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This study examined to evaluate the predictive value of a nomogram with Ki-67 in overall and disease-free survival in glioma patients, a total of 76 patients diagnosed with glioma by pathology in Tengzhou Central People's Hospital were enrolled. The baseline data and follow ups were retrospectively collected from medical records. The associations between Ki-67 and survival status were examined using log-rank test, univariate and multivariate Cox proportional hazard regression models. Calibrations were performed to validate the established nomograms. Ki-67 negative group showed of a longer OS survival time and a longer PFS survival time with log-rank test (x2 = 16.101, P < 0.001 and x2 = 16.961, P < 0.001). Age older than 50 years (HR = 2.074, 95% CI 1.097–3.923), abnormal treatment (HR = 2.932, 95% CI 1.343–6.403) and Ki-67 positive (HR = 2.722, 95% CI 1.097–6.755) were the independent predictive factors of death. High grade pathology (HR = 2.453, 95% CI 1.010–5.956) and Ki-67 positive (HR = 2.200, 95% CI 1.043–4.639) were the independent predictive factors of recurrence. The C-index for the nomogram of OS and PFS were 0.745 and 0.723, respectively. The calibration results showed that the nomogram could predict the overall and disease-free 1-year survival of glioma patients. In conclusion, the nomograms with Ki-67 as independent risk factor for OS and PFS could provide clinical consultation in the treatment and follow-up of malignant glioma. [ABSTRACT FROM AUTHOR]

Purpose: To explore the value of deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram in predicting the Ki-67 expression in rectal cancer. Methods: The data of 491 patients with rectal cancer from two centers were retrospectively analyzed and divided into training, internal validation, and external validation sets. They were categorized into high- and low-expression group based on postoperative pathological Ki-67 expression. Each patient's mp-MRI data were analyzed to extract and select the most relevant features of deep learning, and a deep learning model was constructed. Independent predictive risk factors were identified and incorporated into a clinical model, and the clinical and deep learning models were combined to obtain a nomogram for the prediction of Ki-67 expression. The performance characteristics of the DL-model, clinical model, and nomogram were assessed using ROCs, calibration curve, decision curve, and clinical impact curve analysis. Results: The strongest deep learning features were extracted and screened from mp-MRI data. Two independent predictive factors, namely Magnetic Resonance Imaging T (mrT) staging and differentiation degree, were identified through clinical feature selection. Three models were constructed: a deep learning (DL)-model, a clinical model, and a nomogram. The AUCs of clinical model in the training, internal validation, and external validation set were 0.69, 0.78, and 0.67, respectively. The AUCs of the deep model and nomogram ranged from 0.88 to 0.98. The prediction performance of the deep learning model and nomogram was significantly better than the clinical model (P < 0.001). Conclusion: The nomogram based on deep learning can help clinicians accurately and conveniently predict the expression status of Ki-67 in rectal cancer. [ABSTRACT FROM AUTHOR]

Proliferating cell nuclear antigen is a marker of cell proliferation and genomic maintenance. The protein undergoes several post-translational modifications that expand its playground and amplify its functions. Ubiquitylation, sumoylation, acetylation, phosphorylation, and nitrosylation are some of the modifications that confer a plethora of protein interactions with the antigen. These interactions regulate abundant functions like DNA replication, DNA damage control, and cell cycle control. Due to the versatile functions of the antigen, it may serve as a marker or target for therapeutic intervention for various diseases. This protein can be used as a marker for studies done to validate growth in medical and dental fields. The growth and proliferation of cells is a necessary factor for cancer to progress, both at primary and metastatic sites. It was proposed that PCNA can aid in not only the identification but also as a therapeutic agent for the disease due to its role in cell proliferation and DNA damage control. This review expounds on the structure and functions of PCNA. It discusses how the interactions of the antigen with other proteins can be used to block or enhance the functions of the cell being commanded by the antigen. [ABSTRACT FROM AUTHOR]

Mutations resulting in decreased activity of p53 tumor suppressor protein promote tumorigenesis. P53 protein levels are tightly regulated through the Ubiquitin Proteasome System (UPS). Several E3 ligases were shown to regulate p53 stability, including MDM2. Here we report that the ubiquitin E3 ligase XIAP (X-linked Inhibitors of Apoptosis) is a direct ligase for p53 and describe a novel approach for modulating the levels of p53 by targeting the XIAP pathway. Using in vivo (live-cell) and in vitro (cell-free reconstituted system) ubiquitylation assays, we show that the XIAP-antagonist ARTS regulates the levels of p53 by promoting the degradation of XIAP. XIAP directly binds and ubiquitylates p53. In apoptotic cells, ARTS inhibits the ubiquitylation of p53 by antagonizing XIAP. XIAP knockout MEFs express higher p53 protein levels compared to wild-type MEFs. Computational screen for small molecules with high affinity to the ARTS-binding site within XIAP identified a small-molecule ARTS-mimetic, B3. This compound stimulates apoptosis in a wide range of cancer cells but not normal PBMC (Peripheral Blood Mononuclear Cells). Like ARTS, the B3 compound binds to XIAP and promotes its degradation via the UPS. B3 binding to XIAP stabilizes p53 by disrupting its interaction with XIAP. These results reveal a novel mechanism by which ARTS and p53 regulate each other through an amplification loop to promote apoptosis. Finally, these data suggest that targeting the ARTS binding pocket in XIAP can be used to increase p53 levels as a new strategy for developing anti-cancer therapeutics. [ABSTRACT FROM AUTHOR]

Spinal clear cell meningiomas (CCMs) are a rare histological subtype of meningiomas that pose preoperative diagnostic challenges due to their radiographic similarities with other lesions. They are also more aggressive, exhibiting higher rates of recurrence, particularly in pediatric patients. Overcoming diagnostic challenges of these tumors can improve patient outcomes. In this report, we describe a case of a pediatric patient presenting with a lumbar CCM in whom we were able to obtain gross total resection. Our report reviews previously identified predictors of CCM recurrence, including the Ki-67 proliferation index, number of spinal segments involved, and hormonal influences related to age and sex. We describe the characteristic radiographic features that differentiate spinal CCMs from other tumors to improve pre-operative diagnosis. Furthermore, we provide our rationale for adjuvant therapy for pediatric patients to refine treatment protocols for these rare tumors. [ABSTRACT FROM AUTHOR]

Objectives: To distinguish isocitrate dehydrogenase (IDH) genotypes and tumor subtypes of adult-type diffuse gliomas based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5) in 2021 using standard, high, and ultra-high b-value diffusion-weighted imaging (DWI). Materials and methods: This prospective study enrolled 70 patients with adult-type diffuse gliomas who underwent multiple b-value DWI. Apparent diffusion coefficient (ADC) values including ADCb500/b1000, ADCb500/b2000, ADCb500/b3000, ADCb500/b4000, ADCb500/b6000, ADCb500/b8000, and ADCb500/b10000 in tumor parenchyma (TP) and contralateral normal-appearing white matter (NAWM) were calculated. The ADC ratios of TP/NAWM were assessed for correlations with IDH genotypes, tumor subtypes, and Ki-67 status; diagnostic performances were compared. Results: All ADCs were significantly higher in IDH mutant gliomas than in IDH wild-type gliomas (p < 0.01 for all); ADCb500/b8000 had the highest area under the curve (AUC) of 0.866. All ADCs were significantly lower in glioblastoma than in astrocytoma (p < 0.01 for all). ADCs other than ADCb500/b1000 were significantly lower in glioblastoma than in oligodendroglioma (p < 0.05 for all). ADCb500/b8000 and ADCb500/b10000 were significantly higher in oligodendroglioma than in astrocytoma (p = 0.034 and 0.023). The highest AUCs were 0.818 for ADCb500/b6000 when distinguishing glioblastoma from astrocytoma, 0.979 for ADCb500/b8000 and ADCb500/b10000 when distinguishing glioblastoma from oligodendroglioma, and 0.773 for ADCb500/b10000 when distinguishing astrocytoma from oligodendroglioma. Additionally, all ADCs were negatively correlated with Ki-67 status (p < 0.05 for all). Conclusion: Ultra-high b-value DWI can reliably separate IDH genotypes and tumor subtypes of adult-type diffuse gliomas using WHO CNS5 criteria. Clinical relevance statement: Ultra-high b-value diffusion-weighted imaging can accurately distinguish isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas, which may facilitate personalized treatment and prognostic assessment for patients with glioma. Key Points: • Ultra-high b-value diffusion-weighted imaging can accurately distinguish subtle differences in water diffusion among biological tissues. • Ultra-high b-value diffusion-weighted imaging can reliably separate isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas. • Compared with standard b-value diffusion-weighted imaging, high and ultra-high b-value diffusion-weighted imaging demonstrate better diagnostic performances. [ABSTRACT FROM AUTHOR]

Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Prostate cancer is a significant cause of cancer-related mortality among men worldwide, necessitating the exploration of prognostic biomarkers to aid in accurate risk assessment and treatment decision-making. This cross-sectional study aimed to comprehensively evaluate the role of Ki-67 as a prognostic marker in prostate cancer by examining its association with clinicopathological parameters. A total of 102 archived cases of prostate core biopsy specimens, histopathologically reported as prostate carcinoma, were included in this study. Histopathological grading was conducted using Gleason's scoring and grading system based on morphology. The statistical software "R" was utilized for data analysis. Kruskal–Wallis test and Fisher's exact test were employed to analyze the association between Ki-67 expression and clinicopathological parameters. The study revealed significant correlations between Ki-67 expression and various clinicopathological parameters in prostate cancer cases. High Ki-67 expression levels were associated with higher Gleason scores, increased incidence of perineural invasion, advanced T stages, lymph node metastasis, presence of distant metastasis, and higher prognostic stage groups. The findings of this cross-sectional study support the potential of Ki-67 as a prognostic marker in prostate cancer. The significant associations observed between Ki-67 expression and clinicopathological parameters indicate its usefulness in risk stratification and treatment decision-making. The incorporation of histopathological grading, including Gleason scoring, and analysis of perineural invasion strengthens the validity of the study. Ki-67, in combination with morphological assessments, provides valuable prognostic information for prostate cancer patients. [ABSTRACT FROM AUTHOR]

Purpose: To develop a contrast-enhanced ultrasound (CEUS) clinic-radiomics nomogram for individualized assessment of Ki-67 expression in hepatocellular carcinoma (HCC). Methods: A retrospective cohort comprising 310 HCC individuals who underwent preoperative CEUS (using SonoVue) at three different centers was partitioned into a training set, a validation set, and an external test set. Radiomics signatures indicating the phenotypes of the Ki-67 were extracted from multiphase CEUS images. The radiomics score (Rad-score) was calculated accordingly after feature selection and the radiomics model was constructed. A clinic-radiomics nomogram was established utilizing multiphase CEUS Rad-score and clinical risk factors. A clinical model only incorporated clinical factors was also developed for comparison. Regarding clinical utility, calibration, and discrimination, the predictive efficiency of the clinic-radiomics nomogram was evaluated. Results: Seven radiomics signatures from multiphase CEUS images were selected to calculate the Rad-score. The clinic-radiomics nomogram, comprising the Rad-score and clinical risk factors, indicated a good calibration and demonstrated a better discriminatory capacity compared to the clinical model (AUCs: 0.870 vs 0.797, 0.872 vs 0.755, 0.856 vs 0.749 in the training, validation, and external test set, respectively) and the radiomics model (AUCs: 0.870 vs 0.752, 0.872 vs 0.733, 0.856 vs 0.729 in the training, validation, and external test set, respectively). Furthermore, both the clinical impact curve and the decision curve analysis displayed good clinical application of the nomogram. Conclusion: The clinic-radiomics nomogram constructed from multiphase CEUS images and clinical risk parameters can distinguish Ki-67 expression in HCC patients and offer useful insights to guide subsequent personalized treatment. [ABSTRACT FROM AUTHOR]

Objectives: To develop and validate a contrast-enhanced computed tomography (CECT)–based radiomics nomogram for the preoperative evaluation of Ki-67 proliferation status in pancreatic ductal adenocarcinoma (PDAC). Methods: In this two-center retrospective study, a total of 181 patients (95 in the training cohort; 42 in the testing cohort, and 44 in the external validation cohort) with PDAC who underwent CECT examination were included. Radiomic features were extracted from portal venous phase images. The radiomics signatures were built by using two feature-selecting methods (relief and recursive feature elimination) and four classifiers (support vector machine, naive Bayes, linear discriminant analysis (LDA), and logistic regression (LR)). Multivariate LR was used to build a clinical model and radiomics-clinical nomogram. The predictive performances of the models were evaluated using area under receiver operating characteristic curve (AUC) and decision curve analysis (DCA). Results: The relief selector and LDA classifier using twelve features built the optimal radiomics signature, with AUCs of 0.948, 0.927, and 0.824 in the training, testing, and external validation cohorts, respectively. The radiomics-clinical nomogram incorporating the optimal radiomics signature, CT-reported lymph node status, and CA19-9 showed better predictive performance with AUCs of 0.976, 0.955, and 0.882 in the training, testing, and external validation cohorts, respectively. The calibration curve and DCA demonstrated goodness-of-fit and improved benefits in clinical practice of the nomogram. Conclusions: The radiomics-clinical nomogram is an effective and non-invasive computer-aided tool to predict the Ki-67 expression status in patients with PDAC. Clinical relevance statement: The radiomics-clinical nomogram is an effective and non-invasive computer-aided tool to predict the Ki-67 expression status in patients with pancreatic ductal adenocarcinoma. Key Points: The radiomics analysis could be helpful to predict Ki-67 expression status in patients with pancreatic ductal adenocarcinoma (PDAC). The radiomics-clinical nomogram integrated with the radiomics signature, clinical data, and CT radiological features could significantly improve the differential diagnosis of Ki-67 expression status. The radiomics-clinical nomogram showed satisfactory calibration and net benefit for discriminating high and low Ki-67 expression status in PDAC. [ABSTRACT FROM AUTHOR]

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Background: We investigated the value of three-dimensional amide proton transfer-weighted imaging (3D-APTWI) in the diagnosis of early-stage breast cancer (BC) and its correlation with the immunohistochemical characteristics of malignant lesions. Methods: Seventy-eight women underwent APTWI and dynamic contrast-enhanced (DCE)-MRI. Pathological results were categorized as either benign (n = 43) or malignant (n = 37) lesions. The parameters of APTWI and DCE-MRI were compared between the benign and malignant groups. The diagnostic value of 3D-APTWI was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) to establish a diagnostic threshold. Pearson's correlation was used to analyze the correlation between the magnetization transfer asymmetry (MTRasym) and immunohistochemical characteristics. Results: The MTRasym and time-to-peak of malignancies were significantly lower than those of benign lesions (all p < 0.010). The volume transfer constant, rate constant, and wash-in and wash-out rates of malignancies were all significantly greater than those of benign lesions (all p < 0.010). ROC-AUCs of 3D-APTWI, DCE-MRI, and 3D-APTWI+DCE to differential diagnosis between early-stage BC and benign lesions were 0.816, 0.745, and 0.858, respectively. Only the difference between AUCAPT+DCE and AUCDCE was significant (p < 0.010). When a threshold of MTRasym for malignancy for 2.42%, the sensitivity and specificity of 3D-APTWI for BC diagnosis were 86.5% and 67.6%, respectively; MTRasym was modestly positively correlated with pathological grade (r = 0.476, p = 0.003) and Ki-67 (r = 0.419, p = 0.020). Conclusions: 3D-APTWI may be used as a supplementary method for patients with contraindications of DCE-MRI. MTRasym can imply the proliferation activities of early-stage BC. Relevance statement: 3D-APTWI can be an alternative diagnostic method for patients with early-stage BC who are not suitable for contrast injection. Key points: • 3D-APTWI reflects the changes in the microenvironment of early-stage breast cancer. • Combined 3D-APTWI is superior to DCE-MRI alone for early-stage breast cancer diagnosis. • 3D-APTWI improves the diagnostic accuracy of early-stage breast cancer. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate and analyze radiomics models based on non-contrast-enhanced computed tomography (CT) and different phases of contrast-enhanced CT in predicting Ki-67 proliferation index (PI) among patients with pathologically confirmed gastrointestinal stromal tumors (GISTs). Methods: A total of 383 patients with pathologically proven GIST were divided into a training set (n = 218, vendor 1) and 2 validation sets (n = 96, vendor 2; n = 69, vendors 3–5). Radiomics features extracted from the most recent non-contrast-enhanced and three contrast-enhanced CT scan prior to pathological examination. Random forest models were trained for each phase to predict tumors with high Ki-67 proliferation index (Ki-67>10%) and were evaluated using the area under the receiver operating characteristic curve (AUC) and other metrics on the validation sets. Results: Out of 107 radiomics features extracted from each phase of CT images, four were selected for analysis. The model trained using the non-contrast-enhanced phase achieved an AUC of 0.792 in the training set and 0.822 and 0.711 in the two validation sets, similar to models trained on different contrast-enhanced phases (p > 0.05). Several relevant features, including NGTDM Busyness and tumor size, remained predictive in non-contrast-enhanced and different contrast-enhanced images. Conclusion: The results of this study indicate that a radiomics model based on non-contrast-enhanced CT matches that of models based on different phases of contrast-enhanced CT in predicting the Ki-67 PI of GIST. GIST may exhibit similar radiological patterns irrespective of the use of contrast agent, and such radiomics features may help quantify these patterns to predict Ki-67 PI of GISTs. Clinical relevance statement: GIST may exhibit similar radiomics patterns irrespective of contrast agent; thus, radiomics models based on non-contrast-enhanced CT could be an alternative for risk stratification in GIST patients with contraindication to contrast agent. Key Points: • Performance of radiomics models in predicting Ki-67 proliferation based on different CT phases is evaluated. • Non-contrast-enhanced CT–based radiomics models performed similarly to contrast-enhanced CT in risk stratification in GIST patients. • NGTDM Busyness remains stable to contrast agents in GISTs in radiomics models. [ABSTRACT FROM AUTHOR]

