SoftView is intended to generate an enhanced, secondary digital radiographic image of the chest. The enhanced AP or PA image of the chest provides improved visibility of the lung parenchyma through bone suppression and tissue equalization, and may facilitate discerning the presence or absence of nodules. The SoftView image provides adjunctive information and is not a substitute for the original PA/AP image. This device is intended to be used by trained professionals, such as physicians, radiologists, and technicians on patients with risk of having lung nodules and is not intended to be used on pediatric patients.

Device Description

SoftView is a dedicated post-processing application which suppresses bone structures from digital radiographic image of the chest.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study information for the SoftView™ device, extracted from the provided text:

SoftView™ Acceptance Criteria and Study Information

The acceptance criteria for SoftView™ were demonstrated through a reader study and a comparative analysis of the contrast-to-noise ratio (CNR) against a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria Category	Specific Metric	Acceptance Criteria Description	Reported Device Performance
Reader Study	Area Under the Localization Receiver-Operating Characteristic (LROC) Curve	A statistically significant improvement in the LROC curve area when using SoftView™ assistance for detecting actionable lung nodules, compared to without DeepView™ assistance.	The mean difference in the area under the LROC curve was -0.098 (95% CI: -0.116 to -0.080), indicating a statistically significant improvement with SoftView™.
	Sensitivity for Actionable Lung Nodules	No explicit acceptance criterion for a minimum sensitivity value is stated, but the study aimed to demonstrate improvement with SoftView™.	Sensitivity was 49.5% (95% CI: 45.9-53.0) without SoftView and 66.3% (95% CI: 63.1-69.7) with the addition of the SoftView image.
	Specificity	No explicit acceptance criterion for a minimum specificity value is stated, but the study aimed to demonstrate performance with SoftView™.	Specificity was 96.1% (95% CI: 95.0-97.1) with the standard image and 91.8% (95% CI: 89.5-93.5) with the SoftView image.
Comparative Analysis	Contrast-to-Noise Ratio (CNR) of Residual Bone (Rib and Clavicle Regions)	SoftView™ must be substantially equivalent to the predicate device's hardware/software process (GE Medical Systems Dual Energy and Tissue Equalization Software Options) in terms of CNR of residual bone in soft tissue images. Equivalency and non-inferiority tests were performed, with an "ideal" CNR of residual ribs being 0.0. The analysis stratified data by modality (CR and DR) and lung regions (pleural, mid-lung, and hilum).	For indicated strata, SoftView™ was demonstrated to be equivalent to DES soft tissue images. The exception was the middle area of the lung for the DR modality (GE DES), where SoftView™ was found to be better (closer to an "ideal" CNR of 0.0). Furthermore, SoftView™ was non-inferior to DR and CR dual energy devices' soft tissue images across all strata. Descriptive statistics of means and standard deviations of CNRs across different modalities and regions of the lungs were in agreement.

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

The document does not explicitly state the exact sample size for the test set used in the reader study or the comparative analysis. It mentions "an independent dataset" for the comparative analysis of CNR.

The data provenance is not specified (e.g., country of origin, retrospective or prospective).

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

This information is not provided in the given text. The document refers to "detecting actionable lung nodules" in the reader study, implying a clinical assessment, but does not detail how the ground truth for these nodules was established or by whom.

4. Adjudication Method for the Test Set

The adjudication method for establishing ground truth for the test set is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

Yes, a multi-reader study was conducted. The study assessed the benefit of SoftView™ to radiologists for detecting actionable lung nodules.

Effect Size:
The mean difference in the area under the LROC curve was -0.098 (95% CI: -0.116 to -0.080), which is described as a statistically significant improvement for human readers with the aid of SoftView™. The sensitivity for detecting nodules increased from 49.5% without SoftView to 66.3% with SoftView.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

A standalone performance study of the algorithm without human intervention was not explicitly described in terms of diagnostic effectiveness for nodules. The "Comparative Analysis" focused on the algorithm's output (soft tissue image) against a predicate device's output based on CNR, which is a technical image quality metric rather than direct standalone diagnostic performance. The primary effectiveness study was a reader study with human readers.

