Automated Versus Handheld Breast Ultrasound for Evaluating Axillary Lymph Nodes in Patients With Breast Cancer.

OBJECTIVE: Automated breast ultrasound (ABUS) is a relevant imaging technique for early breast cancer diagnosis and is increasingly being used as a supplementary tool for mammography. This study compared the performance of ABUS and handheld ultrasound (HHUS) in detecting and characterizing the axillary lymph nodes (LNs) in patients with breast cancer. MATERIALS AND METHODS: We retrospectively reviewed the medical records of women with recently diagnosed early breast cancer (≤ T2) who underwent both ABUS and HHUS examinations for axilla (September 2017-May 2018). ABUS and HHUS findings were compared using pathological outcomes as reference standards. Diagnostic performance in predicting any axillary LN metastasis and heavy nodal-burden metastases (i.e., ≥ 3 LNs) was evaluated. The ABUS-HHUS agreement for visibility and US findings was calculated. RESULTS: The study included 377 women (53.1 ± 11.1 years). Among 385 breast cancers in 377 patients, 101 had axillary LN metastases and 30 had heavy nodal burden metastases. ABUS identified benign-looking or suspicious axillary LNs (average, 1.4 ± 0.8) in 246 axillae (63.9%, 246/385). According to the per-breast analysis, the sensitivity, specificity, positive and negative predictive values, and accuracy of ABUS in predicting axillary LN metastases were 43.6% (44/101), 95.1% (270/284), 75.9% (44/58), 82.6% (270/327), and 81.6% (314/385), respectively. The corresponding results for HHUS were 41.6% (42/101), 95.1% (270/284), 75.0% (42/56), 82.1% (270/329), and 81.0% (312/385), respectively, which were not significantly different from those of ABUS (P ≥ 0.53). The performance results for heavy nodal-burden metastases were 70.0% (21/30), 89.6% (318/355), 36.2% (21/58), 97.3% (318/327), and 88.1% (339/385), respectively, for ABUS and 66.7% (20/30), 89.9% (319/355), 35.7% (20/56), 97.0% (319/329), and 88.1% (339/385), respectively, for HHUS, also not showing significant difference (P ≥ 0.57). The ABUS-HHUS agreement was 95.9% (236/246; Cohen's kappa = 0.883). CONCLUSION: Although ABUS showed limited sensitivity in diagnosing axillary LN metastasis in early breast cancer, it was still useful as the performance was comparable to that of HHUS.

High-Resolution Finger MRI: What Should You Look for in Trauma of the Fingers?

The fingers are among the most commonly injured structures in traumatic injuries resulting from sports and work. Finger injuries encompass a broad spectrum of injuries to bone and soft tissues, including tendons, ligaments, and cartilage. The high resolution of 3T MRI with dedicated surface coils allows for optimal assessment of the intricate soft tissue structures of the fingers. There have been several reports on detailed MRI features of the basic anatomy and common pathological findings of the finger and hand. Understanding the normal anatomy and familiarization with common traumatic lesions of the ligaments, tendons, and pulleys of the fingers on high-resolution MRI will allow radiologists to perform accurate preoperative evaluations of traumatic hand lesions. The purpose of this study is to review the normal hand anatomy and common traumatic lesions of the finger on high-resolution MRI and correlate them with surgical findings.

False-negative results on computer-aided detection software in preoperative automated breast ultrasonography of breast cancer patients.

PURPOSE: The purpose of this study was to measure the cancer detection rate of computer-aided detection (CAD) software in preoperative automated breast ultrasonography (ABUS) of breast cancer patients and to determine the characteristics associated with false-negative outcomes. METHODS: A total of 129 index lesions (median size, 1.7 cm; interquartile range, 1.2 to 2.4 cm) from 129 consecutive patients (mean age±standard deviation, 53.4±11.8 years) who underwent preoperative ABUS from December 2017 to February 2018 were assessed. An index lesion was defined as a breast cancer confirmed by ultrasonography (US)-guided core needle biopsy. The detection rate of the index lesions, positive predictive value (PPV), and false-positive rate (FPR) of the CAD software were measured. Subgroup analysis was performed to identify clinical and US findings associated with false-negative outcomes. RESULTS: The detection rate of the CAD software was 0.84 (109 of 129; 95% confidence interval, 0.77 to 0.90). The PPV and FPR were 0.41 (221 of 544; 95% CI, 0.36 to 0.45) and 0.45 (174 of 387; 95% CI, 0.40 to 0.50), respectively. False-negative outcomes were more frequent in asymptomatic patients (P<0.001) and were associated with the following US findings: smaller size (P=0.001), depth in the posterior third (P=0.002), angular or indistinct margin (P<0.001), and absence of architectural distortion (P<0.001). CONCLUSION: The CAD software showed a promising detection rate of breast cancer. However, radiologists should judge whether CAD software-marked lesions are true- or false-positive lesions, considering its low PPV and high FPR. Moreover, it would be helpful for radiologists to consider the characteristics associated with false-negative outcomes when reading ABUS with CAD.

Factors Affecting Breast Cancer Detectability on Digital Breast Tomosynthesis and Two-Dimensional Digital Mammography in Patients with Dense Breasts.

Objective: To compare digital breast tomosynthesis (DBT) and conventional full-field digital mammography (FFDM) in the detectability of breast cancers in patients with dense breast tissue, and to determine the influencing factors in the detection of breast cancers using the two techniques. Materials and Methods: Three blinded radiologists independently graded cancer detectability of 300 breast cancers (288 women with dense breasts) on DBT and conventional FFDM images, retrospectively. Hormone status, histologic grade, T stage, and breast cancer subtype were recorded to identify factors affecting cancer detectability. The Wilcoxon signed-rank test was used to compare cancer detectability by DBT and conventional FFDM. Fisher's exact tests were used to determine differences in cancer characteristics between detectability groups. Kruskal-Wallis tests were used to determine whether the detectability score differed according to cancer characteristics. Results: Forty breast cancers (13.3%) were detectable only with DBT; 191 (63.7%) breast cancers were detected with both FFDM and DBT, and 69 (23%) were not detected with either. Cancer detectability scores were significantly higher for DBT than for conventional FFDM (median score, 6; range, 0-6; p < 0.001). The DBT-only cancer group had more invasive lobular-type breast cancers (22.5%) than the other two groups (i.e., cancer detected on both types of image [both-detected group], 5.2%; cancer not detected on either type of image [both-non-detected group], 7.3%), and less detectability of ductal carcinoma in situ (5% vs. 16.8% [both-detected group] vs. 27.5% [both-non-detected group]). Low-grade cancers were more often detected in the DBT-only group than in the both-detected group (22.5% vs. 10%, p = 0.026). Human epidermal growth factor receptor-2 (HER-2)-negative cancers were more often detected in the DBT-only group than in the both-detected group (92.3% vs. 70.5%, p = 0.004). Cancers surrounded by mostly glandular tissue were detected less often in the DBT only group than in the both-non-detected group (10% vs. 31.9%, p = 0.016). DBT cancer detectability scores were significantly associated with cancer type (p = 0.012), histologic grade (p = 0.013), T and N stage (p = 0.001, p = 0.024), proportion of glandular tissue surrounding lesions (p = 0.013), and lesion type (p < 0.001). Conclusion: Invasive lobular, low-grade, or HER-2-negative cancer is more detectable with DBT than with conventional FFDM in patients with dense breasts, but cancers surrounded by mostly glandular tissue might be missed with both techniques.