DEN130015 · Gauss Surgical, Inc., · PBZ · May 9, 2014 · General Hospital
Device Facts
Record ID
DEN130015
Device Name
PIXEL 3 SYSTEM
Applicant
Gauss Surgical, Inc.,
Product Code
PBZ · General Hospital
Decision Date
May 9, 2014
Decision
DENG
Submission Type
Direct
Regulation
21 CFR 880.2750
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
The Pixel 3 System is a software application intended to be used as an adjunct in the estimation of blood loss and management of surgical sponges. The Pixel 3 System is intended to be used with surgical sponges, software, hardware and accessory devices which have been validated for use with the Pixel 3 System to estimate the hemoglobin (Hb) mass contained on used surgical sponges. The Pixel 3 System is also intended to calculate an estimate of blood volume on used surgical sponges from the estimated Hb mass and a user-entered patient serum Hb value. The validated surgical sponges, hardware, software, accessory devices and Hb mass ranges are listed in the Instructions for Use. The Pixel 3 System is also indicated for use to aid in counting surgical sponges and may be used to record and display case-specific blood components infused over time. The Pixel 3 System is additionally indicated for use to aid in managing surgical sponges, including providing a visual record of sponge images, and to record the user-entered weight of used surgical sponges in order to calculate an estimate of fluid volume on the sponges.
Device Story
Pixel 3 System is a mobile medical application running on an iPad; used by circulating nurses in the OR to manage surgical sponges and estimate blood loss. Input: images of used surgical sponges captured via iPad camera; user-entered patient serum Hb levels; user-entered sponge weights. Operation: software analyzes sponge images sent to an off-site server to estimate hemoglobin mass (sHbL); calculates cumulative blood volume (sEBL) using sHbL and patient Hb. Output: real-time display of sHbL, sEBL, cumulative error (Bland-Altman limits), and sponge counts. Clinical use: provides an adjunct to visual/gravimetric estimation; aids in fluid management decisions. Benefits: higher consistency/precision than visual/gravimetric methods; provides visual record of sponges; assists in sponge accountability to prevent retained items.
Clinical Evidence
Two prospective clinical studies conducted. Study 1 (46 patients, 758 sponges): demonstrated significant positive linear correlation (r=0.93) between Pixel 3 sHbL and reference photometric assay. Study 2 (50 patients, 791 sponges): confirmed accuracy across four intraoperative intervals (r=0.90-0.92). Pixel 3 showed higher precision and lower variance compared to visual and gravimetric methods. Bias increased monotonically during cases (0.1g to 3.7g Hb).
Technological Characteristics
Mobile software application on Apple iPad2 (Model A1395); uses wireless foot pedal (AirTurn BT-105). Sensing principle: optical image analysis of surgical sponges. Connectivity: networked to off-site server for image processing. Software: moderate level of concern; includes ambient light indicator and camera-bounding box for image capture. Sterilization: N/A (iPad kept outside sterile field).
Indications for Use
Indicated for use as an adjunct in blood loss estimation and surgical sponge management in patients undergoing surgical procedures. Intended for use by surgical personnel to estimate hemoglobin mass and blood volume on validated surgical sponges, aid in sponge counting, and record fluid management data.
Regulatory Classification
Identification
An image processing device for estimation of external blood loss is a device to be used as an aid in estimation of patient external blood loss. The device may include software and/or hardware that is used to process images capturing externally lost blood to estimate the hemoglobin mass and/or the blood volume present in the images.
Special Controls
In combination with the general controls of the Food, Drug & Cosmetic Act, the Image processing device for estimation of external blood loss is subject to the following special controls:
*Classification.* Class II (special controls). The special controls for this device are:(1) Non-clinical performance data must demonstrate that the device performs as intended under anticipated conditions of use. Demonstration of the performance characteristics must include a comparison to a scientifically valid alternative method for measuring deposited hemoglobin mass. The following use conditions must be tested:
(i) Lighting conditions;
(ii) Range of expected hemoglobin concentrations;
(iii) Range of expected blood volume absorption; and
(iv) Presence of other non-sanguineous fluids (
*e.g.,* saline irrigation fluid).(2) Human factors testing and analysis must validate that the device design and labeling are sufficient for appropriate use by intended users of the device.
(3) Appropriate analysis and non-clinical testing must validate the electromagnetic compatibility (EMC) and wireless performance of the device.
(4) Appropriate software verification, validation, and hazard analysis must be performed.
