Prediction of high Ki-67 proliferation index of gastrointestinal stromal tumors based on CT at non-contrast-enhanced and different contrast-enhanced phases.

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.

Ultra-high b-value DWI accurately identifies isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas.

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.

BRAF V600E mutation mediates invasive and growth features in ameloblastoma.

OBJECTIVES: Ameloblastoma (AM), a locally aggressive tumor with extensive growth capacity, causes significant damage to the jaw and affects facial appearance. Although the high prevalence of BRAF V600E mutation in AM is known, its specific impacts on patients with AM remain unclear. Thus, the present study investigated the role of BRAF V600E mutation, thereby focusing on its impact on AM invasion and growth. MATERIALS AND METHODS: Immunohistochemical analysis was used to compare BRAF V600E, MMP2, MMP9, and Ki-67 expressions in AM (n = 49), normal oral mucosa (NOM) (n = 10), and odontogenic keratocyst (OKC) (n = 15) tissues. AM was further classified according to the presence or absence of BRAF V600E. The relationship between BRAF V600E and invasion as well as growth was evaluated. In addition, correlation analysis was performed using immunohistochemistry and confirmed via double-labeling immunofluorescence. Finally, comparative analyses using mass spectrometry, immunohistochemistry, and immunofluorescence were performed to explore and identify underlying mechanisms. RESULTS: AM exhibited a higher incidence of BRAF V600E mutation than NOM and OKC. BRAF V600E expression was positively correlated with the invasion-associated proteins MMP2 and MMP9 and the growth-related protein Ki-67. Proteomic data revealed that BRAF V600E primarily activates the MAPK signaling pathway in AM, particularly driving the phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2). CONCLUSIONS: In summary, the findings suggested that the BRAF V600E mutation enhances the invasion and growth abilities of AM via the MAPK/ERK signaling pathway. Thus, targeting BRAF V600E or the MAPK/ERK pathway may be a potential AM therapy.

Artificial intelligence-powered optimization of KI-67 assessment in breast cancer: enhancing precision and workflow efficiency. a literature review.

Breast Cancer (BC) has evolved from traditional morphological analysis to molecular profiling, identifying new subtypes. Ki-67, a prognostic biomarker, helps classify subtypes and guide chemotherapy decisions. This review explores how artificial intelligence (AI) can optimize Ki-67 assessment, improving precision and workflow efficiency in BC management. The study presents a critical analysis of the current state of AI-powered Ki-67 assessment. Results demonstrate high agreement between AI and standard Ki-67 assessment methods highlighting AI's potential as an auxiliary tool for pathologists. Despite these advancements, the review acknowledges limitations such as the restricted timeframe and diverse study designs, emphasizing the need for further research to address these concerns. In conclusion, AI holds promise in enhancing Ki-67 assessment's precision and workflow efficiency in BC diagnosis. While challenges persist, the integration of AI can revolutionize BC care, making it more accessible and precise, even in resource-limited settings.

Near-infrared photoimmunotherapy in the models of hepatocellular carcinomas using cetuximab-IR700.

Epidermal growth factor receptor (EGFR) has emerged as an important therapeutic target in many cancers, and overexpression of EGFR is frequently observed in hepatocellular carcinomas (HCCs). Near-infrared photoimmunotherapy (NIR-PIT) is a new anticancer treatment that selectively damages the cell membrane of cancer cells after NIR light-induced photochemical reaction of IR700, which is bound to a targeting antibody on the cell membrane. NIR-PIT using cetuximab-IR700 has already been approved in Japan, is under review by the US Food and Drug Administration (FDA) for advanced head and neck cancers, and its safety has been established. However, EGFR has not been investigated as a target in NIR-PIT in HCCs. Here, we investigate the application of NIR-PIT using cetuximab-IR700 to HCCs using xenograft mouse models of EGFR-expressing HCC cell lines, Hep3B, HuH-7, and SNU-449. In vitro NIR-PIT using EGFR-targeted cetuximab-IR700 killed cells in a NIR light dose-dependent manner. In vivo NIR-PIT resulted in a delayed growth compared with untreated controls. In addition, in vivo NIR-PIT in both models showed histological signs of cancer cell damage, such as cytoplasmic vacuolation and nuclear dysmorphism. A significant decrease in Ki-67 positivity was also observed after NIR-PIT, indicating decreased cancer cell proliferation. This study suggests that NIR-PIT using cetuximab-IR700 has potential for the treatment of EGFR-expressing HCCs.

