aPROMISE is intended to be used by healthcare professionals and researchers for acceptance, transfer, storage, image display, manipulation, quantification and reporting of digital medical images. The system is intended to be used with images acquired using nuclear medicine (NM) imaging using PSMA PET/CT. The device provides general Picture Archiving and Communications System (PACS) tools as well as a clinical application for oncology including marking of regions of interest and quantitative analysis.

Device Description

aPROMISE (automated PROstate specific Membrane Antigen Imaging SEgmentation) consists of a cloud-based software platform with a web interface where users can upload body scans of PSMA PET/CT image data in the form of DICOM files, review patient studies and share study assessments within a team. The software complies with the Digital Imaging and Communications in Medicine (DICOM) 3 standard.

Multiple scans can be uploaded for each patient and the system provides a separate review for each study. The review page display studies in a 4-panel view showing PET, CT, PET/CT fusion and maximum intensity projection (MIP) simultaneously and includes the option to display each view separately. The device is used to review entire patient studies, using image visualization and analysis tools for users to identify and mark regions of interest (ROIs). While reviewing image data, users can mark ROIs by selecting from pre-defined hotspots that are highlighted when hovering with the mouse pointer over the segmented region, or by manual drawing, i.e selecting individual voxels in the image slices to include as hotspots. Selected or drawn hotspots are subject to automatic quantitative analysis. The user can review the results of this quantitative analysis and determine which hotspots should be reported as suspicious lesions.

To create a report the signing user is required to confirm quality control, and electronically sign the report preview. Signed reports are saved in the device and can be exported as a JPG or DICOM file.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

Important Note: The provided text is an FDA 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a standalone clinical study report with detailed acceptance criteria and performance data in the typical scientific paper format. Therefore, some information, especially very specific numeric acceptance criteria and detailed study results, is inferenced or described broadly as "met predetermined acceptance criteria" because the exact values are not explicitly stated in this regulatory document.

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary does not present specific numeric acceptance criteria (e.g., minimum accuracy percentage, specific sensitivity/specificity thresholds) or detailed reported device performance in a precise tabular format. Instead, it describes functional and analytical performance goals and states that these were met.

For the purpose of this request, I've constructed a table based on the descriptions provided in the "Bench Testing" section:

Acceptance Criteria Category/Description	Reported Device Performance
Digital Phantom Validation Study
Accuracy, Linearity, and Limit of Detection of SUV (Standardized Uptake Value) and Volume quantification against known values of a digital reference object (NEMA phantom).	All SUV and volume quantification tests of aPROMISE met their predetermined acceptance criteria. (Specific numeric thresholds for accuracy, linearity, and LOD are not provided in the document.)
Comparison to Predicate (KSWVWR - K160334)
Equivalent performance for standard functions in marking and quantitative assessments of user-defined regions of interest in PSMA PET/CT.	Demonstrated equivalent performance when compared to the predicate KSWVWR (K160334). (Specific metrics of equivalence are not provided in the document.)
Analytical Performance in Clinical Study (Reproducibility & Consistency)
Enables automated quantification of tracer uptake in reference organs that are more reproducible and consistent than those obtained manually by clinicians.	Demonstrated that aPROMISE enables the automated quantification of tracer uptake in reference organs that are more reproducible and consistent than those obtained manually. (Specific metrics for reproducibility and consistency are not provided in the document.)
Analytical Performance in Clinical Study (Sensitivity for Pre-selection)
High sensitivity in pre-selection of regions of interest determined to be suspicious for metastatic disease.	Demonstrated that aPROMISE has high sensitivity in pre-selection of regions of interest that are determined to be suspicious for metastatic disease. (Specific sensitivity metric is not provided; also note the subject device states "All detected high intensity ROIs can be shown for review by the user without pre-selection," which seems to contradict the predicate's ANN pre-selection method description, but the document clarifies "showing all detected high intensity regions (no preselection as of the predicate)" as the subject device's approach while still achieving high sensitivity in detecting these regions for user review).

2. Sample Size Used for the Test Set and Data Provenance

The document refers to a "Digital Phantom Validation Study" and an "Analytical Performance in Clinical Study."

