) | 305(91%) | 951(97%) | 1,369(86%) | 0 (-) |
| Yes | 931 (10%) | 0 (-) | 60 (5.4%) | 3 (0.4%) | 46 (13%) | 255(20%) | 117(6.8%) | 170(18%) | 30 (9.0%) | 30 (3.1%) | 220(14%) | 0 (-) |
| Missing | 1,011 | 971 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 40 |
| Follow-up time of the censored (year) | | | | | | | | | | | | |
| Median (Q1 - Q3) | 8.7 (6.0 - 11.8) | 9.6 (7.1 - 11.8) | 13.2 (11.7 - 14.5) | 6.0 (5.1 - 6.9) | 10.5 (9.5 - 11.6) | 17.6 (9.1 - 19.7) | 15.1 (7.3 - 17.9) | 13.8 (7.2 - 17.5) | 10.0 (9.1 - 11.8) | 9.3 (8.2 - 10.5) | 6.1 (5.1 - 7.5) | - |
| Min - Max | 0.0 - 24.8 | 0.3 - 24.8 | 0.0 - 17.7 | 0.3 - 8.5 | 0.2 - 12.9 | 0.4 - 22.0 | 0.2 - 21.9 | 0.0 - 20.0 | 0.4 - 13.3 | 0.0 - 12.4 | 1.8 - 11.9 | - |
$^{1}\mathrm{n}$ (%). Note that some percentages may not add up to a hundred percent due to rounding; $^{2}$ Treatment Per Protocol (e.g., randomization assignment); $^{3}$ Active Surveillance; $^{4}$ Radiation Therapy; $^{5}$ Short Term Androgen Deprivation Therapy; $^{6}$ Intermediate Term Androgen Deprivation Therapy; $^{7}$ Long Term Androgen Deprivation Therapy; $^{8}$ Zoledronic Acid; $^{9}$ Abiraterone; $^{10}$ Enzalutamide; $^{11}$ Radiation Therapy Oncology Group
# D. Software and Cybersecurity
ArteraAI Prostate software documentation and software verification and validation testing demonstrate that the device followed all recommendations for basic documentation level as outlined in the FDA guidance document, "Content of Premarket Submissions for Device Software Functions," issued on June 14, 2023. A description of the testing protocols, including pass/fail criteria, and report of results was provided for the verification and validation activities and all testing results met design specifications and passed the acceptance criteria.
ArteraAI Prostate cybersecurity documentation demonstrated that the device met the cybersecurity requirements as outlined in Section 524B of Federal Food, Drug, and Cosmetic Act (FD&C Act). This includes a threat model, software bill of materials, data security training, validation and mitigation of cybersecurity risks, cyber risk management, labeling, cyber testing, and post market cyber vulnerabilities and other information for safeguarding the algorithms.
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V Standards/Guidance Documents Referenced:
1. Guidance for the Content of Premarket Submissions for Device Software Functions; June 2023
2. CLSI document EP12-Ed3: Evaluation of Qualitative, Binary Output Examination Performance; March 2023
3. Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions; September 2023
4. The 510(k) Program: Evaluating Substantial Equivalence in Premarket Notifications [510(k)]; July 2014
5. Guidance for Industry and FDA Staff: De Novo Classification Process (Evaluation of Automatic Class III Designation); October 2021
6. Acceptance of Clinical Data to Support Medical Device Applications and Submissions Frequently Asked Questions; February 2018
7. Guidance for Industry and Food and Drug Administration Staff - Factors to Consider When Making Benefit-Risk Determinations in Medical Device Premarket Approval and De Novo Classifications; August 2019
8. Guidance for Off-the-Shelf Software Use in Medical Devices; August 2023
9. ISO 14971 Third Edition 2019-12 Medical devices - Application of risk management to medical devices
10. IEC 62304 Edition 1.1 2015-06 (2015). Medical device software – Software life cycle processes
11. IEC 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION – Medical devices – Part 1: Application of usability engineering to medical devices
VI Performance Characteristics:
A. Analytical Performance:
The precision of ArteraAI device was evaluated in a between-site reproducibility study which was performed at three laboratory sites in the United States. At each site, slides were scanned by a single operator on a Philips Ultra Fast scanner at 40x objective, with one run per day and five replicates per run, over five non-consecutive days (total number=15). Fifty-two samples (including 6 borderline samples based on ArteraAI Prostate raw score cut-offs) were included in the between-site reproducibility study and these samples were selected from patients with an age at biopsy from 55 years and above, Gleason score 6 to 10, clinical stage T1 to T3, and spanning the low-, intermediate-, and high-risk categories of the device output. The sample characteristics are provided in Table 3 below.