MRI Fat-Saturated T2-Weighted Radiomics Model for Identifying the Ki-67 Index of Soft Tissue Sarcomas.

BACKGROUND: Ki-67 expression has been shown to be an important risk factor associated with prognosis in patients with soft tissue sarcomas (STSs). Its assessment requires fine-needle biopsy and its accuracy can be influenced by tumor heterogeneity. PURPOSE: To develop and test an MRI-based radiomics nomogram for identifying the Ki-67 status of STSs. STUDY TYPE: Retrospective. POPULATION: A total of 149 patients at two independent institutions (training cohort [high Ki-67/low ki-67]: 102 [52/50], external validation cohort [high Ki-67/low ki-67]: 47 [28/19]) with STSs. FIELD STRENGTH/SEQUENCE: Fat-saturated T2-weighted imaging (FS-T2WI) with a fat-suppressed fast spin/turbo spin echo sequence at 1.5 T or 3 T. ASSESSMENT: After radiomics feature extraction, logistic regression (LR), random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) were used to construct radiomics models to distinguish between high and low Ki-67 status. Clinical-MRI characteristics included age, gender, location, size, margin, and MRI morphological features (size, margin, signal intensity, and peritumoral hyperintensity) were assessed. Univariate and multivariate logistic regression analysis were applied for screening significant risk factors. Radiomics nomogram was constructed by radiomics signature and risk factors. STATISTICAL TESTS: Model performances (discrimination, calibration, and clinical usefulness) were validated in the validation cohort. The nomogram was assessed using the Harrell index of concordance (C-index), calibration curve analysis. The clinical utility of the model was assessed by decision curve analysis (DCA). RESULTS: LR, RF, SVM, and KNN models represented AUCs of 0.789, 0.755, 0.726, and 0.701 in the validation cohort (P > 0.05). The nomogram had a C-index of 0.895 (95% CI: 0.837-0.953) in the training cohort and 0.852 (95% CI: 0.796-0.957) in the validation cohort and it demonstrated good calibration and clinical utility (P = 0.972 for the training cohort and P = 0.727 for the validation cohort). DATA CONCLUSION: This MRI-based radiomics nomogram developed showed good performance in identifying Ki-67 expression status in STSs. TECHNICAL EFFICACY STAGE: 2.

T1 and ADC histogram parameters may be an in vivo biomarker for predicting the grade, subtype, and proliferative activity of meningioma.

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.

Correlations between intravoxel incoherent motion-derived fast diffusion and perfusion fraction parameters and VEGF- and MIB-1-positive rates in brain gliomas: an intraoperative MR-navigated, biopsy-based histopathologic study.

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.

Prediction of Ki-67 expression in gastrointestinal stromal tumors using radiomics of plain and multiphase contrast-enhanced CT.

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.

Grading meningiomas with diffusion metrics: a comparison between diffusion kurtosis, mean apparent propagator, neurite orientation dispersion and density, and diffusion tensor imaging.

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.

Dynamic contrast-enhanced MRI perfusion parameters are imaging biomarkers for angiogenesis in lung cancer.

BACKGROUND: Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may have the potential to reflect angiogenesis and proliferation of pulmonary neoplasms. PURPOSE: To verify whether DCE-MRI can identify pulmonary neoplasm property and evaluate the correlation of DCE-MRI perfusion parameters with microvessel density (MVD) and Ki-67 in lung cancer. MATERIAL AND METHODS: This study enrolled 65 patients with one pulmonary neoplasm who underwent computed tomography-guided percutaneous lung biopsy with pathological diagnosis (43 malignant, 22 benign; mean age = 59.71 ± 11.72 years). All patients did DCE-MRI before biopsy. Quantitative MRI parameters including endothelial transfer constant (Ktrans), flux rate constant (Kep), and fractional extravascular extracellular space (EES) volume (Ve) were calculated by extended Tofts linear model. MVD was evaluated by CD34-expressing tumor vessels. Proliferation was assessed by Ki-67 staining. The correlations of parameters with MVD and Ki-67 expression were analyzed. RESULTS: Ktrans and Kep values were significantly increased in malignant lesions compared to benign lesions (P = 0.001 and 0.022, respectively), whereas no statistical difference in Ve was found. The CD34 expression was positively correlated to Ktrans (r = 0.608; P = 0.004) and Kep (r = 0.556; P = 0.001). Subsequent subtype analyses also showed positive correlations of Ktrans and Kep with MVD in adenocarcinoma group (r = 0.550 and 0.563; P = 0.012 and 0.015, respectively). No significant correlation was found between these parameters and Ki-67. CONCLUSION: Ktrans and Kep may distinguish benign and malignant pulmonary neoplasm. Ktrans and Kep, with their positive correlation to MVD, can be used as non-invasive parameters reflecting lung cancer angiogenesis.

