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Background/Objectives: Bone morphogenetic protein and activin membrane-bound inhibitor (BAMBI) is an antagonist of transforming growth factor (TGF)-β type 1 signaling. BAMBI functions as an anti-fibrotic protein and exerts pro- as well as anti-cancerogenic activities. Our study aimed to correlate hepatocyte BAMBI protein levels in hepatocellular carcinoma (HCC) with T stage, lymph node invasion, vessel invasion, grading, tumor size and Union for International Cancer Control (UICC) stage, as well as with liver inflammation and fibrosis stages. Methods: Hepatocyte BAMBI protein expression was assessed by immunohistochemistry in HCC tissues of 320 patients and non-tumor tissues of 51 patients. Results: In the HCC tissues of the whole cohort and sex-specific analysis, BAMBI protein was not related to T stage, vessel invasion, lymph node invasion, histologic grade, UICC stage and tumor size. Accordingly, BAMBI was not associated with overall survival, recurrence-free and metastasis-free survival. BAMBI protein levels in tumor and non-tumor tissues were not related to inflammation and fibrosis grade. BAMBI protein levels in HCC tissues and non-tumor tissues from HCC patients, which were analyzed by immunoblot in a small cohort and by immunohistochemistry in the tissues of patients described above, were similar. Notably, BAMBI protein was low-abundant in HCC tissues of hepatitis C virus (HCV) compared to hepatitis B virus (HBV)-infected patients with comparable disease severity. Immunoblot analysis revealed reduced BAMBI protein in non-tumor tissues of patients with HCV in comparison to patients with HBV and normal human liver tissues. Conclusions: In summary, this analysis showed that hepatocyte BAMBI protein levels of patients with HCC are related to HCV infection rather than the severity of the underlying liver disease and cancer staging. [ABSTRACT FROM AUTHOR]

Poor differentiation is strongly associated with poor outcomes in cutaneous squamous cell carcinoma (CSCC). In addition, the National Comprehensive Cancer Network (NCCN) guidelines designate poorly differentiated tumors as “very high risk”. Despite its clear prognostic implications, there is no standardized grading system for CSCC differentiation in common use today. CSCC differentiation is graded inconsistently by both dermatopathologists and Mohs surgeons, and reliability studies have demonstrated suboptimal inter- and intra-rater reliability in both of these groups. The absence of a standardized and reliable grading system has impeded the use of differentiation in CSCC staging, despite its apparent correlation with disease outcomes. We performed a comprehensive review of the literature summarizing historical CSCC differentiation grading systems, as well as grading systems in non-cutaneous head and neck SCC as a point of reference. Relevant articles were identified by searching Embase and PubMed, as well as by reviewing reference lists for additional articles and histology textbook excerpts. CSCC grading systems that were identified and summarized include the historical Broders system, the World Health Organization system, the College of American Pathologists’ system, and a system described by a 2023 Delphi consensus panel of dermatopathologists. [ABSTRACT FROM AUTHOR]

Simple Summary: Current clinical practice guidelines support additional locoregional surgery after local resection of early colorectal cancer when one or more of the following risk factors are present: poor differentiation grade, lymphovascular invasion, deep submucosal invasion, moderate or high tumor budding, and deep margin involvement. The absence of all these risk criteria selects a subgroup of patients with very good prognosis that can safely avoid additional surgery. However, lymph node metastases are only identified in 10–20% of patients who ultimately undergo additional surgery, so that 80–90% of the surgeries turn out to be unnecessary. In this investigation, we find that indicating additional surgery in early colorectal cancer only when either moderate or high tumor budding, poorly differentiated clusters, or lymphovascular invasion are present could reduce unnecessary surgeries by 40–45% without significantly increasing the proportion of patients with lymph node metastases who are not offered additional surgery. Background: The low positive predictive value for lymph node metastases (LNM) of common practice risk criteria (CPRC) in T1 colorectal carcinoma (CRC) leads to manyunnecessary additional surgeries following local resection. This study aimed to identify criteria that may improve on the CPRC. Methods: Logistic regression analysis was performed to determine the association of diverse variables with LNM or 'poor outcome' (LNM and/or distant metastases and/or recurrence) in a single center T1 CRC cohort. The diagnostic capacity of the set of variables obtained was compared with that of the CPRC. Results: The study comprised 161 cases. Poorly differentiated clusters (PDC) and tumor budding grade > 1 (TB > 1) were the only independent variables associated with LNM. The area under the curve (AUC) for these criteria was 0.808 (CI 95% 0.717–0.880) compared to 0.582 (CI 95% 0.479–0.680) for CPRC. TB > 1 and lymphovascular invasion (LVI) were independently associated with 'poor outcome', with an AUC of 0.801 (CI 95% 0.731–0.859), while the AUC for CPRC was 0.691 (CI 95% 0.603–0.752). TB > 1, combined either with PDC or LVI, would reduce false positives between 41.5% and 45% without significantly increasing false negatives. Conclusions: Indicating additional surgery in T1 CRC only when either TB > 1, PDC, or LVI are present could reduce unnecessary surgeries significantly. [ABSTRACT FROM AUTHOR]