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Table 3. Characteristics of Samples Used in Analytical Studies
| Characteristic | N = 52 |
| --- | --- |
| Age (year), Median, (Min, Max) | 66, (55, 86) |
| PSA (ng/mL), Median, (Min, Max) | 6.95, (1.14, 577.42) |
| Tumor Stage, n (%) | |
| T1 | 35.0 (67.3%) |
| T2 | 15.0 (28.8%) |
| T3 | 2.0 (3.8%) |
| Gleason Grade Group, n (%) | |
| GG 1 | 14.0 (26.9%) |
| GG 2 | 17.0 (32.7%) |
| GG 3 | 11.0 (21.2%) |
| GG 4 | 5.0 (9.6%) |
| GG 5 | 5.0 (9.6%) |
| NCCN Risk Category, n (%) | |
| Very Low/Low | 11.0 (21.2%) |
| Intermediate | 31.0 (59.6%) |
| High/Very High | 10.0 (19.2%) |
| ArteraAI Risk Group (Case-Level Mode) n (%) | |
| Low Risk | 17.0 (32.7%) |
| Intermediate Risk | 20.0 (38.5%) |
| High Risk | 15.0 (28.8%) |
| Borderline Group (Case-Level Mean Within Borderline Threshold), n (%) | |
| Borderline | 6.0 (11.5%) |
| Non-Borderline | 46.0 (88.5%) |
| n (%). Note that some percentages may not add up to a hundred percent due to rounding | |
Summary of Analytical Validation Study Results:
a. Analysis of numeric values of the raw score was performed according to CLSI EP05-A3: Evaluation of Precision of Quantitative Measurement Procedures, 3rd Edition. Within-laboratory, between-site and reproducibility were calculated; in addition, a qualitative analysis (percent of each ArteraAI categories among 15 replicates) was performed and results of these analyses are presented in Table 4 below.
b. Analysis of 10-year DM values for cases with Low- and Intermediate- risk categories was also performed according to the CLSI EP05-A3. Within-laboratory, between-site and reproducibility were calculated; in addition, a qualitative analysis (percent of each ArteraAI categories among 15 replicates) was performed and results of these analyses are presented in Table 5.
c. For ArteraAI raw scores, the %CV for the within-site precision (the same scanner on different days) ranged from 0.1% to 2.8%; the %CV for the between-site precision ranged from 0.0% to 6.0% and %CV for reproducibility ranged from 0.3% to 6.1%.
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d. For ArteraAI DM scores, the $\% \mathrm{CV}$ for the within-site precision (the same scanner on different days) ranged from $0.5\%$ to $5.7\%$ ; the $\% \mathrm{CV}$ for the between-site precision ranged from $0.0\%$ to $12.3\%$ and $\% \mathrm{CV}$ for reproducibility ranged from $1.0\%$ to $12.3\%$ .
Table 4. Within-Site Precision and Reproducibility of ArteraAI Raw Score
| Sample | Mean Raw score | ArteraAI Risk Group (Case-Level Mode) | Borderline Cases | Within-Site | | Between-Site | | Reproducibility (Total) | | Percent Category Agreement Results based on Case-Level Category Call Mode | | | Percent Category Agreement Results | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | SD | %CV | SD | %CV | SD | %CV | Site 1 | Site 2 | Site 3 | Percent Low | Percent Intermediate | Percent High |
| 1 | 0.185 | Low | Non-Borderline | 0.001806 | 1.0 | 0.004039 | 2.2 | 0.004425 | 2.4 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 2 | 0.205 | Low | Non-Borderline | 0.001309 | 0.6 | 0.002012 | 1.0 | 0.002400 | 1.2 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 3 | 0.212 | Low | Non-Borderline | 0.001271 | 0.6 | 0.005407 | 2.6 | 0.005555 | 2.6 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 4 | 0.214 | Low | Non-Borderline | 0.000956 | 0.4 | 0.007615 | 3.6 | 0.007675 | 3.6 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 5 | 0.219 | Low | Non-Borderline | 0.001893 | 0.9 | 0.007039 | 3.2 | 0.007289 | 3.3 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 6 | 0.226 | Low | Non-Borderline | 0.004294 | 1.9 | 0.007521 | 3.3 | 0.008661 | 3.8 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 7 | 0.226 | Low | Non-Borderline | 0.000857 | 0.4 | 0.001573 | 0.7 | 0.001791 | 0.8 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 8 | 0.229 | Low | Non-Borderline | 0.002214 | 1.0 | 0.000000 | 0.0 | 0.002214 | 1.0 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 9 | 0.230 | Low | Non-Borderline | 0.002779 | 1.2 | 0.005070 | 2.2 | 0.005781 | 2.5 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 10 | 0.238 | Low | Non-Borderline | 0.001154 | 0.5 | 0.002927 | 1.2 | 0.003146 | 1.3 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 11 | 0.242 | Low | Non-Borderline | 0.001742 | 0.7 | 0.000497 | 0.2 | 0.001812 | 0.7 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 12 | 0.265 | Low | Non-Borderline | 0.001443 | 0.5 | 0.001743 | 0.7 | 0.002263 | 0.9 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 13 | 0.282 | Low | Non-Borderline | 0.002107 | 0.7 | 0.003652 | 1.3 | 0.004216 | 1.5 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 14 | 0.289 | Low | Non-Borderline | 0.002227 | 0.8 | 0.005834 | 2.0 | 0.006244 | 2.2 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 15 | 0.290 | Low | Non-Borderline | 0.003115 | 1.1 | 0.003817 | 1.3 | 0.004927 | 1.7 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 16 | 0.303 | Low | Borderline | 0.001772 | 0.6 | 0.005988 | 2.0 | 0.006245 | 2.1 | 100.0% | 100.0% | 20.0% | 73% | 27% | 0% |