Consistency and Variation in Doublecortin and Ki67 Antigen Detection in the Brain Tissue of Different Mammals, including Humans.

Recently, a population of "immature" neurons generated prenatally, retaining immaturity for long periods and finally integrating in adult circuits has been described in the cerebral cortex. Moreover, comparative studies revealed differences in occurrence/rate of different forms of neurogenic plasticity across mammals, the "immature" neurons prevailing in gyrencephalic species. To extend experimentation from laboratory mice to large-brained mammals, including humans, it is important to detect cell markers of neurogenic plasticity in brain tissues obtained from different procedures (e.g., post-mortem/intraoperative specimens vs. intracardiac perfusion). This variability overlaps with species-specific differences in antigen distribution or antibody species specificity, making it difficult for proper comparison. In this work, we detect the presence of doublecortin and Ki67 antigen, markers for neuronal immaturity and cell division, in six mammals characterized by widely different brain size. We tested seven commercial antibodies in four selected brain regions known to host immature neurons (paleocortex, neocortex) and newly born neurons (hippocampus, subventricular zone). In selected human brains, we confirmed the specificity of DCX antibody by performing co-staining with fluorescent probe for DCX mRNA. Our results indicate that, in spite of various types of fixations, most differences were due to the use of different antibodies and the existence of real interspecies variation.

Prognostic Value Of Basal Markers (Epidermal Growth Factor Receptor "EGFR" And Cytokeratin 5/6) Expression In Triple-Negative Invasive Breast Cancer.

Objectives: The To distinguish between basal and non-basal subtypes of triple-negative breast cancers based on epidermal growth factor receptor and cytokeratin 5/6, and to establish the association of the diagnosis with clinicopathological parameters and survival rates. Method: The retrospective study was conducted at the Clinical Oncology and Nuclear Medicine Department of Kafrelsheikh University Hospital and Tanta University Hospital, Egypt, and comprised medical records from January 2014 to December 2018 related to cases with histopathologically proven triple-negative breast cancer who had been treated and followed up for at least 5 years. The cases had been evaluated using immunohistochemistry for epidermal growth factor receptor and Cytokeratin 5/6 expression. Data related to prognostic factors, overallsurvival and disease free survival was retrieved. Data was analysed using SPSS 21. RESULTS: There were 100 patients with median age 50 years (inter-quartile range: 35-55.25 years; range: 22-69 years). There were 58(58%) pre-menopausal subjects, 15(15%) had positive family history, and 68(68%) had tumour size T2. Basal markers were noted in 74(74%) patients. Basal subtype was significantly more common in patients aged <50 years at diagnosis, premenopausal women, patients with positive nodal status, those with grade III tumours, and patients with Ki67 proliferation marker >20% (p<0.05). Tumour size, histological subtypes and lympho-vascular invasion were not significantly different between the groups (p>0.05). The basal subtype had worse disease-free survival and overall survival rates (p<0.05). CONCLUSIONS: Triple-negative breast cancer patients who expressed epidermal growth factor receptor and/or cytokeratin 5/6 were found to have poor findings, with worse disease-free survival and overall survival.

Diagnostic and prognostic role of cancer stem cell biomarkers in oral squamous cell carcinoma; A Systematic Review.

Objectives: To evaluate the role of cancer stem cell biomarkers in diagnosis and prognosis of OSCC patients. METHODS: The search strategy was entered into PubMed NLM, EBSCO CINAHL, EBSCO Dentistry & Oral Sciences Source, Wiley Cochrane Library, and Scopus. The full text eligible studies (n=7) were assessed for their quality using the JBI Critical Appraisal Checklist to evaluates the methodological quality of the studies based on possibility of bias in its design, conduct, and analysis. Selected studies were further analysed based on different parameters such as publication year, sample size, and outcomes. RESULTS: A total of 432 studies were identified through the search strategy. A total of 306 records were removed before screening either because of duplication or marked ineligible by the automation tools. The screened records were 126 out of which 104 were removed as they were not conducted on OSCC. Twenty-two reports were sought for retrieval, however, we could not find the full text of 3 studies and12 studies were excluded because the biomarkers were not associated with cancer stem cells. The most common cancer stem cell biomarkers associated with OSCC were MCT1,VEGF-A, GD15, HIF1 α, Ki67, Hsp 70, Cyclin D1, and CD44. CONCLUSIONS: Various stem cell biomarkers have been found to have diagnostic and prognostic role in oral squamous cell carcinoma such as Cyclin D1, VEGF-A, GD15, and CD44. They can be used to predict the overall survival rate, local progression-free survival rate, and distant metastasis-free survival rate in Head and Neck cancer patients.