7. The Type of Ground Truth Used

The type of ground truth used for the reader study is not explicitly stated. It refers to "actionable lung nodules," implying clinical diagnosis or follow-up, but the method (e.g., expert consensus, pathology, outcome data) is not detailed.
For the comparative analysis, the ground truth was the soft tissue images produced by the predicate DES devices (GE and Fuji), used to compare the CNR of residual bone.

8. The Sample Size for the Training Set

The document does not provide information regarding the sample size used for the training set. It mentions that the model is "built from DES data by using simple image features extracted from the standard PA, along with target values derived from a DES soft tissue image," but the size of this training data is not specified.

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

The ground truth for the training set (from which the SoftView™ model was built) was established by using target values derived from a DES soft tissue image. This means that commercially available Dual Energy Subtraction (DES) systems were used as the reference standard to create the "ideal" bone-suppressed images that the SoftView™ algorithm was trained to replicate. The exact process of "deriving target values" is not detailed further.

Summary

{0}------------------------------------------------

KOS2363

Traditional 510(k) Premarket Notification SoftView™

Riverain Medical

510(K) SUMMARY

Submission Date:	August 4, 2009	MAR 1 8 2010
Submitter Information:
Company Name:	Riverain Medical Group, LLC.
Company Address:	3020 South Tech Blvd., Miamisburg, OH 45342-4860
Contact Person:	Jennifer VetterDirector, Regulatory Affairs and Quality AssuranceRiverain Medical800.990.3387937.425.6493jvetter@riverainmedical.com
Device Information:
Trade Name:	SoftView™
Regulation Number:	21 CFR §892.2050
Regulation Name:	System, Image Processing, Radiological
Regulatory Class:	Class II
Product Code:	LLZ
	Predicate Device:Dual Energy and Tissue Equalization Software Options(K013481)GE Medical SystemsClass II
Device Description:	SoftView is a dedicated post-processing application whichsuppresses bone structures from digital radiographic imageof the chest.
Intended Use:	SoftView is intended to generate a bone-suppressed imagefrom a original PA/AP chest radiograph.
Indications for Use:	SoftView is intended to generate an enhanced, secondarydigital radiographic image of the chest. The enhanced APor PA image of the chest provides improved visibility ofthe lung parenchyma through bone suppression and tissue

{1}------------------------------------------------

equalization, and may facilitate discerning the presence or absence of nodules. The SoftView image provides adjunctive information and is not a substitute for the original PA/AP image. This device is intended to be used by trained professionals, such as physicians, radiologists, and technicians on patients with risk of having lung nodules and is not intended to be used on pediatric patients.

Comparison to Predicate Device:

SoftView is substantially equivalent to the cited predicate device. Differences in the design and performance from the cited predicate device do not affect either the safety or effectiveness of SoftView for its intended use.

Conclusion:

SoftView is a mathematical model of a DES system that operates on a standard chest X-ray. It is an accurate representation of the soft tissue image produced by the predicate device's hardware/software process. The model is built from DES data by using simple image features extracted from the standard PA, along with target values derived from a DES soft tissue image. Thus, although SoftView does not generate the soft tissue image based on two exposures to the patient in real time, it is an accurate mathematical model of the process. The result of SoftView processing is a soft tissue image of the patient, consistent with that produced by a DES device but without requiring any additional radiation dose to the patient. Effectiveness of this model was demonstrated both by a reader study and by a comparative analysis of the contrast-to-noise ratio (CNR) of the residual bone in the predicate device's images in the soft tissue rib and clavicle regions, relative to the subject device.

Reader Study Results: A reader study was conducted to assess the benefit of SoftView to a radiologist for detecting actionable lung nodules. Reader performance was quantified by the area under the Localization Receiver-Operating Characteristic (LROC), curve which measures the conjoint ability to detect and correctly localize a true positive location on the radiograph. The difference in the average area under the LROC curve with and without the aid of SoftView was used to assess performance. The mean difference in the area under the curves was -0.098 (95% CI: -0.116 to -0.080), a statistically significant improvement. Sensitivity was 49.5% (95% CI:

{2}------------------------------------------------

Riverain Medical

Traditional 510(k) Premarket Notification SoftViewTM

45.9-53.0) without SoftView and 66.3% (95% CI: 63.1-69.7) with the addition of the SoftView image. Specificity was 96.1% (95% CI: 95.0-97.1) with the standard image and 91.8% (95% CI: 89.5-93.5) with the SoftView image.