| 17 | 0.306 | Low | Borderline | 0.001559 | 0.5 | 0.003432 | 1.1 | 0.003769 | 1.2 | 20.0% | 60.0% | 100.0% | 60% | 40% | 0% |
| 18 | 0.312 | Intermediate | Borderline | 0.008688 | 2.8 | 0.001461 | 0.5 | 0.008810 | 2.8 | 80.0% | 80.0% | 100.0% | 13% | 87% | 0% |
| 19 | 0.314 | Intermediate | Borderline | 0.001071 | 0.3 | 0.009940 | 3.2 | 0.009998 | 3.2 | 100.0% | 100.0% | 0.0% | 33% | 67% | 0% |
| 20 | 0.325 | Intermediate | Non-Borderline | 0.002732 | 0.8 | 0.000000 | 0.0 | 0.002732 | 0.8 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 21 | 0.328 | Intermediate | Non-Borderline | 0.001701 | 0.5 | 0.019817 | 6.0 | 0.019890 | 6.1 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 22 | 0.349 | Intermediate | Non-Borderline | 0.003322 | 1.0 | 0.013573 | 3.9 | 0.013974 | 4.0 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 23 | 0.350 | Intermediate | Non-Borderline | 0.002170 | 0.6 | 0.001723 | 0.5 | 0.002771 | 0.8 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 24 | 0.352 | Intermediate | Non-Borderline | 0.004187 | 1.2 | 0.003820 | 1.1 | 0.005668 | 1.6 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 25 | 0.355 | Intermediate | Non-Borderline | 0.001203 | 0.3 | 0.005651 | 1.6 | 0.005777 | 1.6 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 26 | 0.371 | Intermediate | Non-Borderline | 0.001948 | 0.5 | 0.001776 | 0.5 | 0.002636 | 0.7 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 27 | 0.371 | Intermediate | Non-Borderline | 0.001099 | 0.3 | 0.002040 | 0.5 | 0.002317 | 0.6 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 28 | 0.384 | Intermediate | Non-Borderline | 0.001453 | 0.4 | 0.005392 | 1.4 | 0.005584 | 1.5 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
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| Sample | Mean Raw score | ArteraM Risk Group (Case-Level Mode) | Borderline Cases | Within-Site | | Between-Site | | Reproducibility (Total) | | Percent Category Agreement Results based on Case-Level Category Call Mode | | | Percent Category Agreement Results | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | SD | %CV | SD | %CV | SD | %CV | Site 1 | Site 2 | Site 3 | Percent Low | Percent Intermediate | Percent High |
| 29 | 0.390 | Intermediate | Non-Borderline | 0.005359 | 1.4 | 0.004235 | 1.1 | 0.006831 | 1.8 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 30 | 0.397 | Intermediate | Non-Borderline | 0.001491 | 0.4 | 0.005010 | 1.3 | 0.005227 | 1.3 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 31 | 0.400 | Intermediate | Non-Borderline | 0.001195 | 0.3 | 0.003167 | 0.8 | 0.003385 | 0.8 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 32 | 0.407 | Intermediate | Non-Borderline | 0.001038 | 0.3 | 0.001365 | 0.3 | 0.001715 | 0.4 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 33 | 0.413 | Intermediate | Non-Borderline | 0.002663 | 0.6 | 0.003802 | 0.9 | 0.004642 | 1.1 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 34 | 0.420 | Intermediate | Non-Borderline | 0.002113 | 0.5 | 0.014643 | 3.5 | 0.014795 | 3.5 | 100.0% | 100.0% | 40.0% | 0% | 80% | 20% |
| 35 | 0.426 | Intermediate | Non-Borderline | 0.004043 | 1.0 | 0.000000 | 0.0 | 0.004043 | 1.0 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 36 | 0.436 | Intermediate | Borderline | 0.002847 | 0.7 | 0.014866 | 3.4 | 0.015136 | 3.5 | 80.0% | 100.0% | 0.0% | 0% | 60% | 40% |
| 37 | 0.438 | Intermediate | Borderline | 0.002632 | 0.6 | 0.006176 | 1.4 | 0.006714 | 1.5 | 100.0% | 80.0% | 0.0% | 0% | 60% | 40% |
