Computational Pathology for Prediction of Isocitrate Dehydrogenase Gene Mutation from Whole Slide Images in Adult Patients with Diffuse Glioma.

Isocitrate dehydrogenase gene (IDH) mutation is one of the most important molecular markers of glioma. Accurate detection of IDH status is a crucial step for integrated diagnosis of adult-type diffuse gliomas. Herein, a clustering-based hybrid of a convolutional neural network and a vision transformer deep learning model was developed to detect IDH mutation status from annotation-free hematoxylin and eosin-stained whole slide pathologic images of 2275 adult patients with diffuse gliomas. For comparison, a pure convolutional neural network, a pure vision transformer, and a classic multiple-instance learning model were also assessed. The hybrid model achieved an area under the receiver operating characteristic curve of 0.973 in the validation set and 0.953 in the external test set, outperforming the other models. The hybrid model's ability in IDH detection between difficult subgroups with different IDH status but shared histologic features, achieving areas under the receiver operating characteristic curve ranging from 0.850 to 0.985 in validation and test sets. These data suggest that the proposed hybrid model has a potential to be used as a computational pathology tool for preliminary rapid detection of IDH mutation from whole slide images in adult patients with diffuse gliomas.

Construction of a nomogram model for deep vein thrombosis in patients with tibial plateau fracture based on the Systemic Inflammatory Response Index.

BACKGROUND: In recent years, the incidence of tibial plateau fracture has been on the rise, predominantly affecting the elderly population. Deep vein thrombosis may lead to poor prognosis in patients. the Systemic Inflammatory Response Index are novel biomarkers of inflammation, and this study aims to verify their predictive effect and construct the nomogram model. METHOD: This study used binary logistic regression analysis to predict the predictive effect of SIRI on the occurrence of DVT in tibial plateau fracture patients. And use R studio to construct nomogram model. RESULT: The results showed that NC (7.036 [3.516, 14.080], p < 0.001), LYM (0.507 [0.265, 0.969], p = 0.04), and SIRI (2.090 [1.044, 4.182], p = 0.037) were independent predictive factors for DVT. The nomogram demonstrated good predictive performance with small errors in both the training and validation groups, and most clinical patients could benefit from them. CONCLUSION: The nomogram constructed based on SIRI can assist clinicians in early assessment of the probability of DVT occurrence.

Analysis of Associated Factors, Construction, and Application of a Predictive Model for Lymph Node Metastasis in Colorectal Cancer.

Background: In colorectal cancer (CRC) , understanding lymph node metastasis (LNM) is critical for effective treatment. Better approaches are required for identifying and assessing the risk contributions of factors influencing lymph node metastasis in colorectal cancer. Objective: This study aims to analyze factors associated with LNM in CRC and develop a risk prediction model. Methods: A retrospective cohort study was conducted and a total of 181 CRC patients admitted between March 2020 and April 2023 were selected as research participants. Among them, 47 patients developed LNM, while the remaining 134 did not. Clinical data, including age, sex, pathological stages, were collected. Logistic regression was employed to identify factors influencing LNM in CRC, forming the basis for constructing a risk model. The diagnostic efficiency of this model was assessed through receiver operating characteristic (ROC) curves. Results: Tumor nodules and histological types showed no correlation with LNM in CRC (P > .05). However, pathological staging, vascular and neural invasion, use of VEGF inhibitors, and preoperative CEA were identified as independent risk factors for LNM in CRC (P < .05). The established model demonstrated a good fit with the observations. ROC curve analysis indicated an area under the curve (AUC) of 0.884 for predicting LNM in CRC, signifying excellent predictive performance. Conclusions: The risk model, formulated on factors associated with LNM in CRC, serves as a efficient tool in assessing the probability of LNM. It provides invaluable insights that can significantly enhance clinical approaches to the diagnosis and treatment of CRC in the future.

Nomogram based on high-density lipoprotein cholesterol for the occurrence of preoperative deep vein thrombosis in patients with intertrochanteric femur fracture: a retrospective study.

BACKGROUND: This study aims to develop a nomogram and forecast the incidence of DVT in individuals suffering from an intertrochanteric femur fracture. METHOD: This work created a nomogram using the R programming language and employed logistic regression to determine independent predicting features. An external validation dataset was used to validate the nomogram. RESULT: The findings demonstrated the independence of LYM (0.02[0.01-0.09], p < 0.001), ALB (0.83[0.74, 0.94], p = 0.002), and HDL-C (0.18[0.04, 0.71], p = 0.014). Good prediction performance with modest errors was shown by the nomogram in both the training and validation groups. CONCLUSION: In conclusion, the nomogram that was created using HDL-C, ALB, and LYM can assist medical professionals in determining the likelihood that DVT will occur.

Ultrafast Response Organic Photoswitch Materials and Their Application in Volumetric 3D Display.