(5) Software display must include an estimate of the cumulative error associated with estimated blood loss values.
(6) Labeling must include:
(i) Warnings, cautions, and limitations needed for safe use of the device;
(ii) A detailed summary of the performance testing pertinent to use of the device, including a description of the bias and variance the device exhibited during testing;
(iii) The validated surgical materials, range of hemoglobin mass, software, hardware, and accessories that the device is intended to be used with; and
(iv) EMC and wireless technology instructions and information.
Submission Summary (Full Text)
{0}------------------------------------------------
## DE NOVO CLASSIFICATION REQUEST FOR PIXEL 3 SYSTEM
### REGULATORY INFORMATION
FDA identifies this generic type of device as:
Image processing device for estimation of external blood loss: An image processing device for estimation of external blood loss is a device to be used as an aid in estimation of patient external blood loss. The device may include software and/or hardware that is used to process images capturing externally lost blood to estimate the hemoglobin mass and/or the blood volume present in the images.
NEW REGULATION NUMBER: 21 CFR 880.2750
CLASSIFICATION: II
PRODUCT CODE: PBZ
## BACKGROUND
DEVICE NAME: PIXEL 3 SYSTEM
SUBMISSION NUMBER: K130190
DATE OF DE NOVO: FEBRUARY 4, 2013
CONTACT: GAUSS SURGICAL. INC. % Peggy McLaughlin, Consulting Vice President, Regulatory AFFAIRS 334 STATE STREET SUITE 201 LOS ALTOS, CA 94022
#### REQUESTER'S RECOMMENDED CLASSIFICATION: II
#### INDICATIONS FOR USE
The Pixel 3 System is a software application intended to be used as an adjunct in the estimation of blood loss and management of surgical sponges.
The Pixel 3 System is intended to be used with surgical sponges, software, hardware and accessory devices which have been validated for use with the Pixel 3 System to estimate the hemoglobin (Hb) mass contained on used surgical sponges. The Pixel 3 System is also intended to calculate an estimate of blood volume on used surgical sponges from the estimated Hb mass and a user-entered patient serum Hb value. The validated surgical sponges, hardware, software, accessory devices and Hb mass ranges are listed in the Instructions for Use.
{1}------------------------------------------------
The Pixel 3 System is also indicated for use to aid in counting surgical sponges and may be used to record and display case-specific blood components infused over time. The Pixel 3 System is additionally indicated for use to aid in managing surgical sponges, including providing a visual record of sponge images, and to record the user-entered weight of used surgical sponges in order to calculate an estimate of fluid volume on the sponges.
## LIMITATIONS
The sale, distribution, and use of the Pixel 3 System are restricted to prescription use in accordance with 21 CFR 801.109.
Limitations on device use are also achieved through the following statements included in the Instructions for Use:
Warning: "The device is MR Unsafe. Do not bring the device into an MR environment. The device must not be used in an MR environment."
Warning: "The table computer (iPad) is not a sterile device and should remain outside the sterile field."
Warning: "Information provided by Pixel 3 should not be used as a "trigger" for any clinical action. Patient vital signs such as blood pressure, heart rate, pulse pressure variability, central venous pressure, urine output, respiratory rate, pulse oximeter readings, laboratory-derived Hb, cardiac output, the general clinical presentation of the patient, and your clinical practices should also be used to evaluate the patient before making significant clinical decisions. When the clinical presentation of the patient does not appear consistent with the sHbL [estimated Hb mass lost onto the sponge] or sEBL [estimated cumulative blood volume lost onto the sponges] readings, estimating blood loss by another method (e.g., gravimetric method and/or visual estimation) may be warranted."
"The Pixel 3 System's sHbL estimates have only been validated for patient hemoglobin levels from 5 to 17 g/dl and sponges containing up to 6.0 g of hemoglobin."
"The Pixel 3 System will not provide sHbL and sEBL by sHbL outputs for out-of-range sponges but out-of-range sponges will be counted for the total sponge count. You should estimate blood loss on out-of-range sponges via alternate methods (e.g., gravimetric method and/or visual estimation)."
"sHbL (and the ensuing calculated sEBL) only represent the Hb mass and blood that is estimated to be present on the sponge at the time of scanning. This information is only one aspect of blood loss estimation."
"The sEBL calculator is simply an aid in the assessment of total blood loss (in ml) based on a user-input laboratory-derived Hb value. The accuracy of the sEBL displayed is dependent on the timeliness of the user-entered laboratory-derived Hb concentration of the patient."
