Breast Ultrasound Image Reviewed With Assistance of Deep Learning Algorithms

Samsung

Status: Unknown

Conditions: Breast Cancer; Breast Mass; Breast Lesions

Treatments: Procedure: Biopsy; Device: Ultrasound Image manual review; Device: Ultrasound Image review with CADx; Device: Ultrasound Image review with CADe

Study type: Interventional

Funder types: Other; Industry

Identifiers

NCT03706534

300.08-2018-Samsungmedison-S

Details and patient eligibility

About

This study evaluates a second review of ultrasound images of breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by Samsung Medical Imaging, to see if this artificial intelligence will help the Radiologist make more accurate diagnoses.

Full description

Using ultrasound images prospectively acquired, the purpose of this study entails a second review of ultrasound images with suspicious breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by SamsungMedison Co.,Ltd.

The images will be reviewed by the radiologists twice: first without, and then with assistance of artificial intelligence program by SamsungMedison Co., Ltd.

BIRADS system will be used in this study.

The objectives of the study are twofold: to quantify the statistical equivalence of radiologists' opinion and AI's output (CADe), and to check BIRADS score-based diagnostic accuracy (CADx) that is gained by the Radiologists' use of this interactive tool

Enrollment: 300 patients

Sex: All

Ages: 19+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion and exclusion criteria

1. Inclusion Criteria:

   • Adult females or males recommended for ultrasound-guided breast lesion biopsy or ultrasound follow-up with at least one suspicious lesion
   • Age > 18 years
   • Able to provide informed consent

2. Exclusion Criteria:

   • Unable to read and understand English
   • Unable or unwilling to provide informed consent
   • A patient with current or previous diagnosis of breast cancer in the same quadrant
   • Unable or unwilling to undergo study procedures

3. Subject Characteristics

   1. Number of Subjects: 300 subjects from 300 separate breast lesions can be acquired. If a subject has more than 1 suspicious lesion, each may be chosen by the radiologist attending as suitable for "second review".
   2. Gender and Age of Subjects: Adult females or males aged 18 years or older who meet all of the inclusion criteria and none of the exclusion criteria will be considered for enrollment. Minors are excluded as breast cancer is very rare in this age group.
   3. Racial and Ethnic Origin: There are no enrollment exclusions based on economic status, race, or ethnicity. Based on local and United States census data, the expected ethnic distribution will be approximately 26 Hispanic (approx. 16%) and 134 non-Hispanic people. Furthermore, the expected racial distribution is expected to be approximately 126 White (approx. 79% of the whole study), 21 Black or African America (13%), 8 Asian (5%), and 5 of other categories (3%).
   4. Vulnerable Subjects: It is unlikely that any UR students or employees will be enrolled unless their primary physician refers them to UR Medicine Breast Imaging at Red Creek for breast ultrasound and a suspicious lesion is found. We do not expect any of these referrals to be from staffs who work directly with the PIs.

Trial design

Primary purpose: Device Feasibility

Allocation: Randomized

Interventional model: Crossover Assignment

Masking: Single Blind

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300 participants in 3 patient groups

Manual review

Active Comparator group

Description:

The images will be reviewed by the radiologists using BIRADS scheme without any assistance of artificial assistance. This review will be done off-line using a separate program in entirely manual mode. During this review, BIRADS descriptor choices by each radiologist and the time it takes for the radiologist to make such decision will be stored. Radiologists also make assessment decision without any intervention from artificial intelligence. 10 radiologists review manually.

Treatment:

Device: Ultrasound Image review with CADe

Device: Ultrasound Image review with CADx

Procedure: Biopsy

Device: Ultrasound Image manual review

Review by S-Detect for Breast

Experimental group

Description:

The same images will be separately processed by the artificial intelligence system (S-Detect for Breast) by Samsung. The two results, one by the radiologists and the other by artificial intelligence system, will be compared to statistically quantify equivalence (CADe).

Treatment:

Device: Ultrasound Image review with CADe

Device: Ultrasound Image manual review

Review with assistance of S-Detect for Breast

Experimental group

Description:

Second, the images will be reviewed by the radiologists with the help of artificial intelligence system, which is an interactive tool automatically providing recommendations on BIRADS descriptor choices that can be modified by the radiologists. The radiologists, after selecting all the descriptors of BIRADS, will decide the assessment categories. These decisions will be compared with the ground truths generated from the biopsy results or a 24-month follow-up (CADx).

Treatment:

Device: Ultrasound Image review with CADx

Procedure: Biopsy

Device: Ultrasound Image manual review