Objective: To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC). Materials and methods: Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT–Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve. Results: Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT–Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT–Radiology nomogram was established based on the DECT–Radiology model, which showed the highest net benefit and satisfactory consistency. Conclusions: The DECT–Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients. Critical relevance statement: The DECT–Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression. Key points: • Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT–Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether the feeding artery (FA) feature can aid in discriminating small hepatocellular carcinoma (HCC) using the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) from precancerous lesions. Methods: Between June 2017 and May 2021, a total of 347 patients with 351 precancerous liver lesions or small HCCs who underwent CEUS were enrolled. Two independent radiologists assigned LI-RADS categories to all lesions and assessed the presence of the FA feature, which was used as an ancillary feature to either upgrade or downgrade the LI-RADS category. The diagnostic performance of CEUS LI-RADS, both with and without the FA feature, was evaluated based on accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. Results: The FA feature was found to be more prevalent in HCC (85.54%, p < 0.001) than in regenerative nodules (RNs, 29.73%), low-grade dysplastic nodules (LGDNs, 33.33%), and high-grade dysplastic nodules (HGDNs, 55.26%). Furthermore, the presence of arterial phase hyperenhancement (APHE), washout (WO), and FA in liver nodules was associated with a higher expression of GPC-3 and Ki-67 compared to the group without these features (p < 0.001). After adjusting, the sensitivity and accuracy of LR-5 for HCC improved from 68.67% (95%CI: 62.46%, 74.30%) to 77.51% (95%CI: 71.72%, 82.44%) and from 69.23% (95%CI: 64.11%, 74.02%) to 73.79% (95%CI: 68.86%, 78.31%), respectively. Conclusion: The FA feature is a valuable feature for distinguishing small HCC and precancerous lesions and could be added as a possible ancillary feature in CEUS LI-RADS which was backed up by biomarkers. Clinical relevance statement: The presence of a feeding artery is a valuable imaging feature in the differentiation of HCC and precancerous lesions. Incorporating this characteristic in the CEUS LI-RADS can enhance the diagnostic ability. Key Points: • Feeding artery is more frequent in HCC than in regenerative nodules, low-grade dysplastic nodules, and high-grade dysplastic nodules. • Feeding artery feature is a valuable ancillary feature for CEUS LI-RADS to differentiate regenerative nodules, low-grade dysplastic nodules, high-grade dysplastic nodules, and HCC. • The existence of feeding artery, arterial phase hyperenhancement, and washout is associated with more GPC-3 positive expression and higher Ki-67 expression than the group without these features. [ABSTRACT FROM AUTHOR]

The Ki-67 proliferation index (PI) guides treatment decisions in breast cancer but suffers from poor inter-rater reproducibility. Although AI tools have been designed for Ki-67 assessment, their impact on pathologists' work remains understudied. 90 international pathologists were recruited to assess the Ki-67 PI of ten breast cancer tissue microarrays with and without AI. Accuracy, agreement, and turnaround time with and without AI were compared. Pathologists' perspectives on AI were collected. Using AI led to a significant decrease in PI error (2.1% with AI vs. 5.9% without AI, p < 0.001), better inter-rater agreement (ICC: 0.70 vs. 0.92; Krippendorff's α: 0.63 vs. 0.89; Fleiss' Kappa: 0.40 vs. 0.86), and an 11.9% overall median reduction in turnaround time. Most pathologists (84%) found the AI reliable. For Ki-67 assessments, 76% of respondents believed AI enhances accuracy, 82% said it improves consistency, and 83% trust it will improve efficiency. This study highlights AI's potential to standardize Ki-67 scoring, especially between 5 and 30% PI—a range with low PI agreement. This could pave the way for a universally accepted PI score to guide treatment decisions, emphasizing the promising role of AI integration into pathologist workflows. [ABSTRACT FROM AUTHOR]

Background: The proliferation marker Ki-67 is a major pathological feature for the description of the state of disease in breast cancer. It helps to define the molecular subtype and to stratify between therapy regimens in early breast cancer and helps to assess the therapy response. Circulating tumor cells (CTCs) are a negative prognostic biomarker for progression free (PFS) and overall survival (OS) in patients with metastatic breast cancer. Therefore, the CTC count is often described as surrogate for the tumor burden. Both, decrease of Ki-67 and CTC count are considered as evidence for therapy response. The presented work analyzed the correlation between the Ki-67 indices of metastatic tissue biopsies and CTC counts in biopsy time-adjacent peripheral blood samples. Patients and methods: Blood samples from 70 metastatic breast cancer patients were obtained before the start of a new line of systemic therapy. CTCs were enumerated using CellSearch® (Menarini Silicon Biosystems, Bologna, Italy) whereas intact CTCs (iCTCs) and non-intact or apoptotic CTCs (aCTCs) were distinguished using morphologic criteria. The proportion of cells expressing Ki-67 was evaluated using immunohistochemistry on biopsies of metastases obtained concurrently with CTC sampling before the start of a new line of systemic therapy. Results: 65.7% of patients had a Ki-67 index of > 25%. 28.6% of patients had ≥ 5, 47.1% ≥ 1 iCTCs. 37.1% had ≥ 5, 51.4% ≥ 1 aCTCs. No correlation was shown between Ki-67 index and iCTC and aCTC count (r = 0.05 resp. r = 0.05, Spearman's correlation index). High CTC-counts did not coincide with high Ki-67 index. High Ki-67, ≥ 5 iCTCs and aCTCs are associated with poor progression free (PFS) and overall survival (OS). Conclusion: CTCs and Ki-67 are independent prognostic markers in metastatic breast cancer. High Ki-67 in metastatic tumor tissue is not correlated to high iCTC or aCTC counts in peripheral blood. [ABSTRACT FROM AUTHOR]

Background: Clinical utility of Ki-67 immunohistochemistry (IHC) in breast cancer (BC) is mainly limited to decide for the use of chemotherapy and estimate prognosis in patients with either Ki-67 index < 5% or > 30%; however, lacunae still exists pertaining to its analytical validity. Neutrophilia is common in cancer with accompanying lymphocytopenia. Neutrophil to lymphocyte ratio (NLR) captures the intricate balance between pro-tumor neutrophilia and anti-tumor lymphocyte immunity. This study aimed to correlate cellular proliferation in breast cancer with NLR. Methods: An observational study was carried out including 73 cases of BC; pre-treatment NLR and Ki-67 grading were performed. NLR < 3 was considered low, while ≥ 3 was high. The Ki-67 expression was graded as low ≤ 5%, intermediate 6–29%, or high ≥ 30%. Various clinico-pathological variables were studied, and the association of categorical variables was analyzed using Pearson's chi-square test, and a p-value of < 0.05 was taken as significant. Results: Ki-67 correlated significantly with modified Scarff-Bloom-Richardson (SBR) grade (p < 0.01), and tumor-node-metastasis (TNM) stage (p < 0.001). Correlation of NLR was not significant with SBR grade (p > 0.05) and molecular subtype (p > 0.05); however, NLR was found to be significantly correlated with TNM stage (p < 0.001) and Ki-67 (p < 0.001). Conclusion: NLR is fast emerging as a personalized theranostic marker in breast cancer. Instead of determining a generalized cut-off value, individual baseline NLR and its dynamics with disease progression will help manage patients better, obviating some of the drawbacks associated with Ki-67. [ABSTRACT FROM AUTHOR]

To investigate the value of using VASARI signs preoperatively to assess Ki-67 proliferation index levels in patients with IDH-wildtype glioblastoma (GB). Pathological and imaging data of 154 patients with GB confirmed by surgical pathology were retrospectively analysed, and the level of Ki-67 proliferative index was assessed in tumour tissue samples from patients using immunohistochemistry (IHC) staining. Patients were divided into a high and low Ki-67 proliferation index expression group. Two radiologists analysed MRI images of patients with IDH-wildtype GB using the VASARI features system. VASARI parameters between the two groups were statistically analysed to identify characteristic parameters with significant differences and their predictive performance was determined using ROC curves. Among the obtained clinical and VASARI features of IDH-wildtype GB patients, the distribution of Maximum diameter, Proportion of necrosis and Hemorrhage was significantly different between the two groups (all p < 0.05). Multivariate logistic regression analysis showed that Maximum diameter and Hemorrhage were independent risk factors distinguishing the group with high and low expression of Ki-67 proliferative index. ROC curve analysis showed that the logistic regression model achieved an AUC value of 0.730 (95% CI: 0.639, 0.822), sensitivity of 0.628 and specificity of 0.756. Logistic regression modelling of preoperative VASARI features can be used as a reliable tool for predicting the level of Ki-67 proliferative index in IDH-wildtype GB patients, which can help in preoperative development of treatment and follow-up strategies for patients. [ABSTRACT FROM AUTHOR]