Volumetric three-dimensional (3D) display technology based on static screens is a crucial branch of 3D displays. The essential component in volumetric 3D displays is selectively excitable display media that can generate voxels at any position. Here, we synthesized a series of organic photoswitch materials to meet the specific requirements of 3D display mediums. In these photoswitch solutions, voxels are activated ultrafast within tens of picoseconds at the intersection of two control lasers and faded rapidly within tens of milliseconds when switching light is turned off. An experimental volumetric 3D display system utilizing an organic photoswitch solution as a screen is demonstrated. The system not only achieves a dynamic 3D display but also enables 360° viewing. The volumetric 3D display system can display true 3D images without auxiliary glasses and is expected to be applicable in fields as diverse as virtual reality, medical imaging, architectural design, and military visualization.

Clinicopathologic analysis of nodal T-follicular helper cell lymphomas, a multicenter retrospective study from China.

Background: Nodal T-follicular helper cell lymphomas (nTFHLs) represent a new family of peripheral T-cell lymphomas (PTCLs), and comparative studies of their constituents are rare. Methods: This study retrospectively enrolled 10 patients with nTFHL-F and 30 patients with nTFHL-NOS diagnosed between December 2017 and October 2023 at six large comprehensive tertiary hospitals; 188 patients with nTFHL-AI were diagnosed during the same period at the First Affiliated Hospital of Zhengzhou University for comparison. Results: Compared with nTFHL-AI, nTFHL-NOS patients exhibited better clinical manifestations, lower TFH expression levels, and a lower Ki-67 index. However, no differences in clinicopathological features were observed between nTFHL-F and nTFHL-AI patients as well as nTFHL-NOS patients. According to the survival analysis, the median OS for patients with nTFHL-NOS, nTFHL-AI, and nTFHL-F were 14.2 months, 10 months, and 5 months, respectively, whereas the median TTP were 14 months, 5 months, and 3 months, respectively. Statistical analysis revealed differences in TTP among the three subtypes(P=0.0173). Among the population of patients receiving CHOP-like induction therapy, there were significant differences in the OS and TTP among the nTFHL-NOS, nTFHL-AI, and nTFHL-F patients (P=0.0134, P=0.0205). Both the GDPT and C-PET regimens significantly improved the ORR, OS, and PFS in nTFHL patients. Conclusion: There are significant differences in the clinical manifestations, pathology, and survival outcomes among the three subtypes of nTFHLs. However, further research with a larger sample size, and involving clinical pathology and molecular genetics is needed to determine the distinctive biological characteristics of these tumors.

Peripheral T cell lymphoma initially presenting in lung biopsies: A diagnostic challenge.

BACKGROUND: Primary or secondary pulmonary involvement by peripheral T cell lymphoma (PTCL) is rare and difficult to diagnose particularly via lung biopsies. METHODS: 22 cases of PTCL diagnosed initially in lung biopsies between January 2006 and November 2020 were retrospectively reviewed followed at Nanjing Drum Tower Hospital and the First Affiliated Hospital of Zhengzhou University, respectively, including clinical manifestations, baseline biochemical indexes, images, histological findings and other available ancillary studies such as immunostaining, Epstein-Barr virus encoded RNA (EBER) in situ hybridization and T-cell receptor rearrangement analysis upon diagnosis. RESULTS: The median age of these patients was 59 years old (range: 29-82 years) at diagnosis. The majority of them complained of fever, cough and fatigue. Computed tomography scans mainly revealed multiple ill-defined nodules/masses of various sizes and densities with or without air bronchogram. Microscopically, most lesions showed lymphoid cells with clear cytoplasm and irregular nuclear contours diffusely infiltrating alveolar septa or alveolar spaces in an inflammatory background. Several cases had a predominance of small neoplastic cells (n = 4) with atypical, irregular nuclei. One case showed a diffuse monotonous pattern of growth. Angioinvasion and necrosis were not uncommon findings. The neoplastic cells in all cases were positive for one or more T-cell markers, and negative for B-cell-lineage antigens and EBER. 19 out of 22 patients had complete follow-up information, and 17 patients were dead at the last follow-up. CONCLUSIONS: Pulmonary involvement by PTCL is rare with dismal outcome. Aggressive clinical course and several clinicopathologic clues, albeit unspecific, may alert the pathologists of the possibilities of pulmonary PTCLs.

Immune cell early activation, apoptotic kinetic, and T-cell functional impairment in domestic pigs after ASFV CADC_HN09 strain infection.

