MRI Planner

K211841 · Spectronic Medical AB · MUJ · Aug 25, 2022 · Radiology

Device Facts

• Record ID: K211841
• Device Name: MRI Planner
• Applicant: Spectronic Medical AB
• Product Code: MUJ · Radiology
• Decision Date: Aug 25, 2022
• Decision: SESE
• Submission Type: Traditional
• Regulation: 21 CFR 892.5050
• Device Class: Class 2
• Attributes: AI/ML, Software as a Medical Device

Intended Use

MRI Planner is a software-only medical device intended for use by trained radiation oncologists, dosimetrists and physicists to process images from MRI systems to 1) provide the operator with information of tissue properties for radiation attenuation estimation purposes in photon external beam radiotherapy treatment planning, and to 2) derive contours for input to radiation treatment planning by assisting in localization and definition of healthy anatomical structures. MRI Planner is not intended to automatically contour tumor clinical target volumes. MRI Planner is indicated for radiotherapy planning of adult patients for primary and metastatic cancers in the brain and head-neck regions, as well as soft tissue cancers in the pelvic region. MRI Planner generates synthetic CT images for radiation attenuation estimation purposes for the pelvis, brain and head-neck regions only. MRI Planner generates automatically derived contours of the bladder, colon and femoral heads, for prostate cancer patients only.

Device Story

MRI Planner is a standalone software device for radiation oncology. It takes DICOM MRI image stacks as input. Using pre-trained machine learning models, it transforms MRI data into synthetic CT (sCT) images for radiation attenuation estimation and generates automated contours for specific healthy anatomical structures (bladder, colon, femoral heads in prostate cancer patients). It is used by radiation oncologists, dosimetrists, and physicists in clinical settings. The output is reviewed and modified by the clinician in existing radiotherapy treatment planning software to assist in defining treatment plans. By enabling MRI-only workflows, it potentially reduces the need for additional CT scans, thereby minimizing patient radiation exposure and improving workflow efficiency.

Clinical Evidence

Bench testing only. Dosimetric accuracy evaluated by comparing sCT to conventional CT using mean dose differences and gamma evaluation (3%/3mm for pelvis/head-neck; 2%/2mm for brain). Results showed mean target dose differences of 0.02% ± 0.31% (pelvis) and -0.02% ± 0.25% (head-neck/brain). 100% of cases passed high-dose gamma criteria. Auto-contouring performance evaluated against manual expert delineations using Dice score (DSC) and 95% Hausdorff distance (HD). Average DSC: 0.95 (bladder), 0.90 (colon), 0.96 (femoral heads).

Technological Characteristics

Software-only device; runs on x86-64 systems with NVIDIA GPU (CUDA capable) on Ubuntu Linux 18.04. Utilizes pre-trained machine learning models for synthetic CT generation and anatomical structure segmentation. Complies with ISO 14971, IEC 62304, IEC 62366-1, and IEC 82304-1.

Indications for Use

Indicated for radiotherapy planning of adult patients with primary/metastatic cancers in brain, head-neck, and soft tissue pelvic cancers. Not for automatic tumor/CTV contouring.

Regulatory Classification

Identification

A medical charged-particle radiation therapy system is a device that produces by acceleration high energy charged particles (e.g., electrons and protons) intended for use in radiation therapy. This generic type of device may include signal analysis and display equipment, patient and equipment supports, treatment planning computer programs, component parts, and accessories.

Predicate Devices

• MRCAT Brain (K193109)

Reference Devices

• MRCAT Pelvis (K182888)
• Limbus Contour (K201232)

Submission Summary (Full Text)

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Spectronic Medical AB % Per Bruhn Manager of Quality Assurance and Regulatory Affairs Karbingatan 36 Helsingborg, 25467 SWEDEN

### Re: K211841

Trade/Device Name: MRI Planner Regulation Number: 21 CFR 892.5050 Regulation Name: Medical charged-particle radiation therapy system Regulatory Class: Class II Product Code: MUJ, QKB Dated: July 22, 2022 Received: July 25, 2022

Dear Per Bruhn:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for

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devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email ([e-mail]) or phone [phone] or 301-796-7100).