Sample Size for Test Set:
- Digital Phantom Validation Study: "digital reference object (NEMA phantom)" - This implies a single, well-defined digital phantom, not a large sample size of patient data.
- Analytical Performance in Clinical Study: The specific sample size (number of patients or scans) for this "clinical study" is not specified in the provided document.
Data Provenance:
- Digital Phantom Validation Study: A digital NEMA phantom is a synthetic dataset. The document does not specify its origin.
- Analytical Performance in Clinical Study: The document refers to it as a "Clinical Study" but does not specify the country of origin of the data, nor whether it was retrospective or prospective. Given the context of a 510(k) submission and the lack of detailed clinical trial information, it is likely that this was a retrospective analysis of existing clinical data, but this is not explicitly stated.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

Number of Experts: The document states that the "Analytical Performance in Clinical Study" compared the performance of aPROMISE "to that of clinicians." However, the exact number of clinicians (experts) involved in establishing the ground truth or serving as comparators is not specified.
Qualifications of Experts: The document refers to them as "clinicians." No further specific qualifications (e.g., number of years of experience, subspecialty training like nuclear medicine physician or radiologist) are provided.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1, none) used for establishing ground truth from the "clinicians." It simply states that the device's performance was compared to "that of clinicians" for manual quantification and for identifying suspicious regions. It would imply that the clinicians' outputs themselves served as the comparative "ground truth" or reference for assessing the device's analytical performance.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

Was an MRMC study done? Information provided does not indicate that a formal MRMC comparative effectiveness study was performed where human readers' performance with and without AI assistance was measured. The "Analytical Performance in Clinical Study" primarily assessed the device's standalone analytical capabilities (reproducibility/consistency of quantification and sensitivity of pre-selection) compared to manual clinician performance, not an AI-assisted human workflow versus unassisted human workflow.
Effect size of improvement: Since a formal MRMC study as described (human readers with and without AI) was not detailed, there is no information provided on the effect size of how much human readers improve with AI vs. without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Yes, aspects of standalone performance were analyzed.

The Digital Phantom Validation Study explicitly assessed the algorithm's accuracy, linearity, and limit of detection for SUV and volume quantification against known phantom values, which is a standalone assessment.
The Analytical Performance in Clinical Study also evaluated the device's automated quantification of tracer uptake and its pre-selection of regions of interest, which are functions performed by the algorithm before user interaction. It specifically states "aPROMISE enables the automated quantification..." and "aPROMISE has high sensitivity in pre-selection of regions of interest..." This indicates standalone algorithmic functions were evaluated.

7. Type of Ground Truth Used

For Digital Phantom Validation: The ground truth was known values from a digital reference object (NEMA phantom). This is a synthetic, precisely defined ground truth.
For Analytical Performance in Clinical Study: The ground truth or reference standard for comparison appears to be the manual quantification and determination of suspicious regions by "clinicians." This implies "expert consensus" or "expert readings" served as the benchmark, though the exact process (e.g., single expert, multiple experts with consensus, adjudication) is not detailed. There is no mention of pathology or long-term outcomes data used as ground truth.

8. Sample Size for the Training Set

The document does not provide any information regarding the sample size of the training set used for developing the aPROMISE algorithms (e.g., for organ segmentation or hotspot detection). The 510(k) summary focuses on the validation of the finished device.

9. How the Ground Truth for the Training Set Was Established

Since the document does not specify the training set used, it does not describe how the ground truth for any potential training set was established.

Summary

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July 27, 2021

Image /page/0/Picture/1 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). The FDA logo consists of two parts: the Department of Health and Human Services (DHHS) logo on the left and the FDA wordmark on the right. The DHHS logo is a stylized depiction of a human figure embracing a globe. The FDA wordmark is a blue rectangle with the letters "FDA" in white, followed by the words "U.S. FOOD & DRUG ADMINISTRATION" in blue.

EXINI Diagnostics AB % Donna-Bea Tillman, Ph.D. Senior Consultant Biologics Consulting Group 1555 King Street. Suite 300 ALEXANDRIA VA 22314

Re: K211655

Trade/Device Name: aPROMISE Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: May 27, 2021 Received: May 28, 2021

Dear Dr. Tillman:

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 mediation-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 (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely.