African swine fever (ASF) caused by the African swine fever virus (ASFV) is a fatal and highly contagious disease of domestic pigs characterized by rapid disease progression and death within 2 weeks. How the immune cells respond to acute ASFV infection and contribute to the immunopathogenesis of ASFV has not been completely understood. In this study, we examined the activation, apoptosis, and functional changes of distinct immune cells in domestic pigs following acute infection with the ASFV CADC_HN09 strain using multicolor flow cytometry. We found that ASFV infection induced broad apoptosis of DCs, monocytes, neutrophils, and lymphocytes in the peripheral blood of pigs over time. The expression of MHC class II molecule (SLA-DR/DQ) on monocytes and conventional DCs as well as CD21 expression on B cells were downregulated after ASFV infection, implying a potential impairment of antigen presentation and humoral response. Further examination of CD69 and ex vivo expression of IFN-γ on immune cells showed that T cells were transiently activated and expressed IFN-γ as early as 5 days post-infection. However, the capability of T cells to produce cytokines was significantly impaired in the infected pigs when stimulated with mitogen. These results suggest that the adaptive cellular immunity to ASFV might be initiated but later overridden by ASFV-induced immunosuppression. Our study clarified the cell types that were affected by ASFV infection and contributed to lymphopenia, improving our understanding of the immunopathogenesis of ASFV.

Real-world data on ALK rearrangement test in Chinese advanced non-small cell lung cancer (RATICAL): a nationwide multicenter retrospective study.

BACKGROUND: Anaplastic lymphoma kinase (ALK) test in advanced non-small cell lung cancer (NSCLC) can help physicians provide target therapies for patients harboring ALK gene rearrangement. This study aimed to investigate the real-world test patterns and positive rates of ALK gene rearrangements in advanced NSCLC. METHODS: In this real-world study (ChiCTR2000030266), patients with advanced NSCLC who underwent an ALK rearrangement test in 30 medical centers in China between October 1, 2018 and December 31, 2019 were retrospectively analyzed. Interpretation training was conducted before the study was initiated. Quality controls were performed at participating centers using immunohistochemistry (IHC)-VENTANA-D5F3. The positive ALK gene rearrangement rate and consistency rate were calculated. The associated clinicopathological characteristics of ALK gene rearrangement were investigated as well. RESULTS: The overall ALK gene rearrangement rate was 6.7% in 23,689 patients with advanced NSCLC and 8.2% in 17,436 patients with advanced lung adenocarcinoma. The quality control analysis of IHC-VENTANA-D5F3 revealed an intra-hospital consistency rate of 98.2% (879/895) and an inter-hospital consistency rate of 99.2% (646/651). IHC-VENTANA-D5F3 was used in 53.6%, real-time polymerase chain reaction (RT-PCR) in 25.4%, next-generation sequencing (NGS) in 18.3%, and fluorescence in-situ hybridization (FISH) in 15.9% in the adenocarcinoma subgroup. For specimens tested with multiple methods, the consistency rates confirmed by IHC-VENTANA-D5F3 were 98.0% (822/839) for FISH, 98.7% (1,222/1,238) for NGS, and 91.3% (146/160) for RT-PCR. The overall ALK gene rearrangement rates were higher in females, patients of ≤ 35 years old, never smokers, tumor cellularity of > 50, and metastatic specimens used for testing in the total NSCLC population and adenocarcinoma subgroup (all P < 0.05). CONCLUSIONS: This study highlights the real-world variability and challenges of ALK test in advanced NSCLC, demonstrating a predominant use of IHC-VENTANA-D5F3 with high consistency and distinct clinicopathological features in ALK-positive patients. These findings underscore the need for a consensus on optimal test practices and support the development of refined ALK test strategies to enhance diagnostic accuracy and therapeutic decision-making in NSCLC.

Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning.

Cancer of unknown primary (CUP) site poses diagnostic challenges due to its elusive nature. Many cases of CUP manifest as pleural and peritoneal serous effusions. Leveraging cytological images from 57,220 cases at four tertiary hospitals, we developed a deep-learning method for tumor origin differentiation using cytological histology (TORCH) that can identify malignancy and predict tumor origin in both hydrothorax and ascites. We examined its performance on three internal (n = 12,799) and two external (n = 14,538) testing sets. In both internal and external testing sets, TORCH achieved area under the receiver operating curve values ranging from 0.953 to 0.991 for cancer diagnosis and 0.953 to 0.979 for tumor origin localization. TORCH accurately predicted primary tumor origins, with a top-1 accuracy of 82.6% and top-3 accuracy of 98.9%. Compared with results derived from pathologists, TORCH showed better prediction efficacy (1.677 versus 1.265, P < 0.001), enhancing junior pathologists' diagnostic scores significantly (1.326 versus 1.101, P < 0.001). Patients with CUP whose initial treatment protocol was concordant with TORCH-predicted origins had better overall survival than those who were administrated discordant treatment (27 versus 17 months, P = 0.006). Our study underscores the potential of TORCH as a valuable ancillary tool in clinical practice, although further validation in randomized trials is warranted.