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.
CONCLUSIONS: Qualitative and quantitative MRI parameters are valuable for predicting histological grading and Ki-67 expression levels in ASPS.
UNASSIGNED: This study will help provide a more nuanced understanding of ASPS and guide personalized treatment strategies.
CONCLUSIONS: 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.

UNASSIGNED: To assess the diagnostic utility of clinical magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) in distinguishing between histological grading and isocitrate dehydrogenase (IDH) classification in adult diffuse gliomas.
UNASSIGNED: A retrospective analysis was conducted on 247 patients diagnosed with adult diffuse glioma. Experienced radiologists evaluated DWI and MRS images. The Kruskal-Wallis test examined differences in DWI and MRS-related parameters across histological grades, while the Mann-Whitney U test assessed molecular classification. Receiver Operating Characteristic (ROC) curves evaluated parameter effectiveness. Survival curves, stratified by histological grade and IDH classification, were constructed using the Kaplan-Meier test.
UNASSIGNED: The cohort comprised 141 males and 106 females, with ages ranging from 19 to 85 years. The Kruskal-Wallis test revealed significant differences in ADC mean, Cho/NAA, and Cho/Cr concerning glioma histological grade (P < .01). Subsequent application of Dunn\'s test showed significant differences in ADC mean among each histological grade (P < .01). Notably, Cho/NAA exhibited a marked distinction between grade 2 and grade 3/4 gliomas (P < .01). The Mann-Whitney U test indicated that only ADC mean showed statistical significance for IDH molecular classification (P < .01). ROC curves were constructed to demonstrate the effectiveness of the specified parameters. Survival curves were also delineated to portray survival outcomes categorized by histological grade and IDH classification. Conclusions: Clinical MRS demonstrates efficacy in glioma histological grading but faces challenges in IDH classification. Clinical DWI\'s ADC mean parameter shows significant distinctions in both histological grade and IDH classification.

UNASSIGNED: Breast cancer has the second highest mortality rate of all cancers and occurs mainly in women.
UNASSIGNED: To investigate the relationship between magnetic resonance imaging (MRI) radiomics features and histological grade of invasive ductal carcinoma (IDC) of the breast and to evaluate its diagnostic efficacy.
UNASSIGNED: The two conventional MRI quantitative indicators, i.e. the apparent diffusion coefficient (ADC) and the initial enhancement rate, were collected from 112 patients with breast cancer. The breast cancer lesions were manually segmented in dynamic contrast-enhanced MRI (DCE-MRI) and ADC images, the differences in radiomics features between Grades I, II and III IDCs were compared and the diagnostic efficacy was evaluated.
UNASSIGNED: The ADC values (0.77 ± 0.22 vs 0.91 ± 0.22 vs 0.92 ± 0.20, F= 4.204, p< 0.01), as well as the B_sum_variance (188.51 ± 67.803 vs 265.37 ± 77.86 vs 263.74 ± 82.58, F= 6.040, p< 0.01), L_energy (0.03 ± 0.02 vs 0.13 ± 0.11 vs 0.12 ± 0.14, F= 7.118, p< 0.01) and L_sum_average (0.78 ± 0.32 vs 16.34 ± 4.23 vs 015.45 ± 3.74, F= 21.860, p< 0.001) values of patients with Grade III IDC were significantly lower than those of patients with Grades I and II IDC. The B_uniform (0.15 ± 0.12 vs 0.11 ± 0.04 vs 0.12 ± 0.03, F= 3.797, p< 0.01) and L_SRE (0.85 ± 0.07 vs 0.78 ± 0.03 vs 0.79 ± 0.32, F= 3.024, p< 0.01) values of patients with Grade III IDC were significantly higher than those of patients with Grades I and II IDC. All differences were statistically significant (p< 0.05). The ADC radiomics signature model had a higher area-under-the-curve value in identifying different grades of IDC than the ADC value model and the DCE radiomics signature model (0.869 vs 0.711 vs 0.682). The accuracy (0.812 vs 0.647 vs 0.710), specificity (0.731 vs 0.435 vs 0.342), positive predictive value (0.815 vs 0.663 vs 0.669) and negative predictive value (0.753 vs 0.570 vs 0.718) of the ADC radiomics signature model were all significantly better than the ADC value model and the DCE radiomics signature model.
UNASSIGNED: ADC values and breast MRI radiomics signatures are significant in identifying the histological grades of IDC, with the ADC radiomics signatures having greater value.

