OBJECTIVE: This study aims to evaluate the diagnostic efficacy of abbreviated MRI protocol in detecting breast cancer in screening and diagnostic populations, using histopathology as the reference standard.

MATERIALS AND METHODS: This is a single-centre retrospective cross-sectional study of 134 patients with 198 histologically proven breast lesions who underwent full diagnostic protocol contrast-enhanced breast MRI (FDP-MR) at the University Malaya Medical Centre (UMMC) from 1st January 2018 to 31st December 2019. AB-MR was pre-determined and evaluated with regard to the potential to detect and exclude malignancy from 3 readers of varying radiological experiences. The sensitivity of both AB-MR and FDP-MR were compared using the McNemar test, where both protocols' diagnostic performances were assessed via the receiver operating characteristic (ROC) curve. Inter-observer agreement was analysed using Fleiss Kappa.

RESULT: There were 134 patients with 198 lesions. The average age was 50.9 years old (range 27 - 80). A total of 121 (90%) MRIs were performed for diagnostic purposes. Screening accounted for 9.4% of the cases, 55.6% (n=110) lesions were benign, and 44.4% (n=88) were malignant. The commonest benign and malignant lesions were fibrocystic change (27.3%) and invasive ductal carcinoma (78.4%). The mean sensitivity, specificity, positive predictive value, and negative predictive value for AB-MR were 0.96, 0.57, 0.68 and 0.94, respectively. Both AB-MR and FDP-MR showed excellent diagnostic performance with AUC of 0.88 and 0.96, respectively. The general inter-observer agreement of all three readers for AB-MR was substantial (k=0.69), with fair agreement demonstrated between AB-MR and FDP-MR (k=0.36).

MATERIALS AND METHODS: This was a single-centre cross-sectional study of 115 women with American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BIRADS) breast density C and D on DBT with breast lesions who underwent AB-MR from June 2018 to December 2021. AB-MR was performed on a 3 T MRI system with an imaging protocol consisting of three sequences: axial T1 fat-saturated unenhanced; axial first contrast-enhanced; and subtracted first contrast-enhanced with maximum intensity projection (MIP). DBT and AB-MR images were evaluated by two radiologists blinded to the histopathology and patient outcomes. Diagnostic accuracy (sensitivity, specificity, positive predictive value [PPV] and negative predictive value [NPV]) was assessed.

RESULT: Of the 115 women, the mean age was 50.6 years. There were 48 (41.7%) Malay, 54 (47%) Chinese, and 12 (10.4%) Indian women. The majority (n=87, 75.7%) were from the diagnostic population. Sixty-one (53.1%) were premenopausal and 54 (46.9%) postmenopausal. Seventy-eight (72.4%) had an increased risk of developing breast cancer. Ninety-one (79.1%) women had density C and 24 (20.9%) had density D. There were 164 histopathology-proven lesions; 69 (42.1%) were malignant and 95 (57.9%) were benign. There were 62.8% (n=103/164) lesions detected at DBT. All the malignant lesions 100% (n=69) and 35.7% (n=34) of benign lesions were detected. Of the 61 lesions that were not detected, 46 (75.4%) were in density C, and 15 (24.6%) were in density D. The sensitivity, specificity, PPV, and NPV for DBT were 98.5%, 34.6%, 66.3%, and 94.7%, respectively. There were 65.2% (n=107/164) lesions detected on AB-MR, with 98.6% (n=68) malignant and 41.1% (39) benign lesions detected. The sensitivity, specificity, PPV, and NPV for AB-MR were 98.5%, 43.9%, 67.2%, and 96.2%, respectively. One malignant lesion (0.6%), which was a low-grade ductal carcinoma in-situ (DCIS), was missed on AB-MR.

METHODS: Patients with AIH-ACLF without baseline infection/hepatic encephalopathy were identified from APASL ACLF research consortium (AARC) database. Diagnosis of AIH-ACLF was based mainly on histology. Those treated with steroids were assessed for non-response (defined as death or liver transplant at 90 days for present study). Laboratory parameters, AARC, and model for end-stage liver disease (MELD) scores were assessed at baseline and day 3 to identify early non-response. Utility of dynamic SURFASA score [- 6.80 + 1.92*(D0-INR) + 1.94*(∆%3-INR) + 1.64*(∆%3-bilirubin)] was also evaluated. The performance of early predictors was compared with changes in MELD score at 2 weeks.

METHODS: We recruited ACLF patients between 2009 and 2020 from APASL-ACLF Research Consortium (AARC). Their clinical data, investigations and organ involvement were serially noted for 90-days and utilized for AI modelling. Data were split randomly into train and validation sets. Multiple AI models, MELD and AARC-Model, were created/optimized on train set. Outcome prediction abilities were evaluated on validation sets through area under the curve (AUC), accuracy, sensitivity, specificity and class precision.