{2}------------------------------------------------
"The effect of other materials (e.g., bile, stool, urine, colored irrigation fluids or contrast dyes) on the accuracy of the Pixel 3 System's outputs is unknown."
"Validated hardware, surgical materials and optional accessories (not provided by Gauss Surgical, Inc.)
- iPad2 Model Number A1395 (EMC 2560) running iOS 6.1 (Contact Gauss prior to updating the iPad operating system), Apple Inc.
- . Surgical sponges:
- 0 NovaPlus™ Lap Sponges 18x18
- 0 AMD Ritmed 18x18 Laparotomy Sponges
- 0 RFDetect Premium 18x18 Laparotomy Sponges
- 0 Allegiance® Disposable 18x18 Lap Sponges
- . AirTurn BT-105 with 2 ATFS-2 Pedals and Pedal Board; AirTurn, Inc., www.airturn.com"
# PLEASE REFER TO THE LABELING FOR A MORE COMPLETE LIST OF WARNINGS AND PRECAUTIONS.
## DEVICE DESCRIPTION
The Pixel 3 System is a software program (mobile medical application) used on an Apple iPad® tablet to capture images of used surgical sponges to assist surgical personnel in the management of surgical sponges after surgical use and to aid in the estimation of blood loss. The main functions of the device are summarized below.
The Pixel 3 System provides an estimate of the Hb mass lost onto the sponge (sHbL), which is derived from a software algorithm that analyzes images of sponges sent to the Gauss off-site server along with user-entered information about the type of sponge. An estimate of the cumulative blood volume lost onto the sponges (sEBL) is subsequently calculated by dividing the sHbL for each sponge by a user-entered value for the patient's laboratory-derived serum Hb level at the time of image capture. Whereas sHbL is estimated independently from the laboratory-derived serum Hb (i.e., directly from each image), sEBL is derived from a calculator whose inputs are adjustable by the user. The Pixel 3 System provides this estimate of blood content on sponges (i.e., sEBL by sHbL method) and estimate of sHbL only for the validated laparotomy sponge types listed in Table 1.
| System and corresponding validated ranges of HD mass.<br>Sponge Type | Validated Range of<br>Hb Mass |
|----------------------------------------------------------------------|-------------------------------|
| NovaPlus ™ 18x18 Laparotomy Sponges | (b)(4) Trade Secret/CCI |
| AMD Ritmed 18x18 Laparotomy Sponges | |
| RFDetect Premium 18x18 Laparotomy Sponges | |
| Allegiance® Disposable 18x18 Laparotomy Sponges | |
Table 1: Sponge types validated for the sHbL and sEBL by sHbL methods with the Pixel 3 validated ranger o
{3}------------------------------------------------
The Pixel 3 System may also be used to track the weight of soaked surgical sponges recorded by the user. The device may aid in the estimation of blood loss by calculating an estimate of the cumulative sEBL by weight, provided that a dry and wet weight has been entered for each sponge. This estimate (i.e., sEBL by weight method) is based on the total weight of the soaked sponges less their dry weights normalized by the density of whole blood (1.060 g/mL). For the sEBL by weight method, a user may manually enter sponge types other than those validated for the sEBL by sHbL method (see Table 1 above); however, those sponge types can only be used to calculate sEBL by weight.
The Pixel 3 System also allows surgical personnel to categorize sponges by sponge type and provides an automated ongoing count of the total number of sponge images and sponge images by tag. The device allows for the input and display of case-specific values pertaining to fluid management during surgical procedures (e.g., packed red blood cell volume administered over time, fresh frozen plasma volume administered over time, platelet volume administered over time), as detailed in the Instructions for Use. The Pixel 3 System also provides a visual record of images for further evaluation during the surgical case.
To use the device, the user mounts the iPad tablet onto an IV pole; the device contains alignment indicators to help the user align the IV pole. The user then places a sponge in view of the iPad camera (the device contains a camera-bounding box to help the user with sponge placement), and scans an image of the sponge by touching the iPad screen or using an optional wireless foot pedal. The device also contains an ambient light indicator, which helps the user determine when a poor (indicator is yellow) or appropriate (indicator is white) level of ambient light is present for image capture.