Intervertebral disc degeneration (IVDD) is a major cause of low back pain, and several studies have evaluated the efficacy of extracellular vesicles (EVs) in the treatment of IVDD. The databases PubMed, Embase, and Cochrane Library were systematically searched from inception to the end of 2022 to identify studies investigating the therapeutic potential of cell-derived EVs for IVDD treatment. The following outcome measures were utilized: magnetic resonance imaging (MRI) Pfirrmann grading system, disc height index (DHI), histological grading, and apoptosis rate. A comprehensive meta-analysis was conducted, including a total of 13 articles comprising 19 studies involving 218 experimental animals. Comparative analysis between normal cell-derived EVs and placebo revealed significant reductions in MRI grade, increased DHI values, decreased nucleus pulposus cell apoptosis rates, and improved tissue grades. These findings collectively demonstrate the effective inhibition of IVDD through the application of EVs derived from cells. In conclusion, this study provides an updated synthesis of evidence supporting the efficacy of EVs as a promising therapeutic approach for IVDD treatment.

OBJECTIVE: Accurate preoperative radiological staging of adult-type diffuse glioma is crucial for effective prognostic stratification and selection of appropriate therapeutic interventions. The purpose of this study was to compare the effectiveness of apparent diffusion coefficient (ADC) maps generated from ultrahigh b-value diffusion-weighted imaging (DWI) for molecular grading with that for histological grading of adult-type diffuse glioma, and to evaluate the correlation between these ADC maps and molecular and histological biomarkers.
METHODS: This study retrospectively enrolled forty adult-type diffuse glioma patients, diagnosed using the 2021 WHO classification criteria. Preoperative imaging data, including multiple b-value DWI and conventional magnetic resonance imaging, were collected. Tumors were graded using both histological and molecular criteria. Histogram analysis was conducted to generate 14 parameters for each tumor. Receiver operating characteristic curves and the area under the curve (AUC) were used to evaluate tumor grading and molecular status differentiation. Analysis of histological biomarkers was performed by calculating the Pearson and Spearman correlation coefficients of continuous and hierarchical variables, respectively.
RESULTS: The intensity-related parameters for molecular grading were found to be superior to those for histological grading for the identification of WHO grade 4 (WHO4) adult-type diffuse glioma. The AUC of both grading systems increased with increasing b-values, with ADC8000-based histogram parameters showing the best results (molecular grading, square root: AUC = 0.897; histological grading, median: AUC = 0.737). The intensity-related parameters could also differentiate molecular WHO4 gliomas from histologically lower-grade gliomas (ADC8000-based square root: AUC = 0.919), and different ADC8000-based kurtosis was observed between molecular and histological WHO4 gliomas (AUC = 0.833). Significant correlations between the Ki-67 index and molecular status prediction for IDH, CDKN2A, and EGFR were also demonstrated.
CONCLUSIONS: The histogram parameters derived from high b-value ADC maps were found to be more effective for differentiating molecular grades of WHO4 adult-type diffuse glioma than for differentiating histological grades.

