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.

MATERIALS AND METHODS: A total of 84 patients with treatment-naïve invasive breast cancer were enrolled into this retrospective study. The tumour stroma ratio (TSR) was estimated from the amount of tumour stroma in the pathology specimen of the breast tumour. The MRI images of the patients were analysed based on Breast Imaging Reporting and Data Systems (ACR-BIRADS) for qualitative features which include T2- weighted, diffusion-weighted images (DWI) and dynamic contrast-enhanced (DCE) for kinetic features. The mean signal intensity (SI) of Short Tau Inversion Recovery (STIR), with the ratio of STIR of the lesion and pectoralis muscle (L/M ratio) and apparent diffusion coefficient (ADC) value, were measured for the quantitative features. Correlation tests were performed to assess the relationship between TSR and MRI features.

RESULTS: There was a significant correlation between the margin of mass, enhancement pattern, and STIR signal intensity of breast cancer and TSR. There were 54.76% (n = 46) in the low stromal group and 45.24% (n = 38) in the high stromal group. A significant association were seen between the margin of the mass and TSR (p = 0.034) between the L/M ratio (p <0.001), and between STIR SI of the lesion and TSR (p<0.001). The median L/M ratio was significantly higher in the high TSR group as compared to the lower TSR group (p < 0.001).

MATERIALS AND METHODS: The AGA is a new measured angle formed between the line from midglenoid to lateral end of the acromion with the line parallel to the glenoid surface. The AGA was measured in a group of 85 shoulders with RCT, 49 with GHOA and 103 non-RCT/GHOA control shoulders. The AGA was compared with other radiological parameters, such as, the critical shoulder angle (CSA), the acromion index (AI) and the acromiohumeral interval (AHI). Correlational and regression analysis were performed using SPSS 20.

RESULTS: The mean AGA was 50.9° (45.2-56.5°) in the control group, 53.3° (47.6-59.1°) in RCT group and 45.5° (37.7-53.2°) in OA group. Among patients with AGA > 51.5°, 61% were in the RCT group and among patients with AGA < 44.5°, 56% were in OA group. Pearson correlation analysis had shown significant correlation between AGA and CSA ( r = 0.925, p < 0.001). It was also significant of AHI in RCT group with mean 6.6 mm (4.7-8.5 mm) and significant AI in OA group with mean 0.68 (0.57-0.78) with p value < 0.001 respectively.

METHODS: A cross-sectional study was conducted in a locality within Selangor, sampling a total of 1449 young adults. The Cyberbullying and Online Aggression Survey was used to measure cyberbullying victimisation. The Family APGAR scale, General Health Questionnaire, Pittsburgh Sleep Quality Index and single-item measures were used to assess family dysfunction, psychological distress and health behaviour, respectively.

RESULTS: The 1-month prevalence of cyberbullying victimisation among young adults was 2.4%. The most common cyberbullying act experienced was mean or hurtful comments about participants online (51.7%), whereas the most common online environment for cyberbullying to occur was social media (45.8%). Male participants (adjusted OR (AOR)=3.60, 95% CI=1.58 to 8.23) had at least three times the odds of being cyberbullied compared with female participants. Meanwhile, participants with higher levels of psychological distress had increased probability of being cyberbullied compared with their peers (AOR=1.13, 95% CI=1.05 to 1.21).