For

Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known) K211655

Device Name aPROMISE

Indications for Use (Describe)

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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510(k) Summary

In accordance with 21 CFR 807.87(h) and 21 CFR 807.92 the 510(k) Summary for aPROMISE is provided below.

1. SUBMITTER

Applicant:	EXINI Diagnostics ABIdeon Science ParkScheelevägen 27223 70 LundSweden
Contact:	Aseem Anand, Ph.D.Vice PresidentEXINI Diagnostics ABIdeon Science Park, Scheelevägen 27, SE-223 70Lund, SwedenTel: +46706604084aseem.anand@exini.com
Submission Correspondent:	Donna-Bea Tillman, Ph.D.Senior ConsultantBiologics Consulting1555 King Street, Suite 300Alexandria, Virginia 22314(410) 531-6542dtillman@biologicsconsulting.com
Date Prepared:	May 28, 2021

2. DEVICE

Device Trade Name:	aPROMISE
Device Common Name:	Picture Archiving and Communication System
Classification Name	21 CFR 892.2050 Medical Image Management andProcessing System
Regulatory Class:	II
Product Code:	LLZ

3. PREDICATE DEVICE

Predicate Device:

Exini aBSI (K191262)

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Secondary Predicate Device: Keosys Medical Imaging Suite KSWVWR (K160334 Advanced Medical Imaging Software Suite)

DEVICE DESCRIPTION 4.

5. INTENDED USE/INDICATIONS FOR USE

aPROMISE is intended to be used by healthcare professionals and researchers for acceptance, transfer, storage, image display, manipulation, quantification and reporting of digital medical images. The system is intended to be used with images acquired using nuclear medicine (NM) imaging, using PSMA PET/CT. The device provides general Picture Archiving and Communications System (PACS) tools as well as a clinical application for oncology including marking of regions of interest and quantitative analysis.

SUBSTANTIAL EQUIVALENCE 6.

Comparison of Indications

Both aPROMISE and the predicate aBSI are software-only devices that are used in the acceptance, transfer, storage, image display, manipulation, quantification and reporting of nuclear medicine images by healthcare providers. Both devices perform segmentation of the body in the radiological image and automatically segment hotspots, regions with high tracer uptake. Both devices rely on the user to make the final selection of regions of interest that are considered as lesions. Both devices provide a quantitative metric of radiotracer uptake that can be used to inform patient care decisions.

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The subject aPROMISE device differs from the primary predicate device in that it is intended to be used with PSMA PET/CT images while the predicate device is intended to be used with bone scans.

These differences in the Indications for use do not affect the fundamental intended use of the devices, which is to provide a software tool to aid the user, a healthcare professional or researcher, to mark regions of interest as lesions and provide quantitative analysis. The intended use to aPROMISE in PET/CT is the same as that of aBSI in bone scan images – a PACS device with a clinical application of oncology to mark and quantify regions of interest, intended to be used by healthcare professionals and researchers. Therefore, aBSI can be used as a primary predicate for aPROMISE.

Technological Comparisons

The table below compares the key technological feature of the subject device aPROMISE to the predicate devices, Exini aBSI (K191262) and Keosys Medical Imaging Suite KSWVWR (K160334).