Substantial Equivalence: To establish substantial equivalence, a comparative analysis of the contrast-to-noise ratio (CNR) of the residual bone in the predicate device's soft tissue images versus the subject device was performed. A CNR analysis was performed for both the GE and Fuji dual energy subtraction (DES) soft tissue images.

Analysis of scatter plots of the contrast-to-noise ratio (CNR) for the residual rib objects for an independent dataset was used to compare the SoftView correlative relationship relative to DES. Statistical hypothesis tests were also performed on the independent dataset. Two series of tests were performed, equivalency and non-inferiority tests. Data were stratified across modality, CR (Fuji DES), DR (GE DES), and lung regions, i.e., pleural, mid-lung, and hilum.

For the indicated strata of the data, it was demonstrated that SoftView is equivalent to the DES soft tissue images. The exception was the middle area of the lung for the DR modality (GE DES). SoftView was found to be better in this region based on an "ideal" CNR of the residual ribs in the soft tissue image being 0.0. Furthermore, a non-inferiority test demonstrated that SoftView was non-inferior to the DR and CR dual energy devices soft tissue images across all strata. Descriptive statistics of the means and standard deviations of the CNRs across the different modalities and regions of the lungs were in agreement.

{3}------------------------------------------------

Image /page/3/Picture/0 description: The image shows the seal of the Department of Health & Human Services-USA. The seal is circular and contains an abstract image of an eagle. The text "DEPARTMENT OF HEALTH & HUMAN SERVICES-USA" is arranged around the top half of the circle.

DEPARTMENT OF HEALTH & HUMAN SERVICES

Public Health Service

Food and Drug Administration 10903 New Hampshire Avenue Document Control Room - WO66-G609 Silver Spring. MD 20993-0002

MAR 1 8 2010

Ms. Jennifer Vetter Director-Regulatory and Quality Assurance Riverain Medical Group, LLC 3020 South Tech Blvd. MIAMISBURG OH 45342

Re: K092363

Trade/Device Name: Softview™M Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: LLZ Dated: February 5, 2010 Received: February 12, 2010

Dear Ms. Vetter:

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. 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.

If your device is classified (see above) into class II (Special Controls), it may be subject to such additional controls. Existing major regulations affecting your device can be found in Title 21, Code of Federal Regulations (CFR), Parts 800 to 895. 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 Parts 801 and 809); medical device reporting (reporting of

{4}------------------------------------------------

medical device-related adverse events) (21 CFR 803); and good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820). This letter will allow you to begin marketing your device as described in your Section 510(k) premarket notification. The FDA finding of substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to proceed to the market.

If you desire specific advice for your device on our labeling regulation (21 CFR Parts 801 and 809), please contact the Office of In Vitro Diagnostic Device Evaluation and Safety at (301) 796-5450. 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 http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office

of Surveillance and Biometrics/Division of Postmarket Surveillance.

You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address http://www.fda.gov/cdrh/industry/support/index.html.

Sincerely vours.

Donald J. Trump

Donald J. St.Pierre Acting Director Division of Radiological Devices Office of In Vitro Diagnostic Device Evaluation and Safety Center for Devices and Radiological Health

Enclosure

{5}------------------------------------------------

2.0 INDICATIONS FOR USE STATEMENT

510(k) Number (if known): K

Device Name:

SoftView™

Indications for Use:

Prescription Use X (Part 21 CFR 801 Subpart D)

AND/OR

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

(PLEASE DO NOT WRITE BELOW THIS LINE - CONTINUE ON ANOTHER PAGE OF NEEDED)

Concurrence of CDRH, Office of Device Evaluation (ODE)

(Division Sign-Off)

Page 1 of 1

Division Sign Off)
Division of Radiological Devices
Office of In Vitro Diagnostic Device Evaluation and Safety

510K K092363

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).