To validate a radiomics model based on multi-sequence magnetic resonance imaging (MRI) in predicting the ki-67 expression levels in early-stage endometrial cancer, 131 patients with early endometrial cancer who had undergone pathological examination and preoperative MRI scan were retrospectively enrolled and divided into two groups based on the ki-67 expression levels. The radiomics features were extracted from the T2 weighted imaging (T2WI), dynamic contrast enhanced T1 weighted imaging (DCE-T1WI), and apparent diffusion coefficient (ADC) map and screened using the Pearson correlation coefficients (PCC). A multi-layer perceptual machine and fivefold cross-validation were used to construct the radiomics model. The receiver operating characteristic (ROC) curves analysis, calibration curves, and decision curve analysis (DCA) were used to assess the models. The combined multi-sequence radiomics model of T2WI, DCE-T1WI, and ADC map showed better discriminatory powers than those using only one sequence. The combined radiomics models with multi-sequence fusions achieved the highest area under the ROC curve (AUC). The AUC value of the validation set was 0.852, with an accuracy of 0.827, sensitivity of 0.844, specificity of 0.773, and precision of 0.799. In conclusion, the combined multi-sequence MRI based radiomics model enables preoperative noninvasive prediction of the ki-67 expression levels in early endometrial cancer. This provides an objective imaging basis for clinical diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Background: Intrahepatic cholangiocarcinoma (iCCA) is an aggressive primary liver cancer with dismal outcome, high Ki-67 expression is associated with active progression and poor prognosis of iCCA, the application of MRE in the prediction of iCCA Ki-67 expression has not yet been investigated until now. We aimed to evaluate the value of magnetic resonance elastography (MRE) in assessing Ki-67 expression for iCCA. Results: In the whole cohort, 97 patients (57 high Ki-67 and 40 low Ki-67; 58 males, 39 females; mean age, 58.89 years, ranges 36–70 years) were included. At the multivariate analysis, tumor stiffness (odds ratio (OR) = 1.669 [95% CI: 1.307–2.131], p < 0.001) and tumor apparent diffusion coefficient (ADC) (OR = 0.030 [95% CI: 0.002, 0.476], p = 0.013) were independent significant variables associated with Ki-67. Areas under the curve of tumor stiffness for the identification of high Ki-67 were 0.796 (95% CI 0.702, 0.871). Tumor stiffness was moderately correlated with Ki-67 level (r = 0.593, p < 0.001). When both predictive variables of tumor stiffness and ADC were integrated, the best performance was achieved with area under the curve values of 0.864 (95% CI 0.780–0.926). Conclusion: MRE-based tumor stiffness correlated with Ki-67 in iCCA and could be investigated as a potential prognostic biomarker. The combined model incorporating both tumor stiffness and ADC increased the predictive performance. Critical relevance statement: MRE-based tumor stiffness might be a surrogate imaging biomarker to predict Ki-67 expression in intrahepatic cholangiocarcinoma patients, reflecting tumor cellular proliferation. The combined model incorporating both tumor stiffness and apparent diffusion coefficient increased the predictive performance. Key points: • MRE-based tumor stiffness shows a significant correlation with Ki-67. • The combined model incorporating tumor stiffness and apparent diffusion coefficient demonstrated an optimized predictive performance for Ki-67 expression. • MRE-based tumor stiffness could be investigated as a potential prognostic biomarker for intrahepatic cholangiocarcinoma. [ABSTRACT FROM AUTHOR]

Purpose: The sensitivity of [18F] fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) for detecting hepatocellular carcinoma (HCC) has not been clarified thoroughly. Our study seeks to explore the association between the Ki-67 index and FDG-avidity in HCC tumors using 18F-FDG PET/CT. Methods: 112 HCC lesions from 109 patients detected by 18F-FDG PET/CT were included retrospectively between August 2017 and May 2022, comprising 82 lesions in the training cohort and 30 in the validation cohort to simulate prospective studies. In the training cohort, lesions were stratified by a lesion-to-liver maximum standardized uptake value (SUVmax) ratio cut-off of 1.59. The relationships between lesion-to-liver SUVmax ratios and several clinical factors including tumor differentiation, alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), hepatitis B virus (HBV) infection, Ki-67 index et al. were assessed. These findings were subsequently validated in the independent validation cohort. Results: In the training cohort, group A1 lesions demonstrated a higher Ki-67 index (%, 40.00 [30.00, 57.50] vs. 10.00 [5.00, 28.75], p<0.001) than group A0, the positive correlation between FDG-avidity and Ki-67 index was revealed by multivariate analysis, OR=1.040, 95% CI of OR [1.004–1.077], p=0.030. The calculated cut-off value was 17.5% using the receiver operating characteristic (ROC) curve, with an area under curve (AUC) of 0.834 and 95% CI [0.742–0.926], p<0.001. These findings were further validated in the independent validation cohort, with similar results (AUC=0.875, 95% CI [0.750–1.000], p<0.001). Conclusion: In comparison to tumor differentiation, Ki-67 index demonstrates a stronger association with FDG-avidity in HCC tumors, and when the Ki-67 index exceeds 17.5%, 18F-FDG PET/CT might serve as a useful indicator for HCC. [ABSTRACT FROM AUTHOR]

Objective: To study the value of radiomics models based on plain and multiphase contrast-enhanced CT to predict Ki-67 expression in gastrointestinal stromal tumors (GISTs). Methods: A total of 215 patients with GISTs were retrospectively analyzed, including 150 patients in one hospital as the training set and 65 patients in another hospital as the external verification set. The tumor at the largest level of CT images was delineated as the region of interest (ROI). The maximum diameter of the ROI was defined as the tumor size. A total of 851 radiomics features were extracted from each ROI by 3D Slicer Radiomics. After dimensionality reduction, three machine learning classification algorithms including logistic regression (LR), random forest (RF), and support vector machine (SVM) were used for Ki-67 expression prediction. Using a multivariable logistic model, a nomogram was established to predict the expression of Ki-67 individually. Results: Delong tests showed that the SVM models had the highest accuracy in the arterial phase (Z value 0.217–1.139) and venous phase (Z value 0.022–1.396). For the plain phase, LR and SVM models had the highest accuracy (Z value 0.874–1.824, 1.139–1.763). For the delayed phase, LR models had the highest accuracy (Z value 0.056–1.824). For the combined phase, RF models had the highest accuracy (Z value 0.232–1.978). There was no significant difference among the above models for KI-67 expression prediction (Z value 0.022–1.978). A nomogram was developed with a C-index of 0.913 (95% CI, 0.878 to 0.956). Conclusions: Radiomics of both plain and enhanced CT images could accurately predict the expression of Ki-67 in GIST. For patients who were not suitable to use contrast agents, plain scan could be used as an alternative. Clinical relevance statement: CT radiomics could accurately predict the expression of Ki-67 in GIST, which has a great clinical value in reflecting the proliferative activity of tumor cells and helping determine whether a patient is suitable for adjuvant therapy with imatinib. Key Points: • Radiomics of both plain and enhanced CT images could accurately predict the expression of Ki-67 in GIST. • For patients who were not suitable to use contrast agents, plain scan could be used as an alternative. • A radiomics nomogram was developed to allow personalized preoperative evaluation with high accuracy. [ABSTRACT FROM AUTHOR]

Integrating carrier drug therapy with recent advances in liver tissue regeneration, this paper proposes a novel nanomedicine-based approach to drug delivery, with the aim of enhancing the regenerative capacity of hepatocytes and improving liver function after partial hepatectomy. The proposed decellularized liver matrix provides excellent biocompatibility and similarity to natural liver components, while the molecules encapsulated in the carrier (tannic acid) promote liver regeneration. In in vitro cultures, the 0.001 mg/mL TA-mPEG-DLM group consistently outperformed the blank group in terms of albumin synthesis: Day 1 (11.1 ± 2.4 vs. 8.2 ± 0.7), Day 3 (5.8 ± 1.3 vs. 4.2 ± 0.4), and Day 5 (1.6 ± 0.3 vs. 1.2 ± 0.2) (μg/100% proliferation rate/well/day). In a liver-injured in vivo model, the 0.5 mg/mL TA-mPEG-DLM group outperformed the blank group in terms of relative liver weight: Day 3 (3.50 ± 0.09% vs. 3.22 ± 0.03%) and Day 7 (4.13 ± 0.21% vs. 3.72 ± 0.06%). Furthermore, the TA-mPEG-DLM group outperformed the blank group in terms of Ki-67 expression in hepatocytes on Day 7 (192.7 ± 34.1% vs. 150.4 ± 11.6%). Taken together, these findings indicate that the proposed drug delivery strategy is a promising approach to liver regeneration following partial hepatectomy with potential for clinical translation. [ABSTRACT FROM AUTHOR]