The full-screen display of sHbL and sEBL by sHbL outputs includes an estimate of the cumulative error of the Pixel 3 System, computed as the 95% Bland-Altman Limits of Agreement (and denoted as "95% limits Bland Altman" on the display). The display of estimated error is updated on a real-time basis, as successive sponges are accumulated and scanned. A Bland-Altman plot in biostatistics is a method of data plotting used to analyze the agreement between two different assays. Bias is defined as the arithmetic mean of the differences between the device's output value and measurements obtained using a reference standard. The Bland- Altman Limits of Agreement represent two standard deviations (1.96 x SD) of the differences around the bias, and represent the error range within which 95% of all differences between the device's output and the reference standard's measures are expected to lie.
Additional details regarding device operation and user instructions can be found in the Instructions for Use. The Instructions for Use are available on the mobile platform during use by selecting the appropriate icon at the bottom of the menu screen.
The Pixel 3 System has been validated for use with the following hardware, software and optional accessories:
- iPad2 Model Number A1395 (EMC 2560) running iOS 6.1, Apple Inc. .
- 트 AirTurn BT-105 with 2 ATFS-2 Pedals and Pedal Board; AirTurn, Inc.
{4}------------------------------------------------
# SUMMARY OF NONCLINICAL/BENCH STUDIES
The sponsor conducted a series of non-clinical performance testing to demonstrate that the Pixel 3 System would perform as anticipated for its intended use conditions, as described below.
## ELECTROMAGNETIC COMPATIBILITY (EMC) AND WIRELESS TECHNOLOGY
EMC testing was performed per the relevant requirements of IEC 60601-1-2:2007 Medical electrical equipment - Part 1-2: General requirements for basic safety and essential performance - Collateral standard: Electromagnetic compatibility -Requirements and tests. EMC testing was conducted to meet the requirements of Class B. Based on successful completion of the testing, the Pixel 3 System is deemed compliant to the relevant requirements of IEC 60601-1-2:2007.
Wireless coexistence testing was performed, which subjected the Pixel 3 System to increasingly noisy wireless environments and evaluation of whether essential wireless functionality performed as needed. Essential functionality was defined as capturing of a sponge image and verifying that the sHbL was received at the iPad within one minute.
The testing environments consisted of the following conditions:
- 트 WCE1 - Nominal Conditions: Free of Interferers
- I WCE2 – Single WiFi (neighboring channels), Single Bluetooth Interferers:
- 트 WCE3 - Multiple WiFi, Multiple Bluetooth Interferers
- I WCE4 - Multiple WiFi. Multiple Bluetooth. RFID Interferers
- I WCE5 - Multiple WiFi, Multiple Bluetooth, RFID Interferers, Maximum Power
The Pixel 3 System was found to maintain essential wireless functionality under all test conditions.
All interferers were placed within 6 inches of the Equipment Under Test. This distance is noted in the Instructions for Use as a wireless separation distance; all other WiFi and Bluetooth devices should be placed further than this distance from the Pixel 3 iPad and foot pedal. The Pixel 3 was not tested in the presence of MRI, CT, diathermy, and electromagnetic security systems such as metal detectors; this is noted in the Instructions for Use.
## MAGNETIC RESONANCE (MR) COMPATIBILITY
No testing has been conducted to demonstrate whether the device is MR compatible. The labeling includes a Warning that states "The device is MR Unsafe. Do not bring the device into an MR environment. The device must not be used in an MR environment."
## SOFTWARE
The Agency considers the Pixel 3 System to be of a moderate level of concern (LOC) because inaccurate estimated blood loss may result in serious consequences to health.
{5}------------------------------------------------
All of the elements of software information corresponding to moderate LOC devices as outlined in FDA's Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (issued May 11, 2005) have been provided. The sponsor provided adequate documentation describing the software development program. In addition, the sponsor provided documentation that they performed a hazard analysis from both the patient's and user's standpoint, addressed those hazards, and carried out an appropriate validation process. The verification and validation testing documentation provided an acceptable description of the validation and verification activities, which included system level test protocols, the pass/fail criteria, and the results of these activities. In addition, the sponsor provided a description of the cybersecurity issues involved in the control and use of the device, and the mitigation of the risks arising therefrom.
Overall, the software documentation included in the de novo request is in sufficient detail to provide reasonable assurance that the software performs as intended and all softwarerelated risks have been adequately mitigated.
## PERFORMANCE TESTING - BENCH
Bench testing demonstrated that the Pixel 3 System performs as expected under anticipated conditions of use. Bench top verification and validation studies were performed to evaluate the accuracy of the device in comparison to known Hb mass poured on sponges.