OBJECTIVE: Histological grade and molecular subtype have presented valuable references in assigning personalized or precision medicine as the significant prognostic indicators representing biological behaviors of invasive breast cancer (IBC). To evaluate a two-stage deep learning framework for IBC grading that incorporates with molecular-subtype (MS) information using DCE-MRI.
METHODS: In Stage I, an innovative neural network called IOS2-DA is developed, which includes a dense atrous-spatial pyramid pooling block with a pooling layer (DA) and inception-octconved blocks with double kernel squeeze-and-excitations (IOS2). This method focuses on the imaging manifestation of IBC grades and performs preliminary prediction using a novel class F1-score loss function. In Stage II, a MS attention branch is introduced to fine-tune the integrated deep vectors from IOS2-DA via Kullback-Leibler divergence. The MS-guided information is weighted with preliminary results to obtain classification values, which are analyzed by ensemble learning for tumor grade prediction on three MRI post-contrast series. Objective assessment is quantitatively evaluated by receiver operating characteristic curve analysis. DeLong test is applied to measure statistical significance (P < 0.05).
RESULTS: The molecular-subtype guided IOS2-DA performs significantly better than the single IOS2-DA in terms of accuracy (0.927), precision (0.942), AUC (0.927, 95% CI: [0.908, 0.946]), and F1-score (0.930). The gradient-weighted class activation maps show that the feature representations extracted from IOS2-DA are consistent with tumor areas.
CONCLUSIONS: IOS2-DA elucidates its potential in non-invasive tumor grade prediction. With respect to the correlation between MS and histological grade, it exhibits remarkable clinical prospects in the application of relevant clinical biomarkers to enhance the diagnostic effectiveness of IBC grading. Therefore, DCE-MRI tends to be a feasible imaging modality for the thorough preoperative assessment of breast biological behavior and carcinoma prognosis.

BACKGROUND: The difference between clinical characteristics and outcomes between follicular lymphoma grade 1-2 (FL1-2) and FL3a defined pathologically remains unclear, resulting in uncertainty how to treat FL3a. However, it may be crucial for clinicians to discriminate grade 3a and grade 1-2 for predicting prognosis and thus making treatment decisions.
METHODS: We compared 1403 patients with FL1-2 and 765 patients with FL3a diagnosed between January 2000 and December 2020 from fifteen centers nationwide in China to describe differences in clinical characteristics and outcomes.
RESULTS: Compared with FL1-2 patients, FL3a subgroup had a higher percentage of elderly patients (P = 0.003), and relatively more FL3a patients presented with increased levels of LDH (P < 0.0001) and higher Ki-67 indexs greater than 30% (P < 0.001). More FL3a patients were treated with CHOP ± R (P < 0.0001), and fewer were treated with the watchful-waiting approach (P < 0.0001). The results showed a higher incidence of relapse among FL3a patients, in which more patients underwent histological transformation (HT) when compared to FL1-2 (P = 0.003). 1470 (76.2%) patients of the entire cohort received R-CHOP therapy; survival analysis revealed that FL3a patients had a worse progression-free survival (PFS) rate than FL1-2 patients. Survival of FL3a patients with respect to FLIPI showed an inferior PFS in the intermediate and high-risk groups than FL1-2 patients. FL3a patients had a much worse prognosis than FL1-2 with or without progression of disease within 24 months (POD24). FL3a patients had higher likelihood of lymphoma-related death (LRD, P < 0.05), whereas the rates for non-LRD were comparable.
CONCLUSIONS: In conclusion, this study demonstrates a marked difference in clinical features and outcomes in FL3a patients compared with FL1-2 patients. The results highlight the need for applying therapeutic approaches distinct from FL1-2 when treating FL3a patients.

The WHO Classification of Thoracic Tumors (5(th) edition) mainly has the following changes in the chapter of pleural malignant mesothelioma. (1) The concept of mesothelioma in situ and its diagnostic method have been established for the first time; (2) The tumour grading of pleural malignant mesothelioma was added, it was divided into low grade and high grade according to the cellular atypia, mitotic activity and presence of necrosis. (3) The morphological features of pleural malignant mesothelioma was classified into architectural pattern, cellular and stromal features, the correlation between histological features and prognosis was refined, and some of the controversial cellular types have been reclassified. In this review, we introduced the changes of related pathologic diagnosis, in the WHO Classification of Thoracic Tumors (5(th) edition) and discussed its clinical significance.
《WHO胸部肿瘤分类（第五版）》在胸膜恶性间皮瘤部分主要有以下几点变化：1.确立了原位间皮瘤的概念及其诊断方法；2.新增了胸膜恶性间皮瘤的肿瘤分级，即根据上皮样间皮瘤的细胞异型性、核分裂活性及有无坏死分为低级别和高级别；3.把胸膜恶性间皮瘤的组织学特征分为组织结构、细胞及间质特征，细化了组织学特征与预后的相关性，同时对部分有争议的组织学形态进行了归类。本文主要围绕新版WHO分类病理学诊断相关的主要变化，对其临床意义进行了讨论。.