Aims: Programmed death‐ligand 1 (PD‐L1) expression is a predictive biomarker for adjuvant immunotherapy and has been linked to poor differentiation in lung adenocarcinoma. However, its prevalence and prognostic role in the context of the novel histologic grade has not been evaluated. Methods: We analysed a cohort of 1233 patients with resected lung adenocarcinoma where PD‐L1 immunohistochemistry (22C3 assay) was reflexively tested. Tumour PD‐L1 expression was correlated with the new standardized International Association for the Study of Lung Cancer (IASLC) histologic grading system (G1, G2, and G3). Clinicopathologic features including patient outcome were analysed. Results: PD‐L1 was positive (≥1%) in 7.0%, 23.5%, and 63.0% of G1, G2, and G3 tumours, respectively. PD‐L1 positivity was significantly associated with male sex, smoking, and less sublobar resection among patients with G2 tumours, but this association was less pronounced in those with G3 tumours. PD‐L1 was an independent risk factor for recurrence (adjusted hazard ratio [HR] = 3.25, 95% confidence intervals [CI] = 1.93–5.48, P < 0.001) and death (adjusted HR = 2.69, 95% CI = 1.13–6.40, P = 0.026) in the G2 group, but not in the G3 group (adjusted HR for recurrence = 0.94, 95% CI = 0.64–1.40, P = 0.778). Conclusion: PD‐L1 expression differs substantially across IASLC grades and identifies aggressive tumours within the G2 subgroup. This knowledge may be used for both prognostication and designing future studies on adjuvant immunotherapy. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) has consistently shown a global rise in incidence. p53 exerts regulatory function in signaling processes, with the p53 mutation accelerating the late stage of colorectal carcinogenesis. Programmed death ligand 1 (PD-L1) is an immune checkpoint regulator whose role in targeted therapy of CRCs needs to be evaluated. Beta-catenin plays a fundamental role in cell adhesion, with long-term effects on disease progression and survival. A detailed evaluation of all these factors is essential to tailoring new therapeutic approaches in advanced-stage cases. Aims and Objectives: To study the immunohistochemical (IHC) expression of p53, PD-L1, and beta-catenin in different histologic grades and stages of colorectal carcinomas. Materials and Methods: A total of 29 cases of segmental colectomy were included in the study population. Tumor sections were sent for IHC study of p53, PD-L1, and beta-catenin and interpreted as per standard protocol. Findings were tabulated against the histologic grade and stages of CRCs. Statistical analysis was done using SPSS 25.0 to test for statistical significance at P

Background: Colorectal cancer (CRC) has consistently shown a global rise in incidence. p53 exerts regulatory function in signaling processes, with the p53 mutation accelerating the late stage of colorectal carcinogenesis. Programmed death ligand 1 (PD-L1) is an immune checkpoint regulator whose role in targeted therapy of CRCs needs to be evaluated. Beta-catenin plays a fundamental role in cell adhesion, with long-term effects on disease progression and survival. A detailed evaluation of all these factors is essential to tailoring new therapeutic approaches in advanced-stage cases. Aims and Objectives: To study the immunohistochemical (IHC) expression of p53, PD-L1, and beta-catenin in different histologic grades and stages of colorectal carcinomas. Materials and Methods: A total of 29 cases of segmental colectomy were included in the study population. Tumor sections were sent for IHC study of p53, PD-L1, and beta-catenin and interpreted as per standard protocol. Findings were tabulated against the histologic grade and stages of CRCs. Statistical analysis was done using SPSS 25.0 to test for statistical significance at P<0.05. Results: The study population predominantly consisted of males (66%), mainly in the age group of 46-60 years. p53 was significantly more expressed in left colonic tumors. PD-L1 expression was also significantly associated with histologic grade and nodal metastasis. High beta-catenin expression was seen in well-differentiated adenocarcinomas and lower T and N-stage disease. Positive p53 also correlated with positive PD-L1 expression. However, expression of p53 was also high in tumors with low beta-catenin expression. Conclusion: p53, PD-L1, and beta-catenin may have a role in prognostication and predicting long-term survival outcomes in CRC cases. These may also act as potential therapeutic targets with a more detailed evaluation and a larger sample size of CRC cases. [ABSTRACT FROM AUTHOR]

Background/Objectives: Bone morphogenetic protein and activin membrane-bound inhibitor (BAMBI) is an antagonist of transforming growth factor (TGF)-β type 1 signaling. BAMBI functions as an anti-fibrotic protein and exerts pro- as well as anti-cancerogenic activities. Our study aimed to correlate hepatocyte BAMBI protein levels in hepatocellular carcinoma (HCC) with T stage, lymph node invasion, vessel invasion, grading, tumor size and Union for International Cancer Control (UICC) stage, as well as with liver inflammation and fibrosis stages. Methods: Hepatocyte BAMBI protein expression was assessed by immunohistochemistry in HCC tissues of 320 patients and non-tumor tissues of 51 patients. Results: In the HCC tissues of the whole cohort and sex-specific analysis, BAMBI protein was not related to T stage, vessel invasion, lymph node invasion, histologic grade, UICC stage and tumor size. Accordingly, BAMBI was not associated with overall survival, recurrence-free and metastasis-free survival. BAMBI protein levels in tumor and non-tumor tissues were not related to inflammation and fibrosis grade. BAMBI protein levels in HCC tissues and non-tumor tissues from HCC patients, which were analyzed by immunoblot in a small cohort and by immunohistochemistry in the tissues of patients described above, were similar. Notably, BAMBI protein was low-abundant in HCC tissues of hepatitis C virus (HCV) compared to hepatitis B virus (HBV)-infected patients with comparable disease severity. Immunoblot analysis revealed reduced BAMBI protein in non-tumor tissues of patients with HCV in comparison to patients with HBV and normal human liver tissues. Conclusions: In summary, this analysis showed that hepatocyte BAMBI protein levels of patients with HCC are related to HCV infection rather than the severity of the underlying liver disease and cancer staging.