Correlation of the Ki67 Working Group prognostic risk categories with the Oncotype DX Recurrence Score in early breast cancer.

BACKGROUND: The relationship between Ki67 assessed by immunohistochemistry (IHC) and the Oncotype DX Recurrence Score (RS) is unclear. The objective of this study was to determine the correlation between the 21-gene RS and IHC-measured Ki67 with the prognostic classification groups recommended by the International Ki67 Working Group (IKWG). METHODS: The authors performed a retrospective chart review of women who had hormone receptor (HR)-positive, human epidermal growth factor receptor 2-negative early breast cancer with zero to three positive lymph nodes and both Ki67 and the 21-gene RS performed at their institution from 2013 to 2021. Patients were categorized into low (≤5%), intermediate (6%-29%), and high Ki67 groups (≥30%) according to IKWG recommendations. Overall agreement and risk-stratified agreement between Ki67 and RS were assessed with the proportion of agreement and the κ statistic. RESULTS: The study included 525 patients with HR-positive breast cancer. Among the 49% of patients with intermediate Ki67 values of 6%-29%, the distribution of low (0-10), intermediate (11-25), and high RS (26-100) was 19%, 66%, and 15%, respectively. There was slight agreement (κ = 0.01-0.20) between Ki67 and RS (κ = 0.027) in the overall population, although this was not significant (p = .1985). There was fair agreement (κ = 0.21-0.40) between high Ki67 and RS values (κ = 0.280; p < .0001). A higher progesterone receptor percentage was associated with lower RS values (p > .0001) but not lower Ki67 values. A positive nodal status and a larger tumor size were associated with higher Ki67 values (p = .0059 and p < .0001) but not with RS. CONCLUSIONS: In this group of patients selected to have a 21-gene RS, there was no significant correlation between Ki67 and RS in the overall population, and there was fair agreement between high Ki67 and high RS values. LAY SUMMARY: In patients with early-stage, hormone receptor-positive breast cancer, decisions on adjuvant chemotherapy are based on certain biological features of the cancer and genomic assays such as the Oncotype DX Recurrence Score (RS). The goal of this study was to determine the correlation between Ki67, a marker of proliferation, and the Oncotype DX RS, a 21-gene assay demonstrated to be predictive of an adjuvant chemotherapy benefit in patients with early-stage breast cancer. In 525 patients, the authors did not find a significant correlation between Ki67 and RS.

Soft tissue sarcoma: IVIM and DKI parameters correlate with Ki-67 labeling index on direct comparison of MRI and histopathological slices.

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.

Machine learning with multiparametric breast MRI for prediction of Ki-67 and histologic grade in early-stage luminal breast cancer.

OBJECTIVES: To investigate whether machine learning-based prediction models using 3-T multiparametric MRI (mpMRI) can predict Ki-67 and histologic grade in stage I-II luminal cancer. METHODS: Between 2013 and 2019, consecutive women with luminal cancers who underwent preoperative MRI with diffusion-weighted imaging (DWI) and surgery were included. For prediction models, morphology, kinetic features using computer-aided diagnosis (CAD), and apparent diffusion coefficient (ADC) at DWI were evaluated by two radiologists. Logistic regression analysis was used to identify mpMRI features for predicting Ki-67 and grade. Diagnostic performance was assessed using eight machine learning algorithms incorporating mpMRI features and compared using the DeLong method. RESULTS: Of 300 women, 203 (67.7%) had low Ki-67 and 97 (32.3%) had high Ki-67; 242 (80.7%) had low grade and 58 (19.3%) had high grade. In multivariate analysis, independent predictors for higher Ki-67 were washout component > 13.5% (odds ratio [OR] = 4.16; p < 0.001) and intratumoral high SI on T2-weighted image (OR = 1.89; p = 0.022). Those for higher grade were washout component > 15.5% (OR = 7.22; p < 0.001), rim enhancement (OR = 2.59; p = 0.022), and ADC value < 0.945 × 10-3 mm2/s (OR = 2.47; p = 0.015). Among eight models using these predictors, six models showed the equivalent performance for Ki-67 (area under the receiver operating characteristic curve [AUC]: 0.70) and Naive Bayes classifier showed the highest performance for grade (AUC: 0.79). CONCLUSIONS: A prediction model incorporating mpMRI features shows good diagnostic performance for predicting Ki-67 and histologic grade in patients with luminal breast cancers. KEY POINTS: • Among multiparametric MRI features, kinetic feature of washout component >13.5% and intratumoral high signal intensity on T2-weighted image were associated with higher Ki-67. • Washout component >15.5%, rim enhancement, and mean apparent diffusion coefficient value < 0.945 × 10-3 mm2/s were associated with higher histologic grade. • Machine learning-based prediction models incorporating multiparametric MRI features showed good diagnostic performance for Ki-67 and histologic grade in luminal breast cancers.