# (b)(4) Trade Secret/CCI
. Blood was then poured onto 50 sponges of each type (see below) and normal saline added at various volumes to vary the sponge saturation. Each sponge was scanned with the Pixel 3 System across three ambient light settings (see below) for a [b]4] Trade Secretect scans per sponge type.
Multiple conditions/variables were tested to determine potentially significant covariates, including the following:
- " Sponge type (four brands)
- 0 NovaPlus™ Lap Sponges 18x18
- 0 AMD Ritmed 18x18 Laparotomy Sponges
- 0 RFDetect Premium 18x18 Laparotomy Sponges
- O Allegiance® Disposable 18x18 Lap Sponges
- Source Hb concentration (g/dl)
- O Range: (b)(4) Trade Secreth
- I Fluid volume per sponge (ml)
- o Range:
- Blood volume per sponge (ml) I o Range: 04)m
- I Hb mass per sponge (g)
- o Range: "
- I Blood volume saturation (%)
I
{6}------------------------------------------------
- o Range: Derived from variables listed above
- . Hb mass saturation (%)
- Range: Derived from variables listed above o
- I Brightness/ambient light conditions
- (b)(4) Trade Secret/CCI o
- o Range:
The pre-determined acceptance criterion was (54) Trade Seeel® per sponge for all sponge types and across all Hb mass ranges. The Hb mass bias differed significantly according to the type of sponge and other covariates listed above for sponges overall (p≤0.001); however, the Hb mass bias and EBL bias did not differ significantly among different saline volumes for any sponge type. The limits of agreement (bias ± 2SD) and their corresponding 95% confidence intervals between the Pixel 3 System and the premeasured Hb mass were approximately ± 1.2 g per sponge overall and the differences between the two methods followed a normal distribution with a bias (mean difference) of 0.01 g Hb. Overall, the Pixel 3 System had a strong positive linear correlation (r = 0.92 [95% CI 0.91 to 0.93]) with the reference method (pre-measured Hb mass deposited in controlled amounts).
## PERFORMANCE TESTING - HUMAN FACTORS
Human factors testing and analysis validated that the device design (i.e., user interface) and labeling are sufficient for appropriate use by intended users of the Pixel 3 System (see Table 2). Human factors assessments were used to modify the user interface to promote reasonably safe and effective use of the Pixel 3 System.
| Name of Study | Pixel 3 Usability Study (SW 02089) | | | | | | | | | | | | |
|--------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--|--|--|--|--|--|--|--|--|--|--|--|
| Study Objective | The study explores tasks associated with the use of Pixel 3 that may be confusing or<br>difficult for users based on initial testing and feedback as well as tasks that have been<br>identified in the Hazard Analysis as being a potential source of misinterpretation or<br>subject to judgment. | | | | | | | | | | | | |
| Subject Population | Subjects are registered nurses who make preparations for an operation and continually<br>monitor the patient and staff during its course, who work in the operating room outside<br>the sterile field in which the operation takes place, and who record the progress of the<br>operation, account for the instruments, and handle specimens (commonly known as a<br>circulating nurse). | | | | | | | | | | | | |
| Study Design | Single-center study with two separate arms; one arm focused on live case use and one are<br>focused on simulated use.<br>(b)(4) live surgical case evaluations were completed and 8 simulated task based evaluations<br>were completed. A nurse could participate only once in each arm of the study. Cases<br>enrolled included general surgery, obstetrics, orthopedics, and other specialties. The<br>specific case procedure type and categorization of blood loss per type for the live cases is<br>detailed in the table below. | | | | | | | | | | | | |
| Enrollment | Procedure Type Number of Cases Blood Loss<br>Category Cesarean Section (b)(4) Trade Secret/CCI-<br>46% High Cesarean Section - Simple 8% Medium Open Reduction Internal<br>Fixation Femur 8% Low | | | | | | | | | | | | |
Table 2: Summary of Pixel 3 System Human Factors/Usability Study
{7}------------------------------------------------
| | | (b)(4) Trade Secret/CCI | | |
|-------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------|------|-----------------------------------------------------------------------------|