Objective: The aim of this study is to analyze the differences in independent prognostic factors of cancer-specific survival (CSS) and overall survival (OS) in patients with different grades of histologic differentiation of colorectal cancer (CRC) who received preoperative neoadjuvant chemotherapy (NAC) and to establish a nomogram for predicting postoperative survival based on moderately differentiated CRC. Methods: We analyzed CRC patients from the SEER database who received NAC before operation between 2010 and 2015. The Kaplan-Meier curves were drawn to describe the differences in CSS and OS of CRC patients with different histologic grades of differentiation. Cox regression analysis was used to determine the independent prognostic factors. Nomograms were established to predict CSS and OS at 3 and 5 years by integrating independent prognostic factors. The calibration curve, receiver operating characteristic (ROC) curve, and C-index were used to verify nomograms. Results: A total of 6481 patients with CRC who received preoperative NAC were included in this study. Patients with different grades of histologic differentiation had significant differences in CSS and OS (P < 0.001), and the independent prognostic factors of different grades of histologic differentiation showed heterogeneity. In patients with moderately differentiated grade CRC, the independent prognostic factors for CSS and OS were age, race, marital status, serum carcinoembryonic antigen (CEA) level before treatment, site of primary tumor, histologic type, pT stage, pN stage, liver metastasis, and lung metastasis. Nomograms were established based on the independent prognostic factors of moderately differentiated grade CRC, and its calibration curves, area under the curve (AUC), and C-index showed good prediction accuracy. Conclusions: The independent prognostic factors of CSS and OS are different in patients with different grades of histologic differentiation of CRC who received NAC before the operation. Nomograms can be used to predict the survival of patients with moderately differentiated grade CRC who received preoperative NAC and to assist clinicians in making clinical decisions. [ABSTRACT FROM AUTHOR]

We explored the added value of a radiomic strategy based on quantitative transverse relaxation (T2) mapping and conventional magnetic resonance imaging (MRI) to evaluate the histologic grade of bladder cancer (BCa) preoperatively. Patients who were suspected of BCa underwent pelvic MRI (including T2 mapping and diffusion-weighted imaging (DWI) before any treatment. All patients with histological-proved urothelial BCa were included. We constructed different prediction models using the mean signal values and radiomic features from both T2 mapping and apparent diffusion coefficient (ADC) maps. The diagnostic performance of each model or parameter was assessed using receiver operating characteristic curves. In total, 92 patients were finally included (training cohort, n = 64; testing cohort, n = 28); among these, 71 had high-grade BCa. In the testing cohort, the T2-mapping radiomic model achieved the highest prediction performance (area under the curve (AUC), 0.87; 95% confidence interval (CI), 0.73–1.0) compared with the ADC radiomic model (AUC, 0.77; 95%CI, 0.56–0.97), and the joint radiomic model of 0.78 (95%CI, 0.61–0.96). Our results demonstrated that radiomic mapping could provide more information than direct evaluation of T2 and ADC values in differentiating histological grades of BCa. Additionally, among the radiomic models, the T2-mapping radiomic model outperformed the ADC and joint radiomic models. [ABSTRACT FROM AUTHOR]

Purpose: Accurate histologic grade assessment is helpful for clinical decision making and prognostic assessment of sinonasal squamous cell carcinoma (SNSCC). This research aimed to explore whether whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps with machine learning algorithms can predict histologic grade of SNSCC. Methods: One hundred and forty-seven patients with pathologically diagnosed SNSCC formed this retrospective study. Sixty-six patients were low-grade (grade I/II) and eighty-one patients were high-grade (grade III). Eighteen histogram features were obtained from quantitative ADC maps. Additionally, the mean ADC value and clinical features were analyzed for comparison with histogram features. Machine learning algorithms were applied to build the best diagnostic model for predicting histological grade. The receiver operating characteristic (ROC) curve was used to evaluate the performance of each model prediction, and the area under the ROC curve (AUC) were analyzed. Results: The histogram model based on three features (10th Percentile, Mean, and 90th Percentile) with support vector machine (SVM) classifier demonstrated excellent diagnostic performance, with an AUC of 0.947 on the testing dataset. The AUC of the histogram model was similar to that of the mean ADC value model (0.947 vs 0.957; P = 0.7029). The poor diagnostic performance of the clinical model (AUC = 0.692) was improved by the combined model incorporating histogram features or mean ADC value (P < 0.05). Conclusion: ADC histogram analysis improved the projection of SNSCC histologic grade, compared with clinical model. The complex histogram model had comparable but not better performance than mean ADC value model. [ABSTRACT FROM AUTHOR]

