Breast Ultrasound Image Reviewed With Assistance of Deep Learning
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 300
- 试验地点
- 1
- 主要终点
- Concordance rate
研究概览
简要总结
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.
详细描述
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
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Crossover
- 主要目的
- Device Feasibility
- 盲法
- Single (Outcomes Assessor)
盲法说明
The study consisted of 10 readers with varying levels of training and experience providing analysis on a randomized set of 300 patients' breast ultrasound data with and without S-Detect for Breast. Two reading periods separated by at least 3-week washout, totaling 600 cases analyzed per reader. PI and her associate have knowledge about patients diagnosis and other information. So, they are exclueded in readers for "reviewing". And all breast US images are de-indentified.
入排标准
- 年龄范围
- 19 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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
排除标准
- •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
- •Subject Characteristics
- •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".
- •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.
- •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%).
- •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.
研究组 & 干预措施
Manual review
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.
干预措施: Ultrasound Image review with CADe (Device)
Manual review
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.
干预措施: Ultrasound Image review with CADx (Device)
Manual review
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.
干预措施: Ultrasound Image manual review (Device)
Manual review
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.
干预措施: Biopsy (Procedure)
Review by S-Detect for Breast
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).
干预措施: Ultrasound Image review with CADe (Device)
Review by S-Detect for Breast
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).
干预措施: Ultrasound Image manual review (Device)
Review with assistance of S-Detect for Breast
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).
干预措施: Biopsy (Procedure)
Review with assistance of S-Detect for Breast
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).
干预措施: Ultrasound Image review with CADx (Device)
Review with assistance of S-Detect for Breast
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).
干预措施: Ultrasound Image manual review (Device)
结局指标
主要结局
Concordance rate
时间窗: 2 days
Breast Imaging Reporting and Data System descriptors suggested by S-Detect for Breast are in good agreement with those selected by experts. In other words, the Breast Imaging Reporting and Data System Lexicon values generated by S-Detect for Breast are not statistically different from the consensus of experts. Breast Imaging Reporting and Data System Assessment Category Score: The user makes the final decision on the Assessment Category Score. Using this Score, S-Detect displays the assessment description. Category 0: Incomplete - Need Additional Imaging Evaluation Category 1: Negative Category 2: Benign Category 3: Probably Benign Category 4a: Low suspicion for malignancy Category 4b: Moderate suspicion for malignancy Category 4c: High suspicion for Malignancy Category 5: Highly Suggestive of Malignancy Category 6: Known Biopsy-Proven Malignancy
次要结局
- Accuracy(7 day)
- Sensitivity(7 day)
- Area Under Curve(7 day)
- Consensus(2 day)
- Reporting time(2 day)
- Specificity(7 day)