Specification/Characteristic	aPROMISE(proposed device)	aBSI(predicate device)	Comparison to predicate
General
Intended user	Health care professionalsand researchers	Health care professionalsand researchers	No difference
Intended useenvironment	Healthcare clinics	Healthcare clinics	No difference
Classification	21 CFR 892.2050System, ImageProcessing, Radiological(LLZ) Class II	21 CFR 892.2050System, ImageProcessing, Radiological(LLZ) Class II	No difference
Installation	Cloud-based service andaccess with personal log-in.	Cloud-based service andaccess with personal log-in.	No difference
Operating system	Windows or macOS withChrome browser	Windows or macOS withChrome browser	No difference
DICOMcompatibility andImagingModalities	DICOM 3:Whole body• PET• CT	DICOM 3:Whole body• Bone scans• SPECT	The differences in DICOM 3compatibility reflect thedifferent image modalitieswhich is supported by asecondary predicate, the KeosysMedical Imaging SuiteKSWVWR (K160334), asdiscussed below. The difference
Specification/Characteristic	aPROMISE(proposed device)	aBSI(predicate device)	Comparison to predicate
Image upload	Via file selector or dragand drop from localcomputer ornetwork. Upload canhandle zip files.	Via file selector on localcomputer or network	does not affect the clinical useof the device and does not raisedifferent questions of safety oreffectiveness.The difference involves anadditional option for imageupload. The difference does notaffect the clinical use of thedevice and does not raisedifferent questions of safety oreffectiveness.
Support formultiple scans	Yes, multiple scans canbe analyzed one at atime.	Yes, if multiple scans areprovided, the images areautomatically alignedvertically	The difference in support formultiple scans does not affectthe clinical use of the deviceand does not raise differentquestions of safety oreffectiveness.
Colormaps	A selection of commonlyused colormapssupported:For PET image:Cool• Inverted grayscale• Grayscale withoverflow• Hot Iron• Spectrum• WarmFor CT image:• Grayscale	A selection of commonlyused colormapssupported:• Cool• Electric• Inverted grayscale• Inverted grayscaleoverflow• Grayscale• Thermal	Same feature, both devicesoffer a selection of commonlyused colormaps. Thedifferences in colormaps aredependent on the differentimage modalities. Thedifference does not affect theclinical use of the device and donot raise different questions ofsafety or effectiveness.
Zoom	Automatically adjustedimage size.Manually adjustablezoom in planar views	Automatically adjustedimage size.Manually adjustablezoom in planar views	No difference
Windowing	Manual adjustment ofwindowing. Slider forPET. Click'n'drag andby a drop-down menufor CT.	Manual adjustment ofwindowing. Slider forbone scans.	Same feature, the difference inwindowing is an adjustment forthe different image modalities.The difference does not affectthe clinical use of the deviceand do not raise different
Specification/Characteristic	aPROMISE(proposed device)	aBSI(predicate device)	Comparison to predicate
Image layouts	4 panel view showingPET, CT, PET/CT fusionand MIP simultaneouslyand option to display eachview separately.Coronal, axial and sagittalviews can be displayed	Anterior and posteriorimages shown side byside	The difference in image layoutis dependent on the differentimage modalities. Thedifference does not affect theclinical use of the device and donot raise different questions ofsafety or effectiveness.
Intensity display	Local intensity displayedin left corner of the imagewhen hovering overimage	Local intensity displayedin left corner of the imagewhen hovering overimage	No difference
Hotspot display	Segmented hotspots canbe displayed in planarviews	Segmented hotspots canbe displayed in planarviews	No difference
OrganSegmentation	AI enabled automatedsegmentation of skeletonand soft tissue organs	AI enabled automatedsegmentation of skeleton	Same feature but adjusted forthe different image modalities.The difference does not affectthe clinical use of the deviceand do not raise differentquestions of safety oreffectiveness.
Normalization	Images are normalized sothat healthy bone tissueintensities areautomatically set to apredefined level.	Images are normalized sothat healthy bone tissueintensities areautomatically set to apredefined level.	No difference
Hotspot detection	Algorithm to detect highintensity regions ofinterest in the PET serieswithin the segmentedstructures (skeleton andsoft tissue).	Algorithm to detect highintensity regions ofinterest within thesegmented structures(skeleton).	Same feature but adjusted forthe different image modalities.The difference does not affectthe clinical use of the deviceand do not raise differentquestions of safety oreffectiveness.
Hotspot pre-selection	All detected highintensity ROIs can beshown for review by theuser without pre-selection.	Detected high intensityROIs are sorted into twogroups (high and low)using artificial neuralnetwork (ANN)classifiers. Hotspots,	The devices have a differencein hotspot preselection;showing all detected highintensity regions (nopreselection as of thepredicate), but both devices still
Specification/Characteristic	aPROMISE(proposed device)	aBSI(predicate device)	Comparison to predicate
		classified as high, arepreselected and displayedto the user for review.	require the user to select andmake the final call of whatregions to include as lesions.The difference does not affectthe clinical use of the deviceand do not raise differentquestions of safety oreffectiveness.
Hotspotverification	The user can select pre-defined segmentation ofhotspots or segment eachhotspot manually that areconsidered to be lesionsby the user.	Preselected hotspots areshown to and reviewed bythe user. The hotspotselection is editable bythe user.	The difference in hotspotverification constitutes of theuser to manually review andselect predefined- or drawhotspots in the subject device,instead of being presentedautomatically preselectedhotspots to be reviewed as ofthe predicate. The differencedoes not affect the clinical useof the device and do not raise different questions of safety oreffectiveness.
HotspotQuantification	-Bone Scan Index (BSI)	Standard Uptake Values(SUV):-SUV-max-SUV-mean-SUV-peak-Volume-Lesion Index (LI)-Intensity-weightedTissue Lesion Volume(ITLV)	The differences in calculatedvalues reflect the differentimaging modalities. The use ofthe SUV calculation issupported by a secondarypredicate, the Keosys MedicalImaging Suite KSWVWR(K160334), as discussed insection 12.3.2.
Quality Control	SW enforced requirementto verify the user reviewof- Image quality- PET/CT imagealignment- Patient study data- Reference values- Study is not asuperscan	SW enforced requirementto verify the user reviewof- Image quality- The skeletal outlining(Atlas)- The selected hotspots	Same feature with adjustmentfor the different imagemodalities. The difference doesnot affect the clinical use of thedevice and do not raise differentquestions of safety oreffectiveness.
Specification/Characteristic	aPROMISE(proposed device)	aBSI(predicate device)	Comparison to predicate
Userconfirmation forreport generation	User confirmation that therequirements for imageassessment have beenfollowed is required forreport creation	User confirmation that therequirements for BSIassessment have beenfollowed is required forreport creation	No difference
Report (Summarypage export)	The user can export theresults of a study to thehard drive as an image oras a DICOM SecondaryCapture.	The user can export theresults of a study to thehard drive as an image oras a DICOM SecondaryCapture.	No difference
CSV export	Supports export of studyand lesion values as aCSV file for all createdreports	Supports export of studyand BSI value as a CSVfile for all created reports	No difference

