Which supplementary imaging modality should be used for breast ultrasonography? Comparison of the diagnostic performance of elastography and computer-aided diagnosis

Abstract

PurposeThe aim of this study was to evaluate and compare the diagnostic performance of grayscale ultrasonography (US), US elastography, and US computer-aided diagnosis (US-CAD) in the differential diagnosis of breast masses.MethodsA total of 193 breast masses in 175 consecutive women (mean age, 46.4 years) from June to August 2015 were included. US and elastography images were obtained and recorded. A US-CAD system was applied to the grayscale sonograms, which were automatically analyzed and visualized in order to generate a final assessment. The final assessments of breast masses were based on the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories, while elasticity scores were assigned using a 5-point scoring system. The diagnostic performance of grayscale US, elastography, and US-CAD was calculated and compared. ResultsOf the 193 breast masses, 120 (62.2%) were benign and 73 (37.8%) were malignant. Breast masses had significantly higher rates of malignancy in BI-RADS categories 4c and 5, elastography patterns 4 and 5, and when the US-CAD assessment was possibly malignant (all P<0.001). Elastography had higher specificity (40.8%, P=0.042) than grayscale US. US-CAD showed the highest specificity (67.5%), positive predictive value (PPV) (61.4%), accuracy (74.1%), and area under the curve (AUC) (0.762, all P<0.05) among the three diagnostic tools. ConclusionUS-CAD had higher values for specificity, PPV, accuracy, and AUC than grayscale US or elastography. Computer-based analysis based on the morphologic features of US may be very useful in improving the diagnostic performance of breast US.

Breast Ultrasound Computer-Aided Diagnosis: Analysis of Types of Errors

“…US BI-RADS has substantially contributed to improving communication between physicians and radiologists, but observer variability remains a major limitation of US, which is 97.9 C4A = category 4A, low suspicion for malignancy, C4B = category 4B, moderate suspicious for malignancy, CAD = computer-aided diagnosis, NPV = negative predictive value, PPV = positive predictive value (4,6,9,11,13,15,16). In this study, we evaluated the di- (4,9,11,17).…”

“…Many studies have applied CAD systems to breast US to demonstrate the efficiency of CAD systems and to evaluate the usefulness of CAD systems for improving diagnostic accuracy (4)(5)(6)(7)(8)(9)(10)(11). There are two algorithms in breast US-CAD systems for lesion interpretations.…”

“…S-Detect might be very useful in improving the diagnostic performance of breast US for assistance in either lesion detection or the decisionmaking process during practice. This system has been reported to improve the diagnostic performance of radiologists by proper application of these computer-aided programs (4,11,13).…”

Reliability Studies of Different Readers Using Computer Aided Diagnosis System in Ultrasound for Determining Identical Lesions in a Breast Phantom

“…The main pitfall of breast US is inter-and intra-reader variability in breast cancer detection and diagnosis (5). Many recent researches have used computer-aided diagnosis (CAD) with breast US in order to improve the diagnostic performance (4,(6)(7)(8). In breast US, CAD plays a role in interpreting lesions that are found by the examiner, rather than detecting lesions.…”

“…Several studies have been conducted in order to improve diagnostic performance in breast US using Breast US CAD system (5,6,9), and there are also studies indicating that S-detect™ is useful for improving diagnostic performance in less experienced radiologists (9). However, there have been no studies on several readers analyzing the same lesion, because almost all studies have been conducted on actual patients.…”