| | Open Reduction Internal<br>Fixation Ankle | | I 2% | Low |
| | Myomectomy/Hysterectomy | | 8% | Medium |
| | Abdominal Myomectomy, | | | |
| | Total Abdominal | | 15% | Medium |
| | Hysterectomy | | | |
| | | | | High 6, |
| | Total | | 100% | Medium 4, Low |
| | | | | 3 |
| | | | | |
| | For the simulated use arm, the test equipment was set-up in an operating room<br>I | | | |
| | without a patient present per the Instructions for Use (IFU). The simulated case<br>evaluations were conducted as task based scenarios. In each case use scenario, the<br>circulating nurse was observed performing specific tasks with the Pixel 3 System.<br>The test moderator did not interfere with the process. Each task implemented a<br>specific pass or fail criteria, and users were allowed two attempts at each task. If the | | | |
| | | | | |
| | | | | |
| | | | | |
| | user could not complete the task after two attempts, the specific task was recorded as | | | |
| | a fail. The specific tasks evaluated included pairing the Bluetooth foot pedal to the | | | |
| | iPad, assigning sponges to foot pedals, orienting the iPad correctly to prepare it for | | | |
| | scanning, ambient lighting indicator recognition, entering a Hb value on the | | | |
| | Monitoring screen, scanning a sponge within the bounding box, Hb mass is greater<br>than approved range indicator recognition, deleting a scanned sponge and duplicate | | | |
| | sponge, reading sEBL from the user interface, reviewing scans and verifying sponge<br>count prior to closing the case, and closing the case. | | | |
| | | | | |
| | | | | |
| Study Procedure | For the live case use arm, the test equipment was set-up in an operating room per the<br>I<br>IFU prior to the patient entering the room. Users were trained per the IFU<br>approximately one to two weeks prior to use. During the case, the circulating nurse<br>was observed scanning soiled surgical sponges into the Pixel 3 System and user<br>comments and/or observations were noted as appropriate. The test moderator did not<br>interfere with the process. The study device was not utilized to provide any clinical<br>information during surgical cases.<br>At the completion of the simulated or live use, the circulating nurses provided<br>트<br>feedback in three ways:<br>Completed a 15 item questionnaire that evaluated usability of various tasks<br>1.<br>with the Pixel 3 System, scored using 1 to 5 Likert scale with 1=difficult<br>and 5=easy.<br>Addressed three questions with binary (yes/no) responses regarding aspects<br>2. | | | |
| | | | | |
| | | | | |
| | | | | |
| | | | | |
| | | | | |
| | | | | |
| | | | | |
| | | | | |
| | | | | |
| | | | | |
| | | | | |
| | 3. | of safety related to the use of Pixel 3. | | Provided open-ended answers at the end of the questionnaire about different |
| | tasks. | | | |
| | All eight (8) users in the simulated cases were able to successfully complete the tasks<br>■ | | | |
| | per the protocol pass/fail criteria. Ninety-four (94%) of tasks were completed during | | | |
| | the first pass and 100% of tasks were completed during the second pass. In the | | | |
| | yes/no responses, all questions received a positive response. No users thought that | | | |
| | the Pixel 3 posed any potential safety issues to either the nursing staff or patients. | | | |
| Endpoints/Results | Likert scores were between a high of 4.92 and a low of 4.04 for questions addressed<br>트 | | | |
| | after live case use. The average for all responses was 4.57. All answers for the | | | |
| | binary (yes/no) responses were positive except one. The single negative response, | | | |
| | regarding nurse safety, was noted by a user who stated that if the user didn't have | | | |
| | access to eye protection that a sponge might be too close to the face. The same user<br>also recommended that the screen be lowered so that the scanning doesn't cover the | | | |
| | | | | |
| | user's face. Therefore, it was determined by the sponsor that the iPad may have been | | | |
{8}------------------------------------------------
| | set-up too high for that user. |
|--|--------------------------------|
## SUMMARY OF CLINICAL STUDIES
The sponsor conducted two clinical studies with the Pixel 3 System: (1) preliminary clinical testing (Study 1, 46 patients, 758 sponges) and (2) confirmatory clinical testing (Study 2, 50 patients, 791 sponges).
