RESUMEN
Poor positioning decreases mammography sensitivity and is arguably the single most important contributor to image quality (IQ). Inadequate IQ may subject patients to technical repeat views during the examination or return for technical recalls. Artificial intelligence (AI) software can objectively evaluate breast positioning and compression metrics for all images and technologists. This study assessed whether implementation of AI software across the authors' institution improved IQ and reduced rates of technical repeats and recalls (TR). From April 2019 to March 2022, TR was retrospectively evaluated for 40 technologists (198 054 images; Centricity electronic medical record system, GE HealthCare), and AI IQ metrics were available for 42 technologists (211 821 images; Analytics, Volpara Health Technologies). Diagnostic and digital breast tomosynthesis images and implant cases were excluded. Kolmogorov-Smirnov, χ2, and paired t tests were used to evaluate whether AI IQ metrics and TR rates improved between the initial and most recent 12-month periods following AI software implementation (ie, baseline [April 2019 to March 2020] vs current [April 2021 to March 2022]). Comparing baseline with current periods, TR significantly reduced from 0.77% (788 of 102 953 images) to 0.17% (160 of 95 101 images), respectively (P < .001), and overall mean quality score improved by 6% ([2.42 - 2.28]/2.28; P = .001), demonstrating the potential of AI software to improve IQ and reduce patient TR. Keywords: Mammography, Breast, Oncology, QA/QC, Screening, Technology Assessment © RSNA, 2023.
RESUMEN
OBJECTIVE. Liver transplant patients are monitored for rejection and hepatic fibrosis and often undergo liver biopsies. The purpose of the present study is to determine whether noninvasive shear wave elastography (SWE) can quantify fibrosis in liver transplant recipients, with the aim of decreasing and possibly eliminating unnecessary biopsies for patients with suspected or progressive hepatic fibrosis. MATERIALS AND METHODS. Between May 1, 2015, and December 31, 2017, our prospective study evaluated 111 adult liver transplant patients (age range, 23-79 years) who underwent 147 ultrasound (US) SWE examinations of the right hepatic lobe followed by biopsies. SWE values were compared with the histologic fibrosis (Metavir) scores of the biopsy samples. SWE threshold values were determined using classification and regression tree analysis by anchoring to the degree of fibrosis. The sensitivity, specificity, positive predictive value, and negative predictive value (with 95% CIs) were calculated on the basis of the threshold value. Overall prediction accuracy was estimated using the AUC value from the ROC curve. RESULTS. From the 147 US SWE examinations and liver biopsies, consistent threshold values were identified for patients with no or minimal fibrosis (Metavir scores of F0 and F1, respectively) compared with significant fibrosis (Metavir scores of F2, F3, or F4). A median SWE value of 1.76 m/s or less denoted no or minimal fibrosis, whereas a value greater than 1.76 m/s denoted significant fibrosis. The sensitivity of US SWE examinations in classifying fibrosis was 0.77 (95% CI, 0.5-0.93). The specificity, positive predictive value, and negative predictive value were 0.79 (95% CI, 0.71-0.86), 0.33 (95% CI, 0.19-0.49), and 0.96 (95% CI, 0.91-0.99), respectively. CONCLUSION. Liver transplant patients may avoid liver biopsy if US SWE examination shows a median shear wave velocity of 1.76 or less, which corresponds to a Metavir score of F0 or F1, denoting no or minimal fibrosis.