Nottingham histological grade (NHG) 2 breast cancer has an intermediate risk of recurrence, which is not informative for therapeutic decision-making. We sought to develop and independently validate an MRI-based radiomics signature (Rad-Grade) to improve prognostic re-stratification of NHG 2 tumors. Nine hundred-eight subjects with invasive breast cancer and preoperative MRI scans were retrospectively obtained. The NHG 1 and 3 tumors were randomly split into training and independent test cohort, with the NHG 2 as the prognostic validation set. From MRI image features, a radiomics-based signature predictive of the histological grade was built by use of the LASSO logistic regression algorithm. The model was developed for identifying NHG 1 and 3 radiological patterns, followed with re-stratification of NHG 2 tumors into Rad-Grade (RG)2-low (NHG 1-like) and RG2-high (NHG 3-like) subtypes using the learned patterns, and the prognostic value was assessed in terms of recurrence-free survival (RFS). The Rad-Grade showed independent prognostic value for re-stratification of NHG 2 tumors, where RG2-high had an increased risk for recurrence (HR 2.20, 1.10–4.40, p = 0.026) compared with RG2-low after adjusting for established risk factors. RG2-low shared similar phenotypic characteristics and RFS outcomes with NHG 1, and RG2-high with NHG 3, revealing that the model captures radiomic features in NHG 2 that are associated with different aggressiveness. The prognostic value of Rad-Grade was further validated in the NHG2 ER+ (HR 2.53, 1.13–5.56, p = 0.023) and NHG 2 ER+LN– (HR 5.72, 1.24–26.44, p = 0.025) subgroups, and in specific treatment contexts. The radiomics-based re-stratification of NHG 2 tumors offers a cost-effective promising alternative to gene expression profiling for tumor grading and thus may improve clinical decisions. [ABSTRACT FROM AUTHOR]

The presence of lymph node (LN) positivity in endometrial adenocarcinoma (EAC) patients guides adjuvant treatment, but recommendations regarding LN evaluation at the time of primary surgery remain variable. Primary pathologic tumor characteristics may predict risk of LN involvement in EAC patients with limited LN evaluation. Patients diagnosed between 2004-2016 with pathologic T1-T2 EAC in the National Cancer Database who had at least one lymph node sampled at the time of surgery were included. Pathologic primary tumor predictors of LN involvement were identified using logistic regression. To predict overall, pelvic only, and paraaortic and/or pelvic LN involvement, nomograms were generated. Among 57,810 EAC patients included, 4002 were node positive. On multivariable analysis, increasing pathologic tumor category (pT2 versus pT1a, odds ratio (OR) 5.43, 95% confidence interval (CI) 4.89-6.02, p < 0.001), increasing pathologic tumor grade (grade 3 versus grade 1, OR 1.62, 95% CI 1.47-1.79, p < 0.001), increase in tumor size per centimeter (OR 1.05, 95% CI 1.04-1.06, p < 0.001), and presence of lymphovascular invasion (LVI) (OR 6.33, 95% CI 5.87-6.83, p<0.001) were predictive of overall LN positivity. The presence of LVI was a stronger predictor of paraaortic LN involvement (OR 6.43, 95% CI 5.55-7.47, p < 0.001) than pelvic LN involvement (OR 5.42, 95% CI 4.98-5.90, p < 0.001) in multivariable analysis. For patients with limited LN evaluation, pathologic tumor features can be used to estimate the risk of pelvic or paraaortic LN involvement. This information may inform adjuvant treatment decisions and guide future studies. [ABSTRACT FROM AUTHOR]

Breast cancer is the second utmost common cancer among women. In this research study, two feature selection methods, namely Consistency first Search-Best First search (CFS-BFS) and Consistency-Best First Search (Consistency-BFS) are used to find out the significant biomarkers for breast cancer. The feature selection methods pick a small count of important and relevant genes providing a higher degree of accuracy. The count of biomarkers selected in Consistency-BFS is less in comparison to CFS-BFS method. Three common identified biomarkers' genes are recognised to help in diagnosis and prognosis of breast cancer, namely SLC39A6, ESR1, and CDC20 are selected on the basis of histologic-grade and molecular subtype of breast cancer. These three genes identified are even found in PAM50 and judged for survival variances using Kaplan-Meier Survival Model. The result suggested that overexpression of SLC39A6, ESR1, and CDC20 proves to be an influencing factor for the poor prognosis of patients suffering from breast cancer. The proposed method is successful in creating a prognostic gene signature in forecasting the survival likelihood of patients. [ABSTRACT FROM AUTHOR]

Abstract Background Accurate pathological diagnosis of invasion depth and histologic grade is key for clinical management in patients with bladder cancer (BCa), but it is labour-intensive, experience-dependent and subject to interobserver variability. Here, we aimed to develop a pathological artificial intelligence diagnostic model (PAIDM) for BCa diagnosis. Methods A total of 854 whole slide images (WSIs) from 692 patients were included and divided into training and validation sets. The PAIDM was developed using the training set based on the deep learning algorithm ScanNet, and the performance was verified at the patch level in validation set 1 and at the WSI level in validation set 2. An independent validation cohort (validation set 3) was employed to compare the PAIDM and pathologists. Model performance was evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value and negative predictive value. Results The AUCs of the PAIDM were 0.878 (95% CI 0.875–0.881) at the patch level in validation set 1 and 0.870 (95% CI 0.805–0.923) at the WSI level in validation set 2. In comparing the PAIDM and pathologists, the PAIDM achieved an AUC of 0.847 (95% CI 0.779–0.905), which was non-inferior to the average diagnostic level of pathologists. There was high consistency between the model-predicted and manually annotated areas, improving the PAIDM’s interpretability. Conclusions We reported an artificial intelligence-based diagnostic model for BCa that performed well in identifying invasion depth and histologic grade. Importantly, the PAIDM performed admirably in patch-level recognition, with a promising application for transurethral resection specimens.