Objective: Noninvasive detection of molecular status of astrocytoma is of great clinical significance for predicting therapeutic response and prognosis. We aimed to evaluate whether morphological MRI (mMRI), SWI, DWI, and DSC-PWI could predict Ki-67 labeling index (LI), ATRX mutation, and MGMT promoter methylation status in IDH mutant (IDH-mut) astrocytoma. Methods: We retrospectively analyzed mMRI, SWI, DWI, and DSC-PWI in 136 patients with IDH-mut astrocytoma.The features of mMRI and intratumoral susceptibility signals (ITSS) were compared using Fisher exact test or chi-square tests. Wilcoxon rank sum test was used to compare the minimum ADC (ADCmin), and minimum relative ADC (rADCmin) of IDH-mut astrocytoma in different molecular markers status. Mann–Whitney U test was used to compare the rCBVmax of IDH-mut astrocytoma with different molecular markers status. Receiver operating characteristic curves was performed to evaluate their diagnostic performances. Results: ITSS, ADCmin, rADCmin, and rCBVmax were significantly different between high and low Ki-67 LI groups. ITSS, ADCmin, and rADCmin were significantly different between ATRX mutant and wild-type groups. Necrosis, edema, enhancement, and margin pattern were significantly different between low and high Ki-67 LI groups. Peritumoral edema was significantly different between ATRX mutant and wild-type groups. Grade 3 IDH-mut astrocytoma with unmethylated MGMT promoter was more likely to show enhancement compared to the methylated group. Conclusions: mMRI, SWI, DWI, and DSC-PWI were shown to have the potential to predict Ki-67 LI and ATRX mutation status in IDH-mut astrocytoma. A combination of mMRI and SWI may improve diagnostic performance for predicting Ki-67 LI and ATRX mutation status. Clinical relevance statement: Conventional MRI and functional MRI (SWI, DWI, and DSC-PWI) can predict Ki-67 expression and ATRX mutation status of IDH mutant astrocytoma, which may help clinicians determine personalized treatment plans and predict patient outcomes. Key Points: • A combination of multimodal MRI may improve the diagnostic performance to predict Ki-67 LI and ATRX mutation status. • Compared with IDH-mutant astrocytoma with low Ki-67 LI, IDH-mutant astrocytoma with high Ki-67 LI was more likely to show necrosis, edema, enhancement, poorly defined margin, higher ITSS levels, lower ADC, and higher rCBV. • ATRX wild-type IDH-mutant astrocytoma was more likely to show edema, higher ITSS levels, and lower ADC compared to ATRX mutant IDH-mutant astrocytoma. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to evaluate whether sleep deprivation can induce degenerative changes in rat sublingual glands. Methods: For this purpose, a total of 24 males were distributed into three groups: control (n = 8), in which the animals were not subjected to any procedure; sleep deprivation (n = 8) in which the animals were submitted to sleep deprivation for 96 h; recovery (n = 8), in which the animals were subjected to paradoxical sleep deprivation for 96 consecutive hours followed by 96 h without intervention. Morphological changes in sublingual glands as well as the immunoexpressions of some proteins, such as Ki-67, p16, cleaved caspase-3 and BCL-2 were investigated in this setting. Results: The results showed that paradoxical sleep deprivation induced tissue degeneration as a result of the presence of pyknosis, vacuoles and areas of salivary retention, in the experimental groups. Expression of cleaved caspase 3 and BCL-2 were increased in both sleep deprivation and recovery groups. The analysis of Ki-67 showed an increase in expression only in the recovery group, associated with a decrease in p16 levels. Conclusion: Sleep deprivation can induce a degenerative process in the parenchyma of sublingual gland by means of dysregulation of apoptosis associated with proliferative activity. [ABSTRACT FROM AUTHOR]

This study aims to investigate the predictive value of preoperative whole-tumor histogram analysis of multi-parametric MRI for histological subtypes in patients with lung cancer brain metastases (BMs) and explore the correlation between histogram parameters and Ki-67 proliferation index. The preoperative MRI data of 95 lung cancer BM lesions obtained from 73 patients (42 men and 31 women) were retrospectively analyzed. Multi-parametric MRI histogram was used to distinguish small-cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC), and adenocarcinoma (AC) from squamous cell carcinoma (SCC), respectively. The T1-weighted contrast-enhanced (T1C) and apparent diffusion coefficient (ADC) histogram parameters of the volumes of interest (VOIs) in all BMs lesions were extracted using FireVoxel software. The following histogram parameters were obtained: maximum, minimum, mean, standard deviation (SD), variance, coefficient of variation (CV), skewness, kurtosis, entropy, and 1st–99th percentiles. Then investigated their relationship with the Ki-67 proliferation index. The skewness-T1C, kurtosis-T1C, minimum-ADC, mean-ADC, CV-ADC and 1st – 90th ADC percentiles were significantly different between the SCLC and NSCLC groups (all p < 0.05). When the 10th-ADC percentile was 668, the sensitivity, specificity, and accuracy (90.80%, 76.70% and 86.32%, respectively) for distinguishing SCLC from NSCLC reached their maximum values, with an AUC of 0.895 (0.824 – 0.966). Mean-T1C, CV-T1C, skewness-T1C, 1st – 50th T1C percentiles, maximum-ADC, SD-ADC, variance-ADC and 75th – 99th ADC percentiles were significantly different between the AC and SCC groups (all p < 0.05). When the CV-T1C percentiles was 3.13, the sensitivity, specificity and accuracy (75.00%, 75.60% and 75.38%, respectively) for distinguishing AC and SCC reached their maximum values, with an AUC of 0.829 (0.728–0.929). The 5th-ADC and 10th-ADC percentiles were strongly correlated with the Ki-67 proliferation index in BMs. Multi-parametric MRI histogram parameters can be used to identify the histological subtypes of lung cancer BMs and predict the Ki-67 proliferation index. [ABSTRACT FROM AUTHOR]

Purpose: To develop a radiomics nomogram based on dual-phase enhanced computed tomography (CT) for predicting the Ki-67 index status in patients with advanced non-small cell lung cancer (NSCLC). Methods: 137 patients with NSCLC who had undergone dual-phase enhanced CT scans and Ki-67 examination within 2 weeks were retrospectively enrolled between January 2020 and December 2022. Clinical and laboratory data were collected, and the patients were categorized based on low or high expression of Ki-67 index, with a cut-off value of 40%. The cohort was randomly divided into a training group (n = 95) and a testing group (n = 42) at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) algorithm was employed to select the most valuable radiomics features from the dual-phase enhanced CT images. Subsequently, a nomogram that incorporated the radiomics score and clinical factors associated with Ki-67 index status was established through univariate and multivariate logistic regression analyses. The predictive performance of the nomogram was evaluated using the area under the curve (AUC). Results: The AUC values of the radiomics features of artery phase and vein phase CT in the testing group were 0.748 and 0.758, respectively. The AUC of the dual-phase enhanced CT was 0.785, and the AUC of the developed nomogram was 0.859, which was higher than those of the radiomics (AUC, 0.785) and clinical models (AUC, 0.736). Conclusions: The radiomics nomogram based on dual-phase enhanced CT images provides a promising method for predicting the Ki-67 index status in patients with advanced NSCLC. [ABSTRACT FROM AUTHOR]

Objectives: To explore the correlations between histopathologic findings and intravoxel incoherent motion (IVIM)–derived perfusion and diffusion parameters in brain gliomas. Methods: Thirty-two biopsy samples from twenty-one patients with newly diagnosed gliomas from a previous prospective cohort study were retrospectively analyzed. All patients underwent diffusion-weighted MRI with 22 b values (0–5000 s/mm2), followed by intraoperative MR-guided biopsy surgery and surgical resection. All 32 biopsy samples underwent immunohistochemical staining followed by quantitative analysis of cell density (cellularity), percent of MIB-1 (Ki67)-positive expression (pMIB-1), number of CD34-stained vessels (CD34-MVD), and percent of VEGF-positive expressing cells (pVEGF) using a multispectral phenotyping microscope. Based on the co-registered localized biopsy, correlation analysis was performed between the IVIM-derived biexponential model–based parameters (Dfast1500 and Dfast5000, Dslow1500 and Dslow5000, PF1500 and PF5000) and the above four pathological biomarkers and glioma grades. Results: Significant positive correlations were revealed between Dfast5000 and pVEGF (rho (r) = 0.466, p = 0.007), and Dfast1500 and pVEGF (r = 0.371, p = 0.037). A significant negative correlation was revealed between PF5000 with pMIB-1 (r = − 0.456, p = 0.01). Moderate to good positive correlations were shown between Dfast5000 and glioma grades (r = 0.509, p = 0.003) and Dfast1500 and glioma grades (r = 0.476, p = 0.006). Conclusions: IVIM-DWI-derived Dfast and PF correlate, respectively, with intratumor pVEGF and pMIB-1. When using the wide-high b value scheme, IVIM-derived Dfast and PF tend to demonstrate better efficacy in evaluating malignancy-related characteristics such as angiogenesis and cellular proliferation in gliomas. Key Points: • Intravoxel incoherent motion-diffusion-weighted imaging (IVIM-DWI)–derived fast diffusion (Dfast) and perfusion fraction (PF) can quantitatively reflect intratumor pVEGF and pMIB-1. • IVIM-DWI-derived Dfast and PF tend to demonstrate better efficacy in evaluating glioma malignancy when an optimized scheme is used. • IVIM-DWI-derived Dfast5000 and PF5000 are promising non-invasive parameters correlating with pVEGF and pMIB-1 in gliomas. [ABSTRACT FROM AUTHOR]

Background: For non-functioning pancreatic neuroendocrine tumors (pNETs) ≤ 20 mm, most guidelines consider follow-up observations as an option; however, the various treatment strategies are defined by size alone, even though the Ki-67 index is important for malignancy grading. Endoscopic ultrasound-guided tissue acquisition (EUS-TA) is the standard for the histopathological diagnosis of solid pancreatic lesions; however, recent results for small lesions remain unclear. Therefore, we examined the efficacy of EUS-TA for solid pancreatic lesions ≤ 20 mm suspected as pNETs or requiring differentiation and the non-increase rate in tumor size in follow-up cases. Methods: We retrospectively analyzed data of 111 patients (median age = 58 years) with lesions ≤ 20 mm suspected as pNETs or requiring differentiation who underwent EUS-TA. All patients underwent specimen evaluation by rapid onsite evaluation (ROSE). Results: EUS-TA led to a diagnosis of pNETs in 77 patients (69.4%) and tumors other than pNETs in 22 patients (19.8%). The histopathological diagnostic accuracy of EUS-TA was 89.2% (99/111) overall, 94.3% (50/53) for 10–20 mm lesions, and 84.5% (49/58) for ≤ 10 mm lesions, with no significant difference in diagnostic accuracy (p = 0.13). The Ki-67 index was measurable in all patients with a histopathological diagnosis of pNETs. Among 49 patients with a diagnosis of pNETs who were followed up, one patient (2.0%) showed tumor enlargement. Conclusions: EUS-TA for solid pancreatic lesions ≤ 20 mm suspected as pNETs or requiring differentiation is safe and has adequate histopathological diagnostic accuracy, suggesting that follow-up observations of pNETs with a histological pathologic diagnosis are acceptable in the short term. [ABSTRACT FROM AUTHOR]