Sincerely.

for

Julie Sullivan, Ph.D. Assistant Director DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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## Indications for Use

Submission Number (if known)

K211841

Device Name

MRI Planner

Indications for Use (Describe)

MRI Planner is a software-only medical device intended for use by trained radiation oncologists, dosimetrists and physicists to process images from MRI systems to

1) provide the operator with information of tissue properties for radiation attenuation estimation purposes in photon external beam radiotherapy treatment planning, and to

2) derive contours for input to radiation treatment planning by assisting in localization and definition of healthy anatomical structures.

MRI Planner is not intended to automatically contour tumor clinical target volumes.

MRI Planner is indicated for radiotherapy planning of adult patients for primary and metastatic cancers in the brain and head-neck regions, as well as soft tissue cancers in the pelvic region.

MRI Planner generates synthetic OT images for radiation attenuation estimation purposes for the pelvis, brain and head-neck regions only. MRI Planner generates automatically derived contours of the bladder, colon and femoral heads, for prostate cancer patients only.

Type of Use (Select one or both, as applicable)

> Prescription Use (Part 21 CFR 801 Subpart D)

Over-The-Counter Use (21 CFR 801 Subpart C)

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Spectronic Medical

Image /page/3/Picture/2 description: The image shows the logo for Spectronic Medical. The word "SPECTRONIC" is in large, bold, black letters with a thick black line underneath. To the right of the word "SPECTRONIC" are three diagonal pink lines. Below the black line and to the right is the word "MEDICAL" in smaller, bold, black letters.

# 1. 510(k) Summary

K211841

The following summary of the present 510(k) submission is provided:

| Date Prepared | August 25, 2022 |
|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Contact details | Spectronic Medical AB<br>Karbingatan 36<br>254 67 Helsingborg<br>SWEDEN |
| Contact Person | Per Bruhn<br>Manager of Quality Assurance and Regulatory Affairs<br>Spectronic Medical AB<br>Tel: [phone]<br>Email: [e-mail] |
| Device trade name:<br>Common Name:<br>Classification Regulation:<br>Classification Name:<br>Panel:<br>Classification:<br>Product Code: | MRI Planner<br>MRI Planner<br>21 CFR 892.5050<br>Medical charged-particle radiation therapy system<br>Radiology<br>Class II<br>MUJ, QKB |
| Predicate Device | Device name: MRCAT Brain<br>Manufacturer: Philips Medical Systems MR Finland<br>510(k) Clearance: K193109<br>Classification Regulation: 21 CFR 892.5050<br>Classification Name: Medical charged-particle radiation therapy system<br>Classification Panel: Radiology<br>Device Class: II<br>Product Code: MUJ |
| Reference Devices | Reference Device 1:<br>Device name: MRCAT Pelvis<br>Manufacturer: Philips Medical Systems MR Finland<br>510(k) Clearance: K182888<br>Classification Regulation: 21 CFR 892.5050<br>Classification Name: Medical charged-particle radiation therapy system<br>Classification Panel: Radiology<br>Device Class: II<br>Product Code: MUJ<br>Reference Device 2:<br>Device name: Limbus Contour<br>Manufacturer: Limbus AI, Inc.<br>510(k) Clearance: K201232<br>Classification Regulation: 21 CFR 892.2050<br>Classification Name: Medical image management and processing system<br>Classification Panel: Radiology<br>Device Class: II<br>Product Code: LLZ |
| Device Description Summary | The product MRI Planner is a stand-alone software providing information<br>to the treatment planning process prior to radiotherapy. Based on a DICOM |
| | MR image stack, the software generates synthetic CT images that can be<br>used for attenuation calculations in radiotherapy treatment planning for the<br>pelvis, brain and head-neck regions. In addition, the software also<br>generates contours of anatomical structures in the MR image stack, to be<br>used as a starting point for the manual delineation work required in<br>radiotherapy treatment planning. Contours are generated for prostate cancer<br>patients only (bladder, colon and femoral heads).<br><br>MRI Planner utilizes pre-trained machine learning models to perform both<br>the conversion to synthetic CT and the automated structure contouring. The<br>models for synthetic CT generation was trained using a dataset comprising<br>MR and CT images for 244 patients acquired in the treatment position at<br>four hospitals. The model for prostate cancer patient auto contouring was<br>trained using a dataset comprising MR images for 175 patients acquired in<br>the treatment position at four hospitals, together with in-house generated<br>expert manual contours. MRI Planner does not display or store DICOM<br>images. The user is advised to use existing softwares for radiotherapy<br>treatment planning to display and modify generated images and contours. |
| | MRI Planner runs on a standard x86-64 compatible system with a CUDA<br>capable NVIDIA GPU and requires Ubuntu Linux 18.04 operating system. |
| Indications For Use | MRI Planner is a software-only medical device intended for use by trained<br>radiation oncologists, dosimetrists and physicists to process images from<br>MRI systems to |
| | 1) provide the operator with information of tissue properties for radiation<br>attenuation estimation purposes in photon external beam radiotherapy<br>treatment planning, and to |
| | 2) derive contours for input to radiation treatment planning by assisting in<br>localization and definition of healthy anatomical structures. |
| | MRI Planner is not intended to automatically contour tumors or tumor<br>clinical target volumes. |
| | MRI Planner is indicated for radiotherapy planning of adult patients for<br>primary and metastatic cancers in the brain and head-neck regions, as well<br>as soft tissue cancers in the pelvis region. |
| | MRI Planner generates synthetic CT images for radiation attenuation<br>estimation purposes for the pelvis, brain and head-neck regions only. MRI<br>Planner generates automatically derived contours of the bladder, colon and<br>femoral heads, for prostate cancer patients only. |
| Indications for Use comparison | MRI Planner provides the indications for use of the Predicate Device. The<br>Predicate Device has the intended use to provide the operator with<br>information of tissue properties for radiation attenuation estimation<br>purposes in photon external beam radiotherapy treatment planning. |
| | MRI Planner includes the intended use of the Predicate Device, as it<br>provides the operator with information of tissue properties for radiation<br>attenuation estimation purposes in photon external beam radiotherapy<br>treatment planning. Additionally, it provides the functionality of auto<br>contouring, which is not believed to raise additional safety concerns. |
| | As such, the indications for use of MRI Planner does not raise any |
| | additional or different concerns regarding safety or effectiveness as<br>compared to the Predicate Device. |
| Technological comparison | Both MRI Planner and the Predicate Device are machine learning based.<br>Reference Device 1 was used as predicate device for the Predicate Device<br>and is therefore also technologically equivalent. Both the Predicate Device<br>and Reference Device 1 generates similar outputs as MRI Planner in the<br>form of synthetic CT images. Since MRI Planner has similar technological<br>characteristics as both the Predicate Device and Reference Device 1 with<br>regard to synthetic CT generation, no differences in risk have been<br>identified between the products. |
| | Both MRI Planner and Reference Device 2 use pre-trained machine<br>learning models to derive contours. Since MRI Planner has similar<br>technological characteristics as Reference Device 2 with regard to deriving<br>contours, no differences in risk have been identified between the products. |