Abstract Background Recent studies have shown a lower likelihood of locoregional recurrences in patients with a low 21-gene recurrence score (RS). In this single-institution study, we investigated whether there are any associations between different cutoff values of 21-gene RS, histopathological factors, and outcome in patients with long-term follow-up. Methods The study included 61 patients who had early-stage (I-II) clinically node-negative hormone receptor-positive and HER2-negative breast cancer and were tested with the 21-gene RS assay between February 2010 and February 2013. Demographic, clinicopathological, treatment, and outcome characteristics were analyzed. Results The median age was 48 years (range, 29–72 years). Patients with high histologic grade (HG), Ki-67 ≥ 25%, or Ki-67 ≥ 30% were more likely to have intermediate/high RS (≥ 18). Based on the 21-gene RS assay, only 19 patients (31%) received adjuvant chemotherapy. At a median follow-up of 112 months, 3 patients developed locoregional recurrences (4.9%), which were treated with endocrine therapy alone. Among patients treated with endocrine treatment alone (n = 42), the following clinicopathological characteristics were not found to be significantly associated with 10-year locoregional recurrence free survival (LRRFS): age 11. However, patients with RS ≥ 16 had significantly poorer 10-year LRRFS compared to those with RS

Shihui Wang, Yi Wei, Zhouli Li, Jingya Xu, Yunfeng Zhou Department of Radiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, People’s Republic of ChinaCorrespondence: Yunfeng Zhou, Department of Radiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, People’s Republic of China, Tel +86 18110876440, Email zhouyunfeng808@163.comBackground: Histological grade is an important factor in the overall prognosis of patients with invasive breast cancer. Therefore, the non-invasive assessment of histological grade in breast cancer patients is an increasing concern for clinicians. We aimed to establish an MRI-based radiomics model for preoperative prediction of invasive breast cancer histological grade.Methods: We enrolled 901 patients with invasive breast cancer and pre-operative MRI. Patients were randomly divided into the training cohort (n=630) and validation cohort (n=271) with a ratio of 7:3. A radiomics signature was constructed by extracting radiomics features from MRI images and was developed according to multivariate logistic regression analysis. The diagnostic performance of the radiomics model was assessed using receiver operating characteristic (ROC) curve analysis.Results: Of the 901 patients, 618 (68.6%) were histological grade 1 or 2 while 283 (31.4%) were histological grade 3. The area under the ROC curve (AUC) of the radiomics model for the prediction of the histological grade was 0.761 (95% CI 0.728– 0.794) in the training cohort and 0.722 (95% CI 0.664– 0.777) in the validation cohort. The decision curve analysis (DCA) demonstrated the radiomics model’s clinical application value.Conclusion: This is a preliminary study suggesting that the development of an MRI-based radiomics model can predict the histological grade of invasive breast cancer.Keywords: breast cancer, histologic grade, magnetic resonance imaging, radiomics, signature

Abstract Background The histological differentiation grades of gastric cancer (GC) are closely related to treatment choices and prognostic evaluation. Radiomics from dual-energy spectral CT (DESCT) derived iodine-based material decomposition (IMD) images may have the potential to reflect histological grades. Methods A total of 103 patients with pathologically proven GC (low-grade in 40 patients and high-grade in 63 patients) who underwent preoperative DESCT were enrolled in our study. Radiomic features were extracted from conventional polychromatic (CP) images and IMD images, respectively. Three radiomic predictive models (model-CP, model-IMD, and model-CP–IMD) based on solely CP selected features, IMD selected features and CP coupled with IMD selected features were constructed. The clinicopathological data of the enrolled patients were analyzed. Then, we built a combined model (model-Combine) developed with CP–IMD and clinical features. The performance of these models was evaluated and compared. Results Model-CP–IMD achieved better AUC results than both model-CP and model-IMD in both cohorts. Model-Combine, which combined CP–IMD radiomic features, pT stage, and pN stage, yielded the highest AUC values of 0.910 and 0.912 in the training and testing cohorts, respectively. Model-CP–IMD and model-Combine outperformed model-CP according to decision curve analysis. Conclusion DESCT-based radiomics models showed reliable diagnostic performance in predicting GC histologic differentiation grade. The radiomic features extracted from IMD images showed great promise in terms of enhancing diagnostic performance.

