Objective: To investigate the correlation between MRI findings and histological features for preoperative prediction of histological grading and Ki-67 expression level in alveolar soft part sarcoma (ASPS). Methods: A retrospective analysis was conducted on 63 ASPS patients (Jan 2017–May 2023). All patients underwent 3.0-T MRI examinations, including conventional sequences, dynamic contrast-enhanced scans with time-intensity curve analysis, and diffusion-weighted imaging with apparent diffusion coefficient (ADC) measurements. Patients were divided into low-grade (histological Grade I) and high-grade (histological Grade II/III) groups based on pathology. Immunohistochemistry was used to assess Ki-67 expression levels in ASPS. Statistical analysis included chi-square tests, Wilcoxon rank-sum test, binary logistic regression analysis, Spearman correlation analysis, and receiver operating characteristic curve analysis of various observational data. Results: There were 29 low-grade and 34 high-grade patients (26 males and 37 females) and a wide age range (5–68 years). Distant metastasis, tumor enhancement characteristics, and ADC values were independent predictors of high-grade ASPS. High-grade ASPS had lower ADC values (p = 0.002), with an area under the curve (AUC), sensitivity, and specificity of 0.723, 79.4%, and 58.6%, respectively, for high-grade prediction. There was a negative correlation between ADC values and Ki-67 expression (r = −0.526; p < 0.001). When the cut-off value of ADC was 0.997 × 10⁻³ mm²/s, the AUC, sensitivity, and specificity for predicting high Ki-67 expression were 0.805, 65.6%, and 83.9%, respectively. Conclusion: Qualitative and quantitative MRI parameters are valuable for predicting histological grading and Ki-67 expression levels in ASPS. Critical relevance statement: This study will help provide a more nuanced understanding of ASPS and guide personalized treatment strategies. Key Points: There is limited research on assessing ASPS prognosis through MRI. Metastasis, enhancement, and ADC correlated with histological grade; ADC related to Ki-67 expression. MRI provides clinicians with valuable information on ASPS grading and proliferation activity. Graphical

Background: Differentiating molecular subtypes and identifying biological markers in breast cancer (BC) are essential for prognostic stratification and treatment selection. This study aimed to compare the effectiveness of amide proton transfer-weighted imaging (APTWI) and diffusion-weighted imaging (DWI) in differentiating molecular subtypes and predicting the biological status of BC. Methods: This retrospective study included 109 women (aged 50.8±10.8 years) with BC who underwent 3T APTWI and DWI between May 2023 and January 2024. Patients were categorized by molecular subtypes and expression levels of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67. Magnetization transfer ratio asymmetry (MTRasym) and apparent diffusion coefficient (ADC) values were measured. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the performance of MTRasym and ADC values in distinguishing subtypes. Pearson’s correlation analysis was used to examine the relationship between MTRasym, ADC values, and the Ki-67 proliferation index. Results: Triple-negative (TN) cancers (3.03%±0.56%) had significantly higher MTRasym values than luminal A (2.25%±1.00%) and luminal B (2.39%±0.81%) cancers (P=0.006, 0.012). HER2-enriched cancers (2.93%±0.71%) also had significantly higher MTRasym than luminal A cancers (P=0.039). MTRasym and ADC values were significantly higher in ER-negative (ER−) than they were in ER-positive (ER+) cancers (P<0.001, P=0.040), and MTRasym values were higher in PR-negative (PR−) and high-Ki-67 cancers (P<0.001, P=0.013). AUC values for MTRasym ranged from 0.699 to 0.799, depending on the subtype and biological marker comparison. MTRasym and ADC values showed a weak positive correlation with the Ki-67 index (r=0.37, P<0.001, and r=0.31, P=0.003). Conclusions: APTWI is more effective than DWI for differentiating BC subtypes and predicting biological markers, providing valuable insights for clinical management.

Purpose: To evaluate the effectiveness of using a modified lung imaging reporting and data system (Lung-RADS) for risk stratification of pure ground-glass nodules (pGGNs) in low-dose computed tomography (LDCT) for lung cancer (LC) screenings in China. Patients and Methods: Eight subjects with nine pGGNs originating from a Cancer Screening Program were enrolled as training set and 32 asymptomatic subjects with 35 pGGNs were selected as validation set from November 2013 to October 2018. The complementary Lung-RADS categories were set based on the GGN-vessel relationship (GVR). The correlations between GGN-vessel relationships and pathology were evaluated, and the diagnostic value of complementary Lung-RADS version 1.1 in discriminating malignant pGGNs were analyzed. Results: The inter-reader agreements for Lung-RADS 1.1 (intraclass correlation coefficient (ICC= 0.999) and complementary Lung-RADS 1.1 (ICC= 0.971) displayed good reliability. The combined incidence of invasive adenocarcinoma in type III and IV was more than that of benign and preinvasive diseases (30% vs 75%, P=0.013). Type II GVR between two benign (66.7%), seven preinvasive (53.8%), and six invasive (21.4%) GGN cases was statistically significant (chi(2) =5.415, P=0.019). GGN pathological groups and GVR had a significant correlation (r=0.584, P=0.00). Compared to Lung-RADS 1.1, complementary Lung-RADS 1.1 had better performance in the training set, with its sensitivity increased from 33.3% to 88.9%, accuracy increased from 44.4% to 88.9%, false-negative proportion (FNP) decreased from 66.7% to 11.1%, and the sensitivity to predict malignant nodules increased from 13.8% to 93.1%, accuracy increased from 28.6% to 80.0%, and FNP decreased from 86.2% to 6.9% in validation set. The detection rate of preinvasive disease and adenocarcinoma was increased from 12.5% to 90.6% and that of missed diagnosis decreased from 87.5% to 9.4% in the validation set, P=0.004. Conclusion: Complementary Lung-RADS 1.1 is superior to Lung-RADS 1.1 and would be beneficial for LC screening of LDCT in China.