## PRELIMINARY CLINICAL TESTING (STUDY 1)
Following IRB approval, forty-six patients undergoing surgery with anticipated significant blood loss contributed laparotomy sponges for Hb loss estimation using the Pixel 3 System in a prospective, multi-center study. A total of 46 surgical procedures at three (3) clinical sites between July and November 2012 contributed a total of 758 laparotomy sponges (18 in x 18 in, from Cardinal Health, RFDetect, and AMD Ritmed) for analysis. Of these, 167 sponges were analyzed on a per-sponge basis whereas the remaining 591 sponges were analyzed in batches. Pre-operative hemoglobin level (g/dl) was recorded for all but 7 subjects. The mean (±SD) of preoperative Hb was 12.9±1.5 g/dl. The mean (±SD) laparotomy sponge count per case was 17±10. The mean fluid volume (±SD) contained on sponges per case was 668±455 ml. Cases enrolled included gynecology, obstetrics, orthopedics, urology, and general surgery, without regard for the type of procedures. The Pixel 3 system was used to capture scans of surgical laparotomy sponges following the final sponge count at the conclusion of each surgical procedure. The Hb mass loss estimated by the Pixel 3 System (sHbL) was compared to Hb loss measured by a mechanical extraction method (assay sHbL). Accuracy was evaluated using linear regression and Bland-Altman analysis. In addition, the Pixel 3 System's calculation of blood volume loss on sponges (sEBL) was compared with the gravimetric method of estimating blood loss from sponge weights. A significant positive linear correlation (r = 0.93 [95% Cl 0.88 to 0.96]) was noted between the Pixel 3 estimates of cumulative sHbL per case and a cumulative measure of Hb mass obtained from sponges by rinsing and photometric assay of the effluent (reference method). Bland-Altman analysis revealed a bias of 9.0 g Hb per patient between the two methods. The corresponding lower and upper limits of agreement were -7.5 g and 25.5 g per case, compared to the reference method. The sHbL estimation bias of the Pixel 3 system in this study (9.0 g Hb) would be equivalent to roughly 63 ml of allogeneic whole blood from a donor with a laboratory-derived Hb level between 13-15 g/dl. Mean estimated blood loss on sponges using the Pixel 3 system was more accurate than the gravimetric method, which overestimated the Pixel 3 System's estimate by 359 ml per patient (627 ml vs. 268 ml, p<0.0001). Estimates of blood loss using the gravimetric method may be confounded by the presence of non-sanguineous fluids on the sponges (e.g., saline irrigation), whereas the Pixel 3 estimates of blood loss (sEBL) are not.
In the preliminary clinical study (Study 1), a subset of cases (12 of 46) were evaluated using per-sponge estimates, (n=167 sponges). In this subset of cases, three sponges (1.8% of the 167 sponges collected) exceeded the validated range of Hb mass (greater than approximately 6 g Hb per sponge). Sponges from the remaining cases in Study 1 (34 of 46, n=591 sponges) were assayed in batches and were excluded from this analysis.
{9}------------------------------------------------
# CONFIRMATORY CLINICAL TESTING (STUDY 2)
Following IRB approval, fifty patients undergoing elective surgery and caesarean delivery contributed laparotomy sponges for Hb loss estimation in a prospective accuracy study. A total of 50 surgical procedures contributed a total of 791 laparotomy sponges (18in x 18in, RFDetect laparotomy sponges) for analysis. Enrollment was initiated in July 2013 and continued through October 2013 at one (1) clinical site. Preoperative hemoglobin level (g/dl) was recorded for each subject whose case data (sponges) were collected for analysis in this study. Mean (± SD) of preoperative Hb was 12.0 (± 1.6) g/dl and ranged from 7.6 g/dl to 15.5 g/dl. The mean (± SD) sponge count per case was 16 (± 6) and ranged from 8 to 33 sponges per case. The mean fluid volume contained on sponges per case was 667 (± 353) ml. Cases enrolled included gynecology, obstetrics, orthopedics, urology, and other specialties without regard for the type of procedures. The Pixel 3 system was used "live" (intra-operatively) to capture scans of surgical laparotomy sponges as they were removed from the surgical field and counted. The Hb mass loss estimated by the Pixel 3 System (sHbL) was compared to Hb loss measured by the same reference method used in the prior clinical study. Accuracy of total sHbL per patient, and cumulative sHbL across intraoperative intervals was evaluated using linear regression methods and Bland-Altman analysis. A significant positive linear correlation between the Pixel 3 system and the reference method (rinsing and photometric assay of the effluent) was sustained across the four intervals (r = 0.92, 0.90, 0.91, 0.91, p<0.0001, respectively). Across the intervals, bias of cumulative sHbL (g) increased monotonically from 0.1 g (Interval 1, first 25% of sponges scanned) to 3.7 (Interval 4, End of case). The corresponding lowe…
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.