Background: Amide proton transfer (APT) imaging has been increasingly applied in tumor characterization. However, its value in evaluating breast cancer remains undetermined. Purpose: To assess the diagnostic performance of APT imaging in breast cancer and its association with prognostic histopathologic characteristics. Study Type: Prospective. Subjects: Eighty‐four patients with breast lesions. Field Strength/Sequence: A 3.0 T/single‐shot fast spin echo APT imaging. Assessment: APTw signal in breast lesion was quantified. Lesion malignancy, T stage, grades, Ki‐67 index, molecular biomarkers (estrogen receptor [ER] expression, progesterone receptor [PR] expression, human epidermal growth factor receptor [HER‐2] expression), molecular subtypes (luminal A, luminal B, triple negative, and HER‐2 enriched) were determined. Statistical Tests: Student t‐test, one‐way analysis of variance, receiver operating characteristic analysis, and Pearson's correlation with P < 0.05 as statistical significance. Results: APTw signal was significantly higher in malignant lesions (1.55% ± 1.24%) than in benign lesions (0.54% ± 1.13%), and in grade III lesions than in grade II lesions (1.65% ± 0.84% vs. 0.96% ± 0.96%), and in T2‐ (1.57% ± 0.64%) and T3‐stage lesions (1.54% ± 0.63%) than in T1‐stage lesions (0.81% ± 0.64%) for invasive breast carcinoma of no special type. APTw signal significantly correlated with Ki‐67 index (r = 0.364) but showed no significant difference in groups of ER (P = 0.069), PR (P = 0.069), HER‐2 (P = 0.961), and among molecular subtypes (P = 0.073). Data Conclusion: APT imaging shows potential in differentiating breast lesion malignancy and associates with prognosis‐related tumor grade, T stage, and proliferative activity. Evidence Level: 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

The chemoattractant protein chemerin is protective in experimental hepatocellular carcinoma (HCC), and high expression in HCC tissues of Asian patients was related to a favorable prognosis. Studies from Asia found reduced expression of chemerin in HCC compared to para-tumor tissues while our previous analysis observed the opposite. Aim of this study was to correlate chemerin expression in HCC tissues with disease severity of European patients Hepatocyte chemerin protein expression was assessed by immunohistochemistry in HCC tissue of 383 patients, and was low in 24%, moderate in 49% and high in 27%. High chemerin protein in the HCC tissues was related to the T stage, vessel invasion, histologic grade, Union for International Cancer Control (UICC) stage and tumor size. Chemokine-like receptor 1 (CMKLR1) is a functional chemerin receptor. CMKLR1 protein in hepatocytes was low expressed in HCC tissues of 36%, moderate in tissues of 32% and high in 32% of the HCCs. Tumor CMKLR1 was associated with the T stage, vessel invasion, histologic grade and UICC stage. Notably, sex-specific analysis revealed that associations of chemerin and CMKLR1 expression with HCC progression were significant in males but not in females. The tumor chemerin and CMKLR1 protein expression were not related to steatosis, inflammation and fibrosis grades. In summary, chemerin as well as CMKLR1 protein were related to disease severity of European HCC patients, and this was significant in males. This observation is in contrast to Asian patients where higher chemerin in the tumors was protective. Current analysis provides evidence for ethnicity and sex-related differences of tumor expressed chemerin and HCC severity. [ABSTRACT FROM AUTHOR]

Although imaging is central in the initial staging of patients with soft tissue sarcomas (STS), it remains underused and few radiological features are currently used in practice for prognostication and to help guide the best therapeutic strategy. Yet, several prognostic qualitative and quantitative characteristics from magnetic resonance imaging (MRI) and positron emission tomography (PET) have been identified over these last decades. After an overview of the current validated prognostic features based on baseline imaging and their integration into prognostic tools, such as nomograms used by clinicians, the aim of this review is to summarize more complex and innovative MRI, PET, and radiomics features, and to highlight their role to predict indirectly (through histologic grade) or directly the patients' outcomes. [ABSTRACT FROM AUTHOR]

Estrogen receptor‐positive and human epidermal growth factor receptor 2‐negative (ER+HER2−) breast cancer accounts for ~ 60–70% of all cases of invasive breast carcinoma. High‐grade ER+HER2− tumors respond poorly to endocrine therapy. In this study, we systematically analyzed clinical and multi‐omics data to find potential strategies for personalized therapy of patients with high‐grade ER+HER2− disease. Six different cohorts were analyzed, for which multi‐omics data were available. Grade III ER+HER2− cases harbored higher proportions of large tumor size (> 5 cm), lymph node metastasis, chemotherapy use, and luminal B subtypes defined by PAM50, as compared with grade I/II tumors. DNA methylation (HM450) data and methylation‐specific PCR indicated that the cg18629132 locus in the MKI67 promoter was hypermethylated in grade I/II cases and normal tissue, but hypomethylated in grade III cases or triple‐negative breast cancer, resulting in higher expression of MKI67. Mutations in ESR1 and TP53 were detected in post‐endocrine treatment metastatic samples at a higher rate than in treatment‐naive tumors in grade III cases. We identified 42 and 20 focal copy number events in nonmetastatic and metastatic high‐grade ER+HER2− cases, respectively, with either MYC or MDM2 amplification representing an independent prognostic event in grade III cases. Transcriptional profiling within grade III tumors highlighted ER signaling downregulation and upregulation of immune‐related pathways in non‐luminal‐like tumors defined by PAM50. Recursive partitioning analysis was employed to construct a decision tree of an endocrine‐resistant subgroup (GATA3‐negative and AGR‐negative) of two genes that was validated by immunohistochemistry in a Chinese cohort. All together, these data suggest that grade III ER+HER2− tumors have distinct clinical and molecular characteristics compared with low‐grade tumors, particularly in cases with non‐luminal‐like biology. Due to the dismal prognosis in this group, clinical trials are warranted to test the efficacy of potential novel therapies.