Table 1: Technological Comparison

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7. PERFORMANCE DATA

Sterilization and Shelf Life

aPROMISE consists entirely of software; accordingly, there are no sterilization concerns. As a software only device, shelf-life (including performance date) is also not applicable because of low likelihood of time-dependent product degradation.

Biocompatibility Testing

There are no direct or indirect patient-contacting components of the subject device. Therefore, patient contact information is not needed for this device.

Electrical safety and electromagnetic compatibility (EMC)

Not applicable. The subject device is a software-only device. It contains no electric components, generates no electrical emissions, and uses no electrical energy of any type.

Software Verification and Validation Testing

Software verification and validation testing were conducted and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." The software for this device was considered as a moderate level of concern.

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Bench Testing

Exini performed the following studies verify and validate the performance of aPROMISE.

Digital Phantom Validation Study. This study assessed the accuracy, linearity, and limit . of detection of aPromise against the known values of a digital reference object (NEMA phantom). All SUV and volume quantification tests of aPROMISE met their predetermined acceptance criteria.
Comparison to Predicate. This study demonstrated the equivalent performance of ● APROMISE as compared to the predicate KSWVWR (K160334) for standard functions in marking and quantitative assessments of user defined region of interest in PSMA PET/CT.
. Analytical Performance in Clinical Study. This study compared the performance of aPROMISE to that of clinicians and demonstrated that aPROMISE enables the automated quantification of tracer uptake in reference organs that are more reproducible, and consistent than those obtained manually. The study also demonstrated that aPROMISE has high sensitivity in pre-selection of regions of interest that are determined to be suspicious for metastatic disease.

These results demonstrate that aPROMISE performs in accordance with specifications and meets user needs and intended uses.

Animal Testing

Not applicable. Animal studies are not necessary to establish the substantial equivalence of this device.

Clinical Data

Not applicable. Clinical studies are not necessary to establish the substantial equivalence of this device.

CONCLUSION 8.

Based on the detailed comparison, the differences between the subject and predicate devices do not raise new questions of safety and effectiveness. The software verification (Section 16.9) and the performance testing demonstrates that the device performs according to the device requirements. Therefore, the aPROMISE device can be found substantially equivalent to the predicate device.

Regulation Number and Section

§ 892.2050 Medical image management and processing system.

(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).