| Summary of performance<br>testing | Dose accuracy bench test |
| | The conducted bench tests evaluate the dosimetric equivalence of MRI<br>Planner generated synthetic CT (sCT) and conventional CT. Dosimetric<br>agreement was evaluated by comparing mean doses to target and non-target<br>volumes as well as by means of gamma evaluation. The non-target sCT-CT<br>dose difference was evaluated by computing the mean dose difference in<br>all sub-volumes of the dose matrix not overlapping the target. The<br>acceptance criteria was that 99% of cases should have no sub-volumes with<br>an sCT-CT dose difference in excess of 1.0 Gy or 5% of the CT-dose. Two<br>variations of gamma evaluation were conducted; one focusing on the high<br>dose area (cut off at 75% of the maximum dose) and the other considering<br>also the medium dose regions (cut off at 25% of the maximum dose). In the<br>high dose gamma a 3%/3mm criteria was used for the pelvic and head-neck<br>anatomical regions, while a 2%/2mm criteria was used for brain cases. The<br>gamma index passing rate requirement was 99% for pelvis and head-neck,<br>and 98% for brain. In the medium dose range gamma evaluation the stricter<br>2%/2mm criteria was used for all anatomical regions, while requiring a<br>99% gamma index passing rate. |
| | The average sCT-CT mean target dose difference was found to be 0.02% ±<br>0.31% and -0.02% ± 0.25% for the anatomical regions pelvis, and head-<br>neck and brain, respectively. No cases displayed any sub-volumes with<br>sCT-CT dose differences in excess of 5% or 1.0 Gy. |
| | At least 95% of cases met the passing criteria across all gamma evaluations<br>and anatomical regions. In the high dose gamma evaluation, 100.0% of<br>cases passed the individual passing rate criterion for all anatomical regions,<br>while the average gamma index passing rate was 99.9%, 99.8% and 99.8%<br>for pelvis, head neck and brain, respectively. In the medium dose gamma<br>evaluation, 98.3% and 100.0% of cases passed the individual passing rate<br>criterion for pelvis, and head-neck and brain, respectively, while the<br>average gamma index passing rate was 99.7%, 99.5% and 99.9% for pelvis,<br>head neck and brain, respectively. |
| | Dosimetric bench test data for pelvis consisted of MR (T2w) and CT<br>images for 58 unique pelvis cancer patients acquired in the treatment<br>position at six different hospitals. Patient distribution was 16% female and<br>84% male, age range 51-88 years, 41% of patient images were acquired in<br>the US and 59% outside the US. |
| | Dosimetric bench test data for head-neck-brain consisted of MR (T1-<br>Dixon) and CT images for 75 unique head-neck-brain cancer patients<br>acquired in the treatment position at four different hospitals. Patient<br>distribution was 39% female and 64% male, age range 41-85 years, 55% of<br>patient images were acquired in the US and 45% outside the US.<br>MRI data was acquired at six different MRI scanner models, from two<br>different vendors, with field strengths of 1.5T and 3T. |
| | Auto contouring bench test |
| | The conducted bench tests evaluates the automatically generated prostate<br>patient delineations (of bladder, colon and femoral heads) against manual<br>delineations, using two common metrics; Dice score (DSC) and 95%<br>Hausdorff distance (HD). |
| | The average DSC was found to be 0.95 ± 0.03, 0.90 ± 0.04 and 0.96 ± 0.01<br>for bladder, colon and femoral head delineations, respectively. The average<br>95% HD was found to be 2.69 ± 1.82, 4.96 ± 3.91 and 2.04 ± 0.49 for<br>bladder, colon and femoral head delineations, respectively. |
| | Auto contouring bench test data for prostate cancer patients consisted of<br>MR (T2w) images for 51 unique male prostate cancer patients acquired in<br>the treatment position at five different hospitals, together with manually<br>generated delineations of bladder, colon and femoral heads. Patient age<br>range was 51-88 years, 39% of patient images were acquired in the US and<br>61% outside the US. |
| | Manual delineations were generated by two expert truthers using the<br>consensus approach, based on US clinical guidelines. The manual<br>delineations for the bench tests were generated at a separate time from the<br>generation of the training dataset. The truthers were involved in the<br>development of the product and the generation of the training dataset, but<br>not in the training and tuning of the segmentation model. Both truthers<br>were employed by the manufacturer at the time of performing the manual<br>delineations for the bench test. |
| Non-clinical test summary and<br>conclusion | MRI Planner complies with the following international and FDA-<br>recognized consensus standards: |
| | ISO 14971 Second edition 2007-03-01<br>Medical devices – Application of risk management to medical devices |
| | IEC 62304 Edition 1.1 2015-06<br>CONSOLIDATED VERSION Medical device software - Software life<br>cycle processes |
| | IEC 62366-1:2015<br>Medical devices - Part 1: Application of usability engineering to medical<br>devices |
| | IEC 82304-1 Edition 1.0 2016-10<br>Health software – Part 1: General requirements for product safety |
| | Non-clinical verification and validation tests have been performed |
| | |
| with regards to the intended use, the technical claims, the requirement<br>specifications and the risk management results. Non-clinical verification<br>and validation test results demonstrate that MRI Planner:<br>Complies with the aforementioned international and FDA-<br>recognized consensus standards Meets all acceptance criteria as described in the product test<br>description and is adequate for its intended use. | |
| In addition, non-clinical bench tests have been performed to investigate the<br>performance of MRI Planner against the Predicate Device. The bench tests<br>demonstrate that MRI Planner performs comparably to the Predicate<br>Device. | |
| Taking all of the above into account, Spectronic Medical believes that MRI<br>Planner is as safe and effective as the Predicate Device, and is therefore<br>substantially equivalent. |…