Objectives: To compare the histogram features of multiple diffusion metrics in predicting the grade and cellular proliferation of meningiomas. Methods: Diffusion spectrum imaging was performed in 122 meningiomas (30 males, 13–84 years), which were divided into 31 high-grade meningiomas (HGMs, grades 2 and 3) and 91 low-grade meningiomas (LGMs, grade 1). The histogram features of multiple diffusion metrics obtained from diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) in the solid tumours were analysed. All values between the two groups were compared with the Man-Whitney U test. Logistic regression analysis was applied to predict meningioma grade. The correlation between diffusion metrics and Ki-67 index was analysed. Results: The DKI_AK (axial kurtosis) maximum, DKI_AK range, MAP_RTPP (return-to-plane probability) maximum, MAP_RTPP range, NODDI_ICVF (intracellular volume fraction) range, and NODDI_ICVF maximum values were lower (p < 0.0001), whilst the DTI_MD (mean diffusivity) minimum values were higher in LGMs than those in HGMs (p < 0.001). Amongst the DTI, DKI, MAP, NODDI, and combined diffusion models, no significant differences were found in areas under the receiver operating characteristic curves (AUCs) for grading meningiomas (AUCs, 0.75, 0.75, 0.80, 0.79, and 0.86, respectively; all corrected p > 0.05, Bonferroni correction). Significant but weak positive correlations were found between the Ki-67 index and DKI, MAP, and NODDI metrics (r = 0.26–0.34, all p < 0.05). Conclusions: Whole tumour histogram analyses of the multiple diffusion metrics from four diffusion models are promising methods in grading meningiomas. The DTI model has similar diagnostic performance compared with advanced diffusion models. Key Points: • Whole tumour histogram analyses of multiple diffusion models are feasible for grading meningiomas. • The DKI, MAP, and NODDI metrics are weakly associated with the Ki-67 proliferation status. • DTI has similar diagnostic performance compared with DKI, MAP, and NODDI in grading meningiomas. [ABSTRACT FROM AUTHOR]

Myxoid liposarcoma (MLS) is a common subtype of liposarcoma. Although the prognosis is generally good, there are factors known to be associated with poor prognosis. Accurate indices are important to predict prognosis. We aimed to assess the usefulness of immunohistochemistry for phosphohistone H3 (PHH3) as a potential biomarker in comparison with Ki-67 antigen and other prognostic factors. Twenty-five patients with MLS were evaluated. Age, sex, depth of tumor, tumor size, surgical margin, oncological outcome, histological grade, presence of necrosis, proportion of round cell component (RC%), PHH3 index, and Ki-67 index were examined. Prognostic factors of the examination criteria were statistically analyzed, survival rate analyses were performed using the Kaplan–Meier method, and multivariate analysis was performed using Cox proportional-hazard regression analysis. The number of PHH3-positive tumor cells and the PHH3 and Ki-67 indices demonstrated a statistical correlation with the prognosis of MLS in univariate analysis (P < 0.001, P < 0.001, P = 0.01, respectively). PHH3 index and RC% were significant factors in multivariate analysis (P = 0.03, P = 0.02). The immunohistochemistry of PHH3 may be associated with prognosis and could serve as a valid criterion of histological grade in MLS. [ABSTRACT FROM AUTHOR]

This study aimed to optimize slope and energy levels for evaluating Ki-67 expression in lung cancer using virtual monoenergetic imaging and compare the predictive efficiency of different energy spectrum slopes (λHU) for Ki-67. Forty-three patients with primary lung cancer confirmed via pathological examination were enrolled in this study. They underwent baseline arterial-phase (AP) and venous-phase (VP) energy spectrum computed tomography (CT) scanning before surgery. The CT values were 40–190 keV, with 40–140 keV indicating pulmonary lesions at AP and VP, and P < 0.05 indicating a statistically significant difference. An immunohistochemical examination was conducted, and receiver operating characteristic curves were used to analyze the prediction performance of λHU for Ki-67 expression. SPSS Statistics 22.0 (IBM Corp., NY, USA) was used for statistical analysis, and χ2, t, and Mann–Whitney U tests were used for quantitative and qualitative analyses of data. Significant differences were observed at the corresponding CT values of 40 keV (as 40-keV is considered the best for single-energy image for evaluating Ki-67 expression) and 50 keV in AP and at 40, 60, and 70 keV in VP between high- and low-Ki-67 expression groups (P < 0.05). In addition, the λHU values of three-segment energy spectrum curve in both AP and VP were quite different between two groups (P < 0.05). However, the VP data had greater predictive values for Ki-67. The areas under the curve were 0.859, 0.856, and 0.859, respectively. The 40-keV single-energy sequence was the best single-energy sequence to evaluate the expression of Ki-67 in lung cancer and to obtain λHU values using the energy spectrum curve in the VP. The CT values had better diagnostic efficiency. [ABSTRACT FROM AUTHOR]

Several limitations of [18F]FDG have been reported, such as nonspecific uptake of inflammation foci. Moreover, [11C]MET has been found to accumulate in normal and inflammatory tissues as well as tumors. To increase specificity to tumor tissues, PET probes with tumor-specific molecular targets have been actively developed. [18F]FIMP was found to be highly accumulated in LAT1-positive tumors but not in inflamed tissue. The aim of this study was to explore whether [18F]FIMP can be used for the early-phase evaluation of radiotherapy accompanied by inflammation, and compare its effectiveness with those of [11C]MET and [18F]FDG. Tumor uptake of [18F]FIMP decreased at day 1 after irradiation, and remained low until day 14. Comparatively, that of [18F]FDG initially decreased at day 3 but was transiently elevated at day 7 and then decreased again at day 10. Decreased tumor uptake of [11C]MET was observed at day 10. In line with the uptake of [18F]FIMP, the ratio of Ki-67 immuno-positive cells in tumor tissues significantly decreased at day 1, 7, and 10 as compared with that in the control. These findings suggest that [18F]FIMP may be a PET probe involved in the early detection and prediction of radiotherapy efficacy, although further clarification is needed. [ABSTRACT FROM AUTHOR]

Objective: Primary intracranial tumors are rare tumors in infants. They differ from those found in other pediatric age groups in terms of clinical presentation, histopathological diagnosis, adjuvant therapies, and outcome. Ki-67 index has also shown promising results as a prognostic factor in different types of intracranial tumors in children and adults. However, the importance and the best cutoff point of Ki-67 index in primary intracranial tumors of infants remains unclear. We aimed to analyze prognostic value of Ki-67 index in primary intracranial tumors of infants. Methods: This study retrospectively reviewed the records of 28 infants undergoing surgical resection for primary intracranial tumors between April 2016 and March 2021. We analyzed clinical characteristics, tumor location, extent of resection, histopathological diagnosis, Ki-67 index, and overall survival (OS). To define the most relevant cutoff value for Ki-67 index, "Cutoff Finder" was used. Results: The median age at diagnosis was 188 days for all patients. Fifteen of the patients were boys and 13 were girls. Tumors were located supratentorial in 13 patients and infratentorial in 15 patients. Gross total resection was performed in 7 of 13 supratentorial tumors and 9 of 15 infratentorial tumors. The mean Ki-67 index of the supratentorial tumors was 49.6%, the median was 55%; for infratentorial tumors, the mean was 49.9%, and the median was 70%. Tumor grade (p = 0.019) and Ki-67 index (p = 0.003) were found as significant predictors of OS in log-rank testing for Kaplan–Meier survival analysis. Univariate cox regression analysis identified high Ki-67 index as prognostic factor for worse OS, with hazard ratio of 8.852 (95% CI 1.95–64.80; p = 0.0108). High Ki-67 index was found as independent prognostic factor for worse OS in multivariate cox regression analysis (HR 7.036; 95% CI 1.229–65.82; p = 0.0457). Conclusion: High-grade and high Ki-67 index were associated with worse outcome. Ki-67 index did show a distinct prognostic value for OS within our cohort at a cutoff value of 72.5%. [ABSTRACT FROM AUTHOR]

The clinical significance of thyroglobulin (Tg) expression in papillary thyroid cancer (PTC) has not been systematically explored in relation to the Ki-67 index, lymph node ratio (LNR), or other conventional prognostic predictors. In this retrospective study of 327 patients with PTC, we investigated the immunohistochemical expression of Tg in both primary tumors and their matching lymph node metastases in relation to the Ki-67 index, LNR, and clinical data. Tumoral Tg immunoreactivity was inversely correlated to the Ki-67 index and tumor recurrence. The Ki-67 index was higher in lymph node metastases (mean 4%) than in the primary tumors (mean 3%). Reduced Tg expression, estimated as 0–25% Tg positive tumor cells, was more common in lymph node metastases compared to primary tumors. In addition to advanced metastatic burden (defined as N1b stage and LNR ≥ 21%), low Tg expression (0–25% positive tumor cells) in lymph node metastases had a significant prognostic impact with shorter recurrence-free survival. These findings support the potential value of histopathological assessment of Tg expression and Ki-67 index in lymph node metastases as complementary predictors to anticipate the prognosis of PTC patients better. [ABSTRACT FROM AUTHOR]