| 38 | 0.445 | High | Non-Borderline | 0.001581 | 0.4 | 0.007081 | 1.6 | 0.007255 | 1.6 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 39 | 0.448 | High | Non-Borderline | 0.004839 | 1.1 | 0.003849 | 0.9 | 0.006183 | 1.4 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 40 | 0.461 | High | Non-Borderline | 0.001674 | 0.4 | 0.014430 | 3.1 | 0.014527 | 3.1 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 41 | 0.472 | High | Non-Borderline | 0.001756 | 0.4 | 0.004479 | 0.9 | 0.004811 | 1.0 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 42 | 0.487 | High | Non-Borderline | 0.004797 | 1.0 | 0.007514 | 1.5 | 0.008915 | 1.8 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 43 | 0.507 | High | Non-Borderline | 0.001724 | 0.3 | 0.001841 | 0.4 | 0.002522 | 0.5 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 44 | 0.513 | High | Non-Borderline | 0.002262 | 0.4 | 0.005683 | 1.1 | 0.006116 | 1.2 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 45 | 0.548 | High | Non-Borderline | 0.004224 | 0.8 | 0.004849 | 0.9 | 0.006431 | 1.2 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 46 | 0.571 | High | Non-Borderline | 0.002129 | 0.4 | 0.003163 | 0.6 | 0.003813 | 0.7 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 47 | 0.587 | High | Non-Borderline | 0.000962 | 0.2 | 0.004616 | 0.8 | 0.004715 | 0.8 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 48 | 0.601 | High | Non-Borderline | 0.001474 | 0.2 | 0.002438 | 0.4 | 0.002849 | 0.5 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 49 | 0.619 | High | Non-Borderline | 0.000929 | 0.2 | 0.003225 | 0.5 | 0.003356 | 0.5 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 50 | 0.707 | High | Non-Borderline | 0.001207 | 0.2 | 0.004154 | 0.6 | 0.004326 | 0.6 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 51 | 0.717 | High | Non-Borderline | 0.000674 | 0.1 | 0.001893 | 0.3 | 0.002009 | 0.3 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| 52 | 0.739 | High | Non-Borderline | 0.005590 | 0.8 | 0.006197 | 0.8 | 0.008345 | 1.1 | 100.0% | 100.0% | 100.0% | 0% | 0% | 100% |
| n: 52 | | | | | | | | | | | | | | | |
{12}
Table 5. Within-Site Precision and Reproducibility of ArteraAI Prostate DM Risk
| Sample | Mean | ArteraAI Risk Group (Case-Level Mode) | Borderline Cases | Within-Site | | Between-Site | | Reproducibility (Total) | | Percent Category Agreement Results based on Case-Level Category Call Mode | | | Percent Category Agreement Results | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | SD | %CV | SD | %CV | SD | %CV | Site 1 | Site 2 | Site 3 | Percent Low | Percent Intermediate | Percent High |
| 1 | 0.022 | Low | Non-Borderline | 0.000238 | 1.1 | 0.000530 | 2.5 | 0.000581 | 2.7 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 2 | 0.024 | Low | Non-Borderline | 0.000193 | 0.8 | 0.000299 | 1.2 | 0.000356 | 1.5 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 3 | 0.025 | Low | Non-Borderline | 0.000199 | 0.8 | 0.000847 | 3.3 | 0.000870 | 3.4 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 4 | 0.026 | Low | Non-Borderline | 0.000153 | 0.6 | 0.001217 | 4.7 | 0.001226 | 4.7 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 5 | 0.027 | Low | Non-Borderline | 0.000319 | 1.2 | 0.001155 | 4.3 | 0.001198 | 4.5 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 6 | 0.028 | Low | Non-Borderline | 0.000783 | 2.8 | 0.001298 | 4.7 | 0.001516 | 5.5 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 7 | 0.028 | Low | Non-Borderline | 0.000144 | 0.5 | 0.000266 | 1.0 | 0.000303 | 1.1 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 8 | 0.028 | Low | Non-Borderline | 0.000381 | 1.4 | 0.000000 | 0.0 | 0.000381 | 1.4 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 9 | 0.028 | Low | Non-Borderline | 0.000478 | 1.7 | 0.000874 | 3.1 | 0.000996 | 3.5 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 10 | 0.030 | Low | Non-Borderline | 0.000206 | 0.7 | 0.000533 | 1.8 | 0.000571 | 1.9 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 11 | 0.031 | Low | Non-Borderline | 0.000324 | 1.1 | 0.000092 | 0.3 | 0.000337 | 1.1 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 12 | 0.035 | Low | Non-Borderline | 0.000308 | 0.9 | 0.000371 | 1.1 | 0.000482 | 1.4 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 13 | 0.039 | Low | Non-Borderline | 0.000495 | 1.3 | 0.000862 | 2.2 | 0.000994 | 2.6 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 14 | 0.041 | Low | Non-Borderline | 0.000561 | 1.4 | 0.001442 | 3.5 | 0.001547 | 3.8 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 15 | 0.041 | Low | Non-Borderline | 0.000797 | 1.9 | 0.000960 | 2.3 | 0.001247 | 3.0 | 100.0% | 100.0% | 100.0% | 100% | 0% | 0% |
| 16 | 0.044 | Low | Borderline | 0.000476 | 1.1 | 0.001619 | 3.7 | 0.001688 | 3.8 | 100.0% | 100.0% | 20.0% | 73% | 27% | 0% |
| 17 | 0.045 | Low | Borderline | 0.000427 | 0.9 | 0.000929 | 2.1 | 0.001023 | 2.3 | 20.0% | 60.0% | 100.0% | 60% | 40% | 0% |
| 18 | 0.047 | Intermediate | Borderline | 0.000314 | 0.7 | 0.002804 | 5.9 | 0.002822 | 5.9 | 100.0% | 100.0% | 0.0% | 33% | 67% | 0% |
| 19 | 0.047 | Intermediate | Borderline | 0.002657 | 5.7 | 0.000407 | 0.9 | 0.002688 | 5.8 | 80.0% | 80.0% | 100.0% | 13% | 87% | 0% |