Background: Accurate pathological diagnosis of invasion depth and histologic grade is key for clinical management in patients with bladder cancer (BCa), but it is labour-intensive, experience-dependent and subject to interobserver variability. Here, we aimed to develop a pathological artificial intelligence diagnostic model (PAIDM) for BCa diagnosis. Methods: A total of 854 whole slide images (WSIs) from 692 patients were included and divided into training and validation sets. The PAIDM was developed using the training set based on the deep learning algorithm ScanNet, and the performance was verified at the patch level in validation set 1 and at the WSI level in validation set 2. An independent validation cohort (validation set 3) was employed to compare the PAIDM and pathologists. Model performance was evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value and negative predictive value. Results: The AUCs of the PAIDM were 0.878 (95% CI 0.875–0.881) at the patch level in validation set 1 and 0.870 (95% CI 0.805–0.923) at the WSI level in validation set 2. In comparing the PAIDM and pathologists, the PAIDM achieved an AUC of 0.847 (95% CI 0.779–0.905), which was non-inferior to the average diagnostic level of pathologists. There was high consistency between the model-predicted and manually annotated areas, improving the PAIDM's interpretability. Conclusions: We reported an artificial intelligence-based diagnostic model for BCa that performed well in identifying invasion depth and histologic grade. Importantly, the PAIDM performed admirably in patch-level recognition, with a promising application for transurethral resection specimens. [ABSTRACT FROM AUTHOR]

Background: Recent studies have shown a lower likelihood of locoregional recurrences in patients with a low 21-gene recurrence score (RS). In this single-institution study, we investigated whether there are any associations between different cutoff values of 21-gene RS, histopathological factors, and outcome in patients with long-term follow-up.Methods: The study included 61 patients who had early-stage (I-II) clinically node-negative hormone receptor-positive and HER2-negative breast cancer and were tested with the 21-gene RS assay between February 2010 and February 2013. Demographic, clinicopathological, treatment, and outcome characteristics were analyzed.Results: The median age was 48 years (range, 29-72 years). Patients with high histologic grade (HG), Ki-67 ≥ 25%, or Ki-67 ≥ 30% were more likely to have intermediate/high RS (≥ 18). Based on the 21-gene RS assay, only 19 patients (31%) received adjuvant chemotherapy. At a median follow-up of 112 months, 3 patients developed locoregional recurrences (4.9%), which were treated with endocrine therapy alone. Among patients treated with endocrine treatment alone (n = 42), the following clinicopathological characteristics were not found to be significantly associated with 10-year locoregional recurrence free survival (LRRFS): age < 40 years, age < 50 years, high histological or nuclear grade, high Ki-67-scores (≥ 15%, ≥ 20%, ≥ 25%, ≥ 30%), presence of lymphovascular invasion, luminal-A type, multifocality, lymph node positivity, tumor size more than 2 cm, RS ≥ 18, and RS > 11. However, patients with RS ≥ 16 had significantly poorer 10-year LRRFS compared to those with RS < 16 (75% vs. 100%, respectively; p = 0.039).Conclusions: The results suggest that patients with clinically node-negative disease and RS ≥ 16 are more likely to benefit from adjuvant chemotherapies. However, those with RS < 16 have an excellent outcome and local control in long-term follow-up with endocrine treatment alone. [ABSTRACT FROM AUTHOR]

Purpose: Among head and neck cancers, hypopharyngeal squamous cell carcinoma (HSCC) shows the highest malignancy, which is associated with histologic grading. This study was designed to investigate whether quantitative parameters derived from 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) can preoperatively estimate the histologic grade of HSCC. Methods: 18F-FDG PET/MRI of neck was successfully performed in 21 patients with histologically proven HSCC including poorly differentiated group (ten patients) and well-moderately differentiated group (eleven patients). Quantitative parameters derived from FDG-PET, diffusion-weighted imaging (DWI), and dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) were calculated based on volume of interest drawn on the tumor and compared between two groups. The efficacy of quantitative parameters for the estimation of histologic grades of HSCC was evaluated. Results: There were statistically significant differences in mean value of standard uptake value (SUV), apparent diffusion coefficient (ADC), and Ktrans derived from 18F-FDG PET/MRI of HSCC between two groups (p < 0.05). There was no statistically significant difference in other quantitative parameters derived from 18F-FDG PET/MRI of HSCC between two groups. The area under the curve (AUC) of the combination of SUVmean, ADCmean, and Ktrans in the estimation of histologic grade of HSCC was 0.936 with sensitivity of 90.0% and specificity of 81.8%. Conclusion: The combination of SUVmean, ADCmean, and Ktrans derived from 18F-FDG PET/MRI can accurately predict the histologic grade of HSCC preoperatively. [ABSTRACT FROM AUTHOR]