Objective: To investigate the value of histogram analysis of T1 mapping and diffusion-weighted imaging (DWI) in predicting the grade, subtype, and proliferative activity of meningioma. Methods: This prospective study comprised 69 meningioma patients who underwent preoperative MRI including T1 mapping and DWI. The histogram metrics, including mean, median, maximum, minimum, 10th percentiles (C10), 90th percentiles (C90), kurtosis, skewness, and variance, of T1 and apparent diffusion coefficient (ADC) values were extracted from the whole tumour and peritumoural oedema using FeAture Explorer. The Mann-Whitney U test was used for comparison between low- and high-grade tumours. Receiver operating characteristic (ROC) curve and logistic regression analyses were performed to identify the differential diagnostic performance. The Kruskal-Wallis test was used to further classify meningioma subtypes. Spearman's rank correlation coefficients were calculated to analyse the correlations between histogram parameters and Ki-67 expression. Results: High-grade meningiomas showed significantly higher mean, maximum, C90, and variance of T1 (p = 0.001–0.009), lower minimum, and C10 of ADC (p = 0.013–0.028), compared to low-grade meningiomas. For all histogram parameters, the highest individual distinctive power was T1 C90 with an AUC of 0.805. The best diagnostic accuracy was obtained by combining the T1 C90 and ADC C10 with an AUC of 0.864. The histogram parameters differentiated 4/6 pairs of subtype pairs. Significant correlations were identified between Ki-67 and histogram parameters of T1 (C90, mean) and ADC (C10, kurtosis, variance). Conclusion: T1 and ADC histogram parameters may represent an in vivo biomarker for predicting the grade, subtype, and proliferative activity of meningioma. Key Points: • The histogram parameter based on T1 mapping and DWI is useful to preoperatively evaluate the grade, subtype, and proliferative activity of meningioma. • The combination of T1 C90 and ADC C10 showed the best performance for differentiating low- and high-grade meningiomas. [ABSTRACT FROM AUTHOR]

Background: Ki-67 is widely used as a proliferative and prognostic factor in HCC. This study aimed to analyze the relationship between dynamic contrast-enhanced ultrasonography (DCE-US) parameters and Ki-67 expression. Methods: One hundred and twenty patients with histopathologically confirmed HCC who underwent DCE-US were included in this prospective study. Patients were classified according to the Ki-67 marker index into low Ki-67 (< 10%) (n = 84) and high Ki-67 (≥ 10%) groups (n = 36). Quantitative perfusion parameters were obtained and analyzed. Results: Clinicopathological features (pathological grade and microvascular invasion) were significantly different between the high and low Ki-67 expression groups (p = 0.029 and p = 0.020, respectively). In the high Ki-67 expression group, the peak energy (PE) in the arterial phase and fall time (FT) were significantly different between the HCC lesions and distal liver parenchyma (p = 0.016 and p = 0.025, respectively). PE in the Kupffer phase was significantly different between the HCC lesions and the distal liver parenchyma in the low Ki-67 expression group (p = 0.029). The difference in PE in the Kupffer phase between HCC lesions and distal liver parenchyma was significantly different between the high and low Ki-67 expression groups (p = 0.045). The difference in PE in the Kupffer phase between HCC lesions and distal liver parenchyma < − 4.0 × 107 a.u. may contribute to a more accurate diagnosis of the high Ki-67 expression group, and the sensitivity and specificity were 82.9% and 38.7%, respectively. Conclusions: The DCE-US parameters have potential as biomarkers for predicting Ki-67 expression in patients with HCC. [ABSTRACT FROM AUTHOR]

Atypical spindle cell/pleomorphic lipomatous tumor (ASPLT) is a new entity of benign adipocytic tumor that spans a wide spectrum of histology from adipocytic to spindle cell/pleomorphic tumors. The latter non-adipocytic component rarely shows sarcomatous features although ASPLTs are not thought to dedifferentiate. A 78-year-old woman with ASPLT in the left thigh had a sarcomatous component with high mitotic activity and Ki-67 labeling index (LI) mimicking dedifferentiated liposarcoma. The adipocytic component consisted of various-sized adipocytic cells with few lipoblasts. The sarcomatous component consisted of a fascicular proliferation of atypical spindle cells with scattered large bizarre and multinucleated giant cells. Mitotic figures including atypical mitoses were frequently observed. Immunohistochemically, the tumor cells were positive for cluster of differentiation 34 but not mouse double minute 2 homolog (MDM2), cyclin-dependent kinase 4 (CDK4), or retinoblastoma (Rb) protein. Ki-67 LI in the sarcomatous component reached 40%. MDM2 and CDK4 genes were not amplified and 13q14 including the RB1 locus was deleted according to fluorescence in situ hybridization. The patient is alive with no evidence of local recurrence or distant metastasis 3.5 years after surgery. As ASPLT may exhibit morphological variation, it is important to rule out dedifferentiated liposarcoma with careful pathological examination. [ABSTRACT FROM AUTHOR]

Actinic cheilitis (AC) and lower lip squamous cell carcinoma (LLSCC) exhibit epithelial alterations mainly associated with chronic ultraviolet ray exposure. Currently, it is impossible to predict which AC cases will progress to LLSCC; thus, biomolecular markers have been studied. The aim of this study was to evaluate the immunoexpression of IMP-3 and KI-67 in AC and LLSCC. Forty AC and 40 LLSCC cases were submitted to peroxidase method and quantitatively analyzed, using the following scores: 0 (0% positive cells), + 1(≤ 30%), + 2 (> 30% to ≤ 60%), and + 3 (> 60%). Results were submitted to non-parametric Mann–Whitney (U) test. A p value < 0.05 was considered to indicate statistical significance. IMP-3 immunoexpression was observed in 26 AC cases, with predominance of the score 1 (35% of cases). This protein was also positive in 22 LLSCC cases, with predominance of the score 3 (37.5% of cases). Immunoexpression of KI-67 was observed in all studied cases, with predominance of the score 2 (70% of AC cases and 57.5% LLSCC cases). The association between IMP-3 and Ki-67 immunoexpression, AC dysplastic severity and LLSCC tumoral grade revealed no significant differences. The present results demonstrate that IMP-3 and Ki-67 immunoexpression are frequent in AC and in LLSCC. Moreover, these proteins could be involved in lower lip carcinogenesis process. [ABSTRACT FROM AUTHOR]

Background: Oral potentially malignant lesions (OPML) are suspicious lesions that may turn into malignancy according to the degree of dysplasia. Early diagnosis of these lesions allows their treatment before malignant transformation. Saliva is a liquid biopsy that can be obtained easily from the patient and assessed for biomarkers expression. Our study aimed to investigate the possibility of using salivary and serum TNF-α and Ki-67 in early detection of OPML. Patients with OPML were selected according to histopathological evaluation of the suspected lesions. The lesions were stained immunohistochemically by tumor necrosis factor alpha (TNF-α) and Ki-67. Saliva and blood samples were collected from the patients for detecting the expression of the markers by ELISA. Results: The level of TNF-α and Ki-67 was higher in patients with OPML than healthy individuals regarding both saliva and serum. TNF-α was significantly higher in saliva than in serum unlike Ki-67 which was insignificantly higher in saliva than in serum. The OPML show negative expression of TNF-α in OPML immunohistochemically unlike Ki-67 which show intense positive expression in OPML immunohistochemically. Conclusions: Saliva can be used as an early noninvasive biomarker detector depending on selecting the appropriate salivary biomarker. Salivary TNF-α can be used in early diagnosis of OPML. [ABSTRACT FROM AUTHOR]

Objectives: To explore the correlation of parameters derived from intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) with Ki-67 labeling index (LI) in soft tissue sarcoma (STS). Methods: Forty-one patients with STS underwent IVIM and DKI imaging at 3.0 MRI. The standard apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) were compared between Ki-67 low- and high-expression groups by two independent observers. A novel method was used to ensure the topographic correlation of histologic sections and magnetic resonance imaging slices. Receiver operating characteristic (ROC), intraclass correlation coefficient (ICC), and Spearman's rank correlations were performed for statistical analysis. Results: The high-expression group displayed lower standard ADC, D, and MD values and a higher MK value than the low-expression group. No significant differences were found for D∗ and f values. The areas under the curve for standard ADC, D, MD, and MK when discriminating between low- and high-expression groups were 0.736, 0.745, 0.848, and 0.894, respectively. MK was positively correlated with Ki-67 LI (r = 0.809, p < 0.001). Standard ADC, D, and MD were negatively correlated with Ki-67 LI (r = −0.541, −0.556, −0.702, respectively, p < 0.001). Conclusions: IVIM and DKI parameters are correlated with Ki-67 LI. MK may be the optimal imaging biomarker for assessing the Ki-67 expression of STS. Key Points: • IVIM and DKI parameters are correlated with the expression of Ki-67 in STS. • The MRI-pathology control method ensured a strong correlation between MRI slices and histologic sections, resulting in a robust radiological-pathological correlation. [ABSTRACT FROM AUTHOR]