| 20 | 0.051 | Intermediate | Non-Borderline | 0.000835 | 1.7 | 0.000000 | 0.0 | 0.000835 | 1.7 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 21 | 0.052 | Intermediate | Non-Borderline | 0.000520 | 1.0 | 0.006351 | 12.3 | 0.006372 | 12.3 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 22 | 0.059 | Intermediate | Non-Borderline | 0.001271 | 2.2 | 0.004875 | 8.3 | 0.005038 | 8.6 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 23 | 0.059 | Intermediate | Non-Borderline | 0.001542 | 2.6 | 0.001350 | 2.3 | 0.002050 | 3.5 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 24 | 0.059 | Intermediate | Non-Borderline | 0.000765 | 1.3 | 0.000608 | 1.0 | 0.000977 | 1.7 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 25 | 0.061 | Intermediate | Non-Borderline | 0.000428 | 0.7 | 0.002067 | 3.4 | 0.002111 | 3.5 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 26 | 0.066 | Intermediate | Non-Borderline | 0.000774 | 1.2 | 0.000702 | 1.1 | 0.001045 | 1.6 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 27 | 0.067 | Intermediate | Non-Borderline | 0.000435 | 0.7 | 0.000812 | 1.2 | 0.000921 | 1.4 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 28 | 0.072 | Intermediate | Non-Borderline | 0.000631 | 0.9 | 0.002338 | 3.2 | 0.002422 | 3.4 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 29 | 0.074 | Intermediate | Non-Borderline | 0.002295 | 3.1 | 0.001834 | 2.5 | 0.002938 | 3.9 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 30 | 0.078 | Intermediate | Non-Borderline | 0.000682 | 0.9 | 0.002326 | 3.0 | 0.002424 | 3.1 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 31 | 0.079 | Intermediate | Non-Borderline | 0.000565 | 0.7 | 0.001490 | 1.9 | 0.001594 | 2.0 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
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| Sample | Mean | ArteraAI Risk Group (Case-Level Mode) | Borderline Cases | Within-Site | | Between-Site | | Reproducibility (Total) | | Percent Category Agreement Results based on Case-Level Category Call Mode | | | Percent Category Agreement Results | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | SD | %CV | SD | %CV | SD | %CV | Site 1 | Site 2 | Site 3 | Percent Low | Percent Intermediate | Percent High |
| 32 | 0.082 | Intermediate | Non-Borderline | 0.000506 | 0.6 | 0.000665 | 0.8 | 0.000836 | 1.0 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 33 | 0.085 | Intermediate | Non-Borderline | 0.001342 | 1.6 | 0.001908 | 2.2 | 0.002332 | 2.7 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 34 | 0.089 | Intermediate | Non-Borderline | 0.001160 | 1.3 | 0.007888 | 8.8 | 0.007972 | 8.9 | 100.0% | 100.0% | 40.0% | 0% | 80% | 20% |
| 35 | 0.092 | Intermediate | Non-Borderline | 0.002180 | 2.4 | 0.000000 | 0.0 | 0.002180 | 2.4 | 100.0% | 100.0% | 100.0% | 0% | 100% | 0% |
| 36 | 0.098 | Intermediate | Borderline | 0.001628 | 1.7 | 0.008692 | 8.9 | 0.008843 | 9.0 | 80.0% | 100.0% | 0.0% | 0% | 60% | 40% |
| 37 | 0.099 | Intermediate | Borderline | 0.001563 | 1.6 | 0.003636 | 3.7 | 0.003958 | 4.0 | 100.0% | 80.0% | 0.0% | 0% | 60% | 40% |
| n: 37 | | | | | | | | | | | | | | | |
# B Clinical Performance:
The clinical performance of the ArteraAI Prostate device was evaluated in a retrospective clinical study which included a total of 886 patients across three sites in the US. The dataset for pivotal clinical performance study included patients with non-metastatic prostate cancer diagnosed since 2005 without clinically or pathologically defined metastases. Patients across 3 US sites were considered eligible if age at date of biopsy was 55 years of age and older with clinical T-stage T1-T4 (T1a, T1b, T1c, T1, T2a, T2b, T2c, T2, T3a, T3b, T3c, T4a, T4b, T4c, T4), baseline median PSA value closest to the biopsy were $6.2\mathrm{ng / mL}$ , and Gleason score at diagnosis was 6-10. The intended patient should also have been a candidate for curative intent management (surgery, radiation therapy with or without systemic therapy), or active surveillance. Patients were required to have non-metastatic prostate cancer and at least one H&E slide containing at least one FFPE biopsy core with the highest Gleason grade tumor as diagnosed by the pathologist. The slides were scanned to a digital image format using the Philips Ultra Fast Scanner. Patients with prior or concurrent malignancy (except non-melanoma skin cancer) within the 5 years prior to prostate cancer diagnosis, recurring cancer, metastatic disease at diagnosis or patients who received only palliative care were excluded from the study resulting in pivotal clinical performance cohort of $\mathbf{N} = 886$ .