Gliomas are the most common type of central nervous system tumors in children, and the combination of histological and molecular classification is essential for prognosis and treatment. Here, we proposed a newly developed microstructural mapping technique based on diffusion-time-dependent diffusion MRI td-dMRI theory to quantify tumor cell properties and tested these microstructural markers in identifying histological grade and molecular alteration of H3K27.
This prospective study included 69 pediatric glioma patients aged 6.14 ± 3.25 years old, who underwent td-dMRI with pulsed and oscillating gradient diffusion sequences on a 3T scanner. dMRI data acquired at varying tds were fitted into a 2-compartment microstructural model to obtain intracellular fraction (fin), cell diameter, cellularity, etc. Apparent diffusivity coefficient (ADC) and T1 and T2 relaxation times were also obtained. H&E stained histology was used to validate the estimated microstructural properties.
For histological classification of low- and high-grade pediatric gliomas, the cellularity index achieved the highest area under the receiver-operating-curve (AUC) of 0.911 among all markers, while ADC, T1, and T2 showed AUCs of 0.906, 0.885, and 0.886. For molecular classification of H3K27-altered glioma in 39 midline glioma patients, cell diameter showed the highest discriminant power with an AUC of 0.918, and the combination of cell diameter and extracellular diffusivity further improved AUC to 0.929. The td-dMRI estimated fin correlated well with the histological ground truth with r = 0.7.
The td-dMRI-based microstructural properties outperformed routine MRI measurements in diagnosing pediatric gliomas, and the different microstructural features showed complementary strength in histological and molecular classifications.

The aim of the present study was to compare the diagnostic performance of the main parameters derived from diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) regarding the detection and grading of hepatocellular carcinoma (HCC). A total of 78 patients diagnosed with HCC by biopsy were prospectively enrolled in the present study, and underwent routine magnetic resonance imaging (MRI), DWI, IVIM, DKI and contrast-enhanced MRI prior to surgery. Measurements, including mean diffusivity (MD), mean diffusional kurtosis (MK), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and apparent diffusion coefficient (ADC), were compared with grading HCC using one-way ANOVA followed by the Student-Neuman-Keuls-q post-hoc test. Spearman\'s correlation coefficient was used to analyze the correlation between each parameter and pathological grade, while the diagnostic efficiency was evaluated using a receiver operating characteristic (ROC) curve. The 78 patients enrolled in the present study were grouped into highly (n=22), moderately (n=41) or poorly (n=15) differentiated HCC groups according to the criteria of Pathology and Genetics Tumors of the Digestive System. MK values differed significantly between different grades and decreased gradually with the degree of tumor differentiation. The MD, D and ADC values in the highly differentiated HCC group were significantly higher than those in the moderately or poorly differentiated HCC groups (all P<0.001), whereas no significant differences were observed in D* or f (P=0.502 and P=0.853, respectively). A significant correlation was observed between MK, MD, D and ADC, and HCC grades (r=0.705, r=0.570, r=0.423 and r=0.687, respectively). The comparison of the ROC curves of MK, MD, D, ADC, D* and f values for predicting highly differentiated HCC suggested that MK and D were the best indicators for predicting highly differentiated HCC, as the area under the ROC curve (AUC) of MK and D was significantly higher than that of ADC (Z=2.247 and 2.428, P=0.025 and 0.016, respectively), whereas non-statistically significant differences were observed in the AUC values between MK and D (Z=0.072; P=0.942). The DKI-derived MK and IVIM-derived D values had a similar diagnostic performance and were superior to ADC in discriminating the histological grade of HCC. In addition, the combination of MK and D values exhibited an improved diagnostic performance.