Background: The prevalence and incidence of neuroendocrine tumors (NETs) are increasing worldwide. Primary mesenteric NETs are extremely rare. Solid tumors that arise in the mesentery are typically metastatic. We present an extremely rare case of a primary grade 2 NET (NET G2) in the ileal mesentery. Case presentation: A 54-year-old man was referred to our hospital for further examination of a previously diagnosed right mesenteric tumor. Mild tenderness was noted on the right side of the abdomen, but there were no palpable masses. Fluorodeoxyglucose-positron emission tomography (FDG-PET) revealed slight FDG uptake (maximum standardized uptake value, 2.0) in the right abdomen, and a benign or low-grade malignant tumor was suspected. We extracted the ileal mesenteric tumor with an ileal resection (90 cm). The cut surface of the 55 × 33 × 33 mm3 tumor was pale yellowish-white. Immunohistochemistry revealed diffuse staining for synaptophysin and chromogranin A, and focal staining for CD56. The Ki-67 index was 3%. The final pathological diagnosis was NET G2. The patient's postoperative course was uneventful, and he developed no recurrence 1.5 years after surgery. Postoperative antitumor therapy was not performed for this patient because the histological diagnosis was NET G2, and it was determined that the tumor could be completely resected by surgery. Conclusions: We report an extremely rare case of primary ileal mesenteric NET. Mesenteric tumors that show slight FDG uptake on FDG-PET examination should be considered well-differentiated NET. [ABSTRACT FROM AUTHOR]

This study aims to explore the chemopreventive mechanisms of hydroethanolic extracts from avocado (Persea Americana) in diethylnitrosamine (DEN)/2-acetylaminofluorene (2AAF)-induced hepatocarcinogenesis. Chemical induction of hepatocarcinogenesis was induced by intraperitoneal injection of DEN at 150 mg/kg body weight (b.w.) twice a week for a fortnight, followed by oral administration of 2AAF at 20 mg/kg b.w. four times a week for 3 weeks. Rats administered DEN/2AAF were orally treated with hydroethanolic extracts of avocado fruits and seeds at a dose of 50 mg/kg b.w. every other day for 20 weeks. Moreover, rats administered DEN/2AAF and treated with avocado extracts revealed a marked decrease in liver enzyme activities, total bilirubin levels, and elevated liver tumor markers, but revealed an increase in total protein and albumin levels. The hepatocytes with hyperchromatic and bile duct cystadenoma observed in the liver of rats administered DEN/2AAF were reduced due to treatment with avocado extracts. Furthermore, the treatments prevented the elevation of lipid peroxidation levels and ameliorated the lowered glutathione peroxidase, glutathione-S-transferase, superoxide dismutase activities, and glutathione content in the liver tissues. Also, antigen Ki-67, cyclooxygenase-2, and nuclear factor kappa-B expression levels were decreased, but of the suppressor proteins p53 and BAX levels were increased in the liver of rats administered DEN/2AAF and treated with avocado extracts. In conclusion, the current results demonstrated that avocado extracts could abate hepatocarcinogenesis in rats administered DEN/2AAF through activation of antioxidant, anti-inflammatory, and apoptotic properties. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the glioma grade, Ki-67 expression, and IDH-1 mutation status using mean apparent propagator (MAP) MRI. Methods: Forty enrolled glioma patients underwent structural and diffusion MRI. The diffusion metric values including fractional anisotropy (FA), mean diffusivity (MD), mean squared displacement (MSD), q-space inverse variance (QIV), return-to-origin probability (RTOP), return-to-axis probability (RTAP), and return-to-plane probability (RTPP) in tumor parenchyma (TP) and contralateral normal-appearing white matter (NAWM) were calculated. The TP/NAWM ratios of diffusion metric values were correlated with tumor grades, Ki-67, and IDH-1 mutation statuses, and the diagnostic performance was assessed. Results: QIV were significantly higher, whereas RTAP and RTOP were significantly lower in low-grade gliomas (LGGs) than those in high-grade gliomas (HGGs); QIV and MD were significantly higher, whereas RTAP and RTOP were significantly lower in lower-grade gliomas (grade II and III) than those in grade IV gliomas (p < 0.05 for all). RTAP performed best in grading gliomas. MSD, QIV, and MD were significantly higher, whereas RTAP, RTOP, RTPP, and FA were significantly lower in the IDH-1 mutant gliomas than those in the IDH-1 wild-type ones both for all gliomas and lower-grade gliomas (p < 0.05 for all). RTAP performed best in all gliomas, while QIV performed best in lower-grade gliomas. Additionally, RTAP, RTOP, and FA correlated positively, whereas MSD, QIV, and MD correlated negatively with Ki-67 (p < 0.05 for all). Conclusions: MAP-MRI is a potent approach in evaluating the microstructural changes in gliomas with different grades, cellular proliferation, and IDH-1 mutation statuses. Key Points: • MAP-MRI, a newly developed diffusion technique, accurately reveals microstructure-related features in the complex white matter by recovering important microstructural tissue parameters. • MAP-MRI is a potent approach in evaluating the glioma grade, IDH-1 mutation status, and Ki-67 expression. • Compared with DTI, MAP-MRI seems to demonstrate higher diagnostic performance. [ABSTRACT FROM AUTHOR]

Grade 3, type 3 gastric neuroendocrine tumor (g-NET) shows specific features of clinical interest and the therapeutic management of the lesion is not yet completely standardized. We present the unusual case of a 34-year-old male patient with a diminutive (less than 0.5 cm), well-differentiated, G3, type 3g-NET with extremely high Ki-67 index (higher than 80%). The lesion was subsequently removed en bloc via endoscopic submucosal dissection. Regarding the proliferation rate, Ki-67 index values usually range from 21 to 50%, and less commonly above 55%, in G3 NET. To our knowledge, this lesion represents a small size with the highest Ki-67 index diagnosed with G3 g-NET. However, as g-NET might recur even after a long duration, we recommend a long-term follow-up, such as 10 years after complete resection in patients to evaluate the endoscopic resection approach. [ABSTRACT FROM AUTHOR]

This study evaluated the value of the apparent diffusion coefficient (ADC) in distinguishing grade II and III intracranial solitary fibrous tumors/hemangiopericytomas and explored the correlation between ADC and Ki-67. The preoperative MRIs of 37 patients treated for solitary fibrous tumor/hemangiopericytoma (grade II, n = 15 and grade III, n = 22) in our hospital from 2011 to October 2020 were retrospectively analyzed. We compared the difference between the minimum, average, maximum, and relative ADCs based on tumor grade and examined the correlation between ADC and Ki-67. Receiver operating characteristic curve analysis was used to analyze the diagnostic efficiency of the ADC. There were significant differences in the average, minimum, and relative ADCs between grade II and III patients. The optimal cutoff value for the relative ADC value to differentiate grade II and III tumors was 0.998, which yielded an area under the curve of 0.879. The Ki-67 proliferation indexes of grade II and III tumors were significantly different, and the average (r = − 0.427), minimum (r = − 0.356), and relative (r = − 0.529) ADCs were significantly negatively correlated with the Ki-67 proliferation index. ADC can be used to differentiate grade II and III intracranial solitary fibrous tumors/hemangiopericytomas. Our results can be used to formulate a personalized surgical treatment plan before surgery. [ABSTRACT FROM AUTHOR]

The proliferation index (PI) is crucial in histopathologic diagnostics, in particular tumors. It is calculated based on Ki-67 protein expression by immunohistochemistry. PI is routinely evaluated by a visual assessment of the sample by a pathologist. However, this approach is far from ideal due to its poor intra- and interobserver variability and time-consuming. These factors force the community to seek out more precise solutions. Virtual pathology as being increasingly popular in diagnostics, armed with artificial intelligence, may potentially address this issue. The proposed solution calculates the Ki-67 proliferation index by utilizing a deep learning model and fuzzy-set interpretations for hot-spots detection. The obtained region-of-interest is then used to segment relevant cells via classical methods of image processing. The index value is approximated by relating the total surface area occupied by immunopositive cells to the total surface area of relevant cells. The achieved results are compared to the manual calculation of the Ki-67 index made by a domain expert. To increase results reliability, we trained several models in a threefold manner and compared the impact of different hyper-parameters. Our best-proposed method estimates PI with 0.024 mean absolute error, which gives a significant advantage over the current state-of-the-art solution. [ABSTRACT FROM AUTHOR]

The present investigation focuses on understanding the role of photobiomodulation in enhancing tissue proliferation. Circular excision wounds of diameter 1.5 cm were created on Swiss albino mice and treated immediately with 2 J/cm2 and 10 J/cm2 single exposures of the Helium-Neon laser along with sham-irradiated controls. During different days of healing progression (day 5, day 10, and day 15), the tissue samples upon euthanization of the animals were taken for assessing collagen deposition by Picrosirius red staining and cell proliferation (day 10) by proliferating cell nuclear antigen (PCNA) and Ki67. The positive influence of red light on collagen synthesis was found to be statistically significant on day 10 (P < 0.01) and day 15 (P < 0.05) post-wounding when compared to sham irradiation, as evident from the image analysis of collagen birefringence. Furthermore, a significant rise in PCNA (P < 0.01) and Ki67 (P < 0.05) expression was also recorded in animals exposed to 2 J/cm2 when compared to sham irradiation and (P < 0.01) compared to the 10 J/cm2 treated group as evidenced by the microscopy study. The findings of the current investigation have distinctly exhibited the assenting influence of red laser light on excisional wound healing in Swiss albino mice by augmenting cell proliferation and collagen deposition. [ABSTRACT FROM AUTHOR]