The summary of patient characteristics for the pivotal clinical performance study is presented in Table 6 below.
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Table 6. Summary of Clinical Validation Patient Cohort Characteristics
| Variables | Overall N = 886^{1} |
| --- | --- |
| Sites, n(%) | |
| Site 1 | 290 (33%) |
| Site 2 | 444 (50%) |
| Site 3 | 152 (17%) |
| Treatment Per Protocol, n(%) | |
| Active Surveillance | 314 (36%) |
| Radiation Therapy
(With or without Androgen Deprivation Therapy) | 203 (23%) |
| Radical Prostatectomy | 354 (41%) |
| Missing | 15 |
| Age at time of biopsy | |
| Median (Q1 - Q3) | 65 (61 - 70) |
| Min - Max | 55 - 98 |
| Race, n(%) | |
| Black | 72 (8.1%) |
| White | 675 (76%) |
| Other | 133 (15%) |
| Unknown | 6 (0.7%) |
| PSA (ng/mL) at time of biopsy | |
| Median (Q1 - Q3) | 6.2 (4.6 - 9.6) |
| Clinical Tumor Stage, n(%) | |
| T1a | 3 (0.3%) |
| T1b | 1 (0.1%) |
| T1c | 579 (65%) |
| T2 | 2 (0.2%) |
| T2a | 178 (20%) |
| T2b | 48 (5.4%) |
| T2c | 46 (5.2%) |
| T3a | 20 (2.3%) |
| T3b | 6 (0.7%) |
| T4 | 3 (0.3%) |
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| Variables | Overall N = 886^{1} |
| --- | --- |
| Gleason Grade Group at time of biopsy, n(%) | |
| 1 | 372 (42%) |
| 2 | 220 (25%) |
| 3 | 132 (15%) |
| 4 | 97 (11%) |
| 5 | 64 (7.2%) |
| Missing | 1 |
| NCCN risk group (3-level), n(%) | |
| Low | 313 (35%) |
| Intermediate | 358 (40%) |
| High | 206 (23%) |
| N1-3^{2} | 7 (0.8%) |
| Missing | 2 |
| Follow-up time of the censored (year) | |
| Median (Q1 - Q3) | 8.2 (6.2 - 11.2) |
| Min - Max | 0.1 - 18.7 |
| 1n (%). Note that some percentages may not add up to a 100% due to rounding
2Clinically node positive patients, not applicable for NCCN risk grouping | |
## Summary of Clinical Validation Results:
a. 10-Year Risk of DM for ArteraAI Prostate Risk Categories (High, Intermediate, Low)
The prognostic ability of the ArteraAI Prostate was evaluated for 10-year risk of DM.
The estimates of 10-year risks of DM for ArteraAI Prostate Risk categories along with two-sided 95% CI are presented in Table 7 and Figure 2 below.
The results of the pivotal clinical performance study support that:
i. 10-year risk of DM for ArteraAI Prostate Risk category High (28.1%) is statistically significantly higher than the overall risk (8.1%) and this difference (20.0%) is clinically significant.
ii. 10-year risk of DM for ArteraAI Prostate Risk category Low (3.3%), is statistically significantly lower than the overall risk (8.1%) and this difference (4.8%) is clinically significant.
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Table 7. 10-Year Risks of DM for Artera AI Prostate Risk Categories
| ArteraAI Prostate Risk Category | Total Number | Number of DM for 10 years | Estimated 10-year Risk of DM (95% CI) * | Percentage of Patients with the Risk Category (Total/886) |
| --- | --- | --- | --- | --- |
| High | 144 | 30 | 28.1% (19.4%-37.5%) | 16.3% |
| Intermediate | 214 | 12 | 6.6% (3.6%-10.8%) | 24.2% |
| Low | 528 | 13 | 3.3% (1.8%-5.6%) | 59.6% |
| Total | 886 | 55 | Estimated overall risk (95% CI): 8.1% (6.1%-10.4%) | |
* The estimated 10-year risk of DM and 95% CI were calculated by Kaplan-Meier survival analysis.
Figure 2. Kaplan-Meier curves for 10-Year Risk of DM for ArteraAI Prostate Risk Categories (High, Intermediate, Low)
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b. 10-Year Risk of PCSM for ArteraAI Prostate Risk Categories (High, Intermediate, Low)
The prognostic ability of the ArteraAI Prostate was evaluated for 10-year risk of PCSM. Estimates of 10-year risks of PCSM for ArteraAI Prostate Risk categories along with two-sided 95% CI are presented in Table 8 and Figure 3.
The results of the pivotal clinical performance study support that:
i. 10-year risk of PCSM for ArteraAI Prostate Risk category High (10.2%), is statistically significantly higher than the overall risk (2.3%) and this difference (7.9%) is clinically significant.
ii. 10-year risk of PCSM for ArteraAI Prostate Risk category Low (0.6%), is statistically significantly lower than the overall risk (2.3%) and this difference (1.7%) is clinically significant.