Mean apparent propagator-MRI in evaluation of glioma grade, cellular proliferation, and IDH-1 gene mutation status.

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.

Reliability of negative cone specimens of the cervix: A review.

OBJECTIVES: Cervical conization specimens with a negative result for high-grade lesion are not infrequent in clinical practice and there are no protocols to address this issue. The purpose of this manuscript is to analyze factors that affect the reliability on these situations and provide recommendations to guide the gynecologists on their practice. METHODS: We searched original articles on Pubmed/Medline database that analyzed negative cones using different combinations of descriptors. There were no restrictions regarding the language or the year of publication. RESULTS: Nineteen articles were selected and a total of 7310 cones analyzed. The negative excision rate ranged from 10 to 35%. Among the reasons to explain absence of lesion, the most frequent were errors in colposcopy, spontaneous lesion regression, complete removal of small lesions during biopsy, errors in the pre-conization material, false-negative results, and excisional error. Pathological specimen review and application of immunohistochemical biomarkers p16 and Ki-67 seemed to improve accuracy and help in challenging differential diagnosis. Recurrence was detected in up to 30%, as seen in positive cones with compromised margins. Importantly, testing for HPV demonstrated benefits in reducing the number of negative cones. CONCLUSIONS: Several factors could contribute to a negative result in a conization. Our main recommendations include: interval of 4-6 weeks between biopsy and conization, repeat the colposcopy during the excision, consider short-term reevaluation for small colposcopy lesions, perform deep sectioning levels in the paraffin block, use of immunohistochemical markers, HPV testing, and strict surveillance during follow-up as performed for positive cases with compromised margins.

Evaluation of Caspase-3 and Ki-67 expression in squamous cell hyperplasia of the stomach induced by Platycodi radix water extract in Sprague-Dawley rats.

Platycodi radix is widely used in traditional herbal medicine for the treatment of bronchitis, asthma, pulmonary tuberculosis, hypertension, hyperlipidemia, and diabetes. This study aimed to investigate cell proliferation (Ki-67) and apoptosis (Caspase-3) potential in squamous cell hyperplasia of the stomach induced by a Platycodi radix water extract in a subchronic toxicity study. One hundred formalin-fixed, paraffin-embedded stomach tissues of rats treated with Platycodi radix at doses of 0, 500, 1,000, and 3,000 mg/kg body weight/day were used for the analysis. They were conventionally stained using hematoxylin and eosin (H&E) and immunohistochemically (IHC) stained using caspase-3 and Ki-67 antibodies. The incidence of squamous cell hyperplasia was significantly increased in the 3,000 mg/kg b.w./day treatment group in both sexes (p<0.01). However, the hyperplastic change was completely repaired after 4 weeks of recovery period. Ki-67 expression was similar in all groups, with no statistically significant differences among the groups. Caspase-3 expression was significantly increased in both sexes in the 3,000 mg/kg b.w./day treatment group (p<0.01), compared with the vehicle control groups, and then reduced to normal levels in the recovery groups in both sexes. In conclusion, this study showed that squamous cell hyperplasia induced by the Platycodi radix water extract in the limiting ridge of the stomach is not considered to be abnormal proliferative change; as a result, squamous cell hyperplasia is considered to be a non-adverse effect when induced by the oral administration of the Platycodi radix water extract once daily for 13 weeks in rats.