Table 8. 10-year Risk for PCSM for ArteraAI Prostate Risk Categories
| ArteraAI Prostate Risk Category | Total Number | Number of PCSM for 10 years | Estimated 10-year Risk of PCSM (95% CI) * | Percentage of Patients with the Risk Category (Total/886) |
| --- | --- | --- | --- | --- |
| High | 144 | 9 | 10.2% (4.7% - 18.2%) | 16.3% |
| Intermediate | 214 | 2 | 1.1% (0.2% - 3.7%) | 24.2% |
| Low | 528 | 2 | 0.6% (0.1% - 2.0%) | 59.6% |
| Total | 886 | 13 | Estimated overall risk (95% CI): 2.3% (1.2% - 3.8%)) | |
* The estimated 10-year risk of DM and 95% CI were calculated by Kaplan-Meier survival analysis.
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Figure 3. Kaplan-Meier curves for 10-Year Risk of PCSM for ArteraAI Prostate Risk Categories (High, Intermediate, Low)
c. Subgroup Analysis for 10-Year Risk of DM for ArteraAI Prostate Risk Categories (Low, Intermediate, High)
# i. African American Vs Non-African American
This subgroup analysis shows that the ArteraAI Prostate risk categories for 10-year risk of distant metastasis outputs are validated between African American and Non-African American patients. A higher 10-year DM risk estimates for African American patients vs non-African American patients for ArteraAI categories High (35.6% vs 27.4%) and Low (9.0% vs 2.9%), and overall risk (13.5% vs 7.7%) was observed (Table 9). The number of patients from African American patient group was limited (72) and this should be taken in consideration when using the risk estimates provided by ArteraAI Prostate for African American patients.
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Table 9. 10-year Risk of DM for African American Patients
| African American Patients (N=72) | | | | |
| --- | --- | --- | --- | --- |
| ArteraAI Prostate Risk Category | Total Number | Number of DM for 10 Years | Estimated 10-year Risk of DM, (95%CI) | Percentage of Patients with the Risk Category |
| High | 10 | 2 | 35.6% (1.6%-77.2%) | 13.9% |
| Intermediate | 26 | 2 | 8.7% (1.4%-24.8%) | 36.1% |
| Low | 36 | 2 | 9.0% (1.3%-26.3%) | 50.0% |
| Total | 72 | 6 | Estimated overall 10-year DM risk, 95%CI: 13.5% (5.1%-26.1%) | |
Table 10. 10-year risk for DM for Non-African American Patients
| Non-African American Patients (N=814) | | | | |
| --- | --- | --- | --- | --- |
| ArteraAI Prostate Risk Category | Total Number | Number of DM for 10 years | Estimated 10-year Risk of DM, (95%CI) | Percentage of Patients with the Risk Category |
| High | 134 | 28 | 27.4% (18.6%-36.9%) | 16.5% |
| Intermediate | 188 | 10 | 6.3% (3.2%-10.8%) | 23.1% |
| Low | 492 | 11 | 2.9% (1.5%-5.2%) | 60.4% |
| Total | 814 | 49 | Estimated overall 10-year DM risk, 95%CI: 7.7% (5.7%-10.0%) | |
d. Different Treatment Groups
This subgroup analysis shows that the ArteraAI Prostate risk categories for 10-year risk of distant metastasis outputs are validated across patients treated with all different treatment regimens related to nonmetastatic prostate cancer (Table 11). This subgroup analysis stratified by different types of treatment [Active surveillance (n=314), Radiation therapy (n=203) and radical prostatectomy (n=354)] was performed and ArteraAI Prostate risk estimates were acceptable for each treatment group.
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Table 11. 10-year risk of DM for patients with different treatments
| Treatment Subgroup (N=871*) (all patients with known treatment types) | ArteraAI Prostate Risk Category (N) | Number of DM for 10 Years | Estimated 10-year Risk of DM (95% CI) | Percentage of Patients with the Risk Category (N=871) |
| --- | --- | --- | --- | --- |
| Active Surveillance (N=314) | High (N=24) | 5 | 23.1% (8.0%-42.8%) | 2.8% |
| | Intermediate (N=56) | 1 | 2.1% (0.2%-9.9%) | 6.4% |
| | Low (N=234) | 3 | 2.4% (0.6%-6.7%) | 26.9% |
| Radiation Therapy (N=203) | High (N=64) | 16 | 33.4% (19.6%-47.8%) | 7.3% |
| | Intermediate (N=47) | 5 | 13.6% (4.8%-26.8%) | 5.4% |
| | Low (N=92) | 3 | 3.5% (0.9%-9.0%) | 10.6% |
| Radical Prostatectomy (N=354) | High (N=53) | 8 | 22.6% (9.8%-38.6%) | 6.1% |
| | Intermediate (N=107) | 6 | 6.3% (2.6%-12.6%) | 12.3% |
| | Low (N=194) | 6 | 3.8% (1.5%-7.8%) | 22.3% |
* For 15 out 886 patients, treatment type information was not available.
e. Additional study: Samples with more than one highest Gleason Grade slides
In addition, a study was conducted for cases with multiple slides containing the highest Gleason grade, 15 cases including 14 cases with 2 slides and 1 case with 3 slides which had the same highest Gleason grade. One out of 15 cases (6.7%) had different ArteraAI Prostate risk categories. In real-life settings, all slides with same highest Gleason grade should be analyzed by the ArteraAI Prostate device and the highest risk category is provided in the patient ArteraAI report.
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VII Pre-Determined Change Control Plan
The ArteraAI Prostate includes a pre-determined change control plan (PCCP) approved by the US Food and Drug Administration (FDA). The PCCP provides an overview of the planned modifications which is to add additional FDA cleared WSI scanners as intended use components. As outlined in the PCCP, each modification is designed to address specific differences in device input, ensuring consistent performance and prognostic accuracy. Verification and validation testing will ensure that software updates made to add interoperability with additional FDA cleared scanners will not have an impact on existing interoperable scanners or other functionality. The verification/validation process for each additional scanner is same as the validation process used to show interoperability with the Philips Ultra Fast Scanner that is authorized as part of this De Novo submission.
Specific validation study protocols and acceptance criteria are also detailed in the PCCP to ensure that device maintains the following performance characteristics for the stated modification:
- Addition of additional FDA cleared whole slide image (WSI) scanners as intended use components (Interoperability to an additional WSI scanner)
Per ArteraAI’s change control procedure, a change request for the following changes will be created:
i. Update the User Interface to include an additional interoperable scanner in the file upload workflow.
ii. Update the Back End to verify image metadata from files from the new interoperable scanner.
iii. If necessary: Update the Image Converter component to convert compatible files from the new scanner to the expected format for the AI Engine.
Upon successful validation, labeling will be updated in accordance with the authorized PCCP to provide users with current information regarding the device’s interoperable scanner.
VIII Proposed Labeling:
The labeling supports the decision to grant the De Novo request for this device.
IX Identified Risks and Mitigations:
| Risks to Health | Mitigation Measures |
| --- | --- |
| Risk of false positive, false negative, or failure to provide a result. | Certain design verification and validation activities, including certain analytical and clinical studies.
Certain labeling information, including certain performance information and limitations. |
| Incorrect interpretation of test results by the user. | Certain design verification and validation activities.
Certain labeling information, including certain performance information and limitations. |
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X Benefit/Risk Assessment:
A Summary of the Assessment of Benefit:
ArteraAI Prostate device provides 10-year categorical risk (High, Intermediate, Low) for DM and PCSM. The device also provides a 10-year individual risk estimate of DM for Low and Intermediate risk groups. These risk estimates in the IU population are intended to help physicians make more informed treatment decisions. The device may help in reducing under or over treatment of patients by estimating the risk of DM.
B Summary of the Assessment of Risk:
The probable risks associated with the use of this device are mainly due to erroneous results and incorrect use and interpretation of test results by the healthcare providers. Incorrect test results may be due the prognostic ArteraAI Prostate 10-year categorical risk (High, Intermediate, Low) for DM and PCSM being reported as higher or lower than true risk and the individual risk estimate of DM for Low and Intermediate risk groups being reported as higher or lower than true risk. In both scenarios above, there is probable risk of mismanagement of patient care in accordance with professional guidelines, based on false test results from this test, or incorrect interpretation of test results.
C Patient Perspectives:
This submission did not include specific information on patient perspectives for this device.
D Summary of the Assessment of Benefit-Risk:
The probable benefit of this device was demonstrated by analytical and clinical validation studies (refer to Section VI Performance Characteristics for details). The clinical performance of ArteraAI device was evaluated in a clinical study which included a total of 886 patients across three sites in the US. The pivotal clinical performance study showed that the 10-year risk of DM for ArteraAI Prostate risk category High (28.1%) is statistically significantly higher than the overall risk (8.1%) and this difference (20.0%) is clinically significant. The 10-year risk of DM for ArteraAI Prostate category Low (3.3%) is statistically significantly lower than the overall risk (8.1%) and this difference (4.8%) is clinically significant.
False test results from this test, or incorrect interpretation of test results, could result in improper medical management of patients. The probable risks associated with false test results includes prognostic ArteraAI Prostate 10-year categorical risk (High, intermediate, Low) for DM and PCSM and prognostic ArteraAI 10-year individual risk estimate of DM for Low and Intermediate risk groups being reported as higher or lower than the true risk. These risks are mitigated by adequate analytical and clinical performance of the device. The probable risks associated with incorrect interpretation of test results are mitigated by inclusion of adequate instructions in the labeling on proper use of the device within the clinical workflow. Further, the
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test results are unlikely to be the only factor considered while making clinical decisions. These results may support risk-based decisions within recommended guidelines.
While general controls are insufficient to ensure the safety and effectiveness of the device, in light of the mitigations provided by the special controls, the probable benefits outweigh the probable risks for the use of the ArteraAI Prostate device.
XI Conclusion:
The De Novo request is granted, and the device is classified under the following and subject to the special controls identified in the letter granting the De Novo request:
Product Code(s): SFH
Device Type: Software algorithm device analyzing digital images for cancer prognosis
Class: II
Regulation: 21 CFR 864.3755
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