Background: The histological differentiation grades of gastric cancer (GC) are closely related to treatment choices and prognostic evaluation. Radiomics from dual-energy spectral CT (DESCT) derived iodine-based material decomposition (IMD) images may have the potential to reflect histological grades. Methods: A total of 103 patients with pathologically proven GC (low-grade in 40 patients and high-grade in 63 patients) who underwent preoperative DESCT were enrolled in our study. Radiomic features were extracted from conventional polychromatic (CP) images and IMD images, respectively. Three radiomic predictive models (model-CP, model-IMD, and model-CP–IMD) based on solely CP selected features, IMD selected features and CP coupled with IMD selected features were constructed. The clinicopathological data of the enrolled patients were analyzed. Then, we built a combined model (model-Combine) developed with CP–IMD and clinical features. The performance of these models was evaluated and compared. Results: Model-CP–IMD achieved better AUC results than both model-CP and model-IMD in both cohorts. Model-Combine, which combined CP–IMD radiomic features, pT stage, and pN stage, yielded the highest AUC values of 0.910 and 0.912 in the training and testing cohorts, respectively. Model-CP–IMD and model-Combine outperformed model-CP according to decision curve analysis. Conclusion: DESCT-based radiomics models showed reliable diagnostic performance in predicting GC histologic differentiation grade. The radiomic features extracted from IMD images showed great promise in terms of enhancing diagnostic performance. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common malignant tumor in women. Some factors, including histological grade, vascular invasion, and metastasis, are known prognostic factors. Many studies have been performed to find more predictive factors such as urokinase plasminogen activator system markers. Here, we tried to evaluate the relationship between Urokinase-type plasminogen activator receptor expression and other histopathologic parameters. 62 malignant breast tumors were enrolled. UPAR immunohistochemistry staining was performed on paraffin blocks. We evaluated the relationship between UPAR expression and histopathologic factors, including tumor size, tumor type, histologic grade, lymph node status, lymphovascular and perineural invasions, and hormone receptors status (ER, PR, and HER2). The patient's mean age was 46.18±10.35 years. We found a positive relationship between UPAR expression and the presence of carcinoma insitu (P=0.027). A negative relationship was observed between UPAR expression and lymph node involvement (P=0.01), the number of involved lymph nodes (P=0.027), and also intensity and percentage of UPAR positivity in the case with lymph node involvement (P=0.005 and 0.029, respectively). UPAR expression is associated with lymph node metastasis which is one of the most important predictors of prognosis in breast cancer. So, it could be used as a favorable prognostic factor in breast cancer. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common malignant tumor in women. Some factors, including histological grade, vascular invasion, and metastasis, are known prognostic factors. Many studies have been performed to find more predictive factors such as urokinase plasminogen activator system markers. Here, we tried to evaluate the relationship between Urokinase-type plasminogen activator receptor expression and other histopathologic parameters. 62 malignant breast tumors were enrolled. UPAR immunohistochemistry staining was performed on paraffin blocks. We evaluated the relationship between UPAR expression and histopathologic factors, including tumor size, tumor type, histologic grade, lymph node status, lymphovascular and perineural invasions, and hormone receptors status (ER, PR, and HER2). The patient's mean age was 46.18±10.35 years. We found a positive relationship between UPAR expression and the presence of carcinoma insitu (P=0.027). A negative relationship was observed between UPAR expression and lymph node involvement (P=0.01), the number of involved lymph nodes (P=0.027), and also intensity and percentage of UPAR positivity in the case with lymph node involvement (P=0.005 and 0.029, respectively). UPAR expression is associated with lymph node metastasis which is one of the most important predictors of prognosis in breast cancer. So, it could be used as a favorable prognostic factor in breast cancer.

The chemoattractant protein chemerin is protective in experimental hepatocellular carcinoma (HCC), and high expression in HCC tissues of Asian patients was related to a favorable prognosis. Studies from Asia found reduced expression of chemerin in HCC compared to para-tumor tissues while our previous analysis observed the opposite. Aim of this study was to correlate chemerin expression in HCC tissues with disease severity of European patients Hepatocyte chemerin protein expression was assessed by immunohistochemistry in HCC tissue of 383 patients, and was low in 24%, moderate in 49% and high in 27%. High chemerin protein in the HCC tissues was related to the T stage, vessel invasion, histologic grade, Union for International Cancer Control (UICC) stage and tumor size. Chemokine-like receptor 1 (CMKLR1) is a functional chemerin receptor. CMKLR1 protein in hepatocytes was low expressed in HCC tissues of 36%, moderate in tissues of 32% and high in 32% of the HCCs. Tumor CMKLR1 was associated with the T stage, vessel invasion, histologic grade and UICC stage. Notably, sex-specific analysis revealed that associations of chemerin and CMKLR1 expression with HCC progression were significant in males but not in females. The tumor chemerin and CMKLR1 protein expression were not related to steatosis, inflammation and fibrosis grades. In summary, chemerin as well as CMKLR1 protein were related to disease severity of European HCC patients, and this was significant in males. This observation is in contrast to Asian patients where higher chemerin in the tumors was protective. Current analysis provides evidence for ethnicity and sex-related differences of tumor expressed chemerin and HCC severity.

Oral squamous cell carcinoma (OSCC) occasionally occurs in young patients and is likely to be distinct from OSCC in older patients. In this retrospective study, we described the clinicopathologic features and outcome of 150 OSCCs that were diagnosed in patients 40-year-old or younger. Most patients (63%) were non-smokers. The most common site of the primary tumor was oral tongue (n = 131, 87%), followed by gingiva (n = 9), buccal mucosa (n = 8) and lip (n = 2). The median patients' age at presentation was 34 (range: 16–40). Seven patients (5%) had Fanconi anemia with the gingiva being the most common location (4/7, 57%). All OSCCs were of keratinizing type. All cases tested for high-risk HPV (n = 34) were negative. On univariate analysis, high tumor budding was associated with decreased overall survival (OS) and distant metastasis free survival (DMFS), pattern of invasion correlated with OS and tumors with high stromal tumor infiltrating lymphocytes (sTIL) were associated with improved locoregional recurrence free survival (LRFS). Compared with patients 31 to 40-year-old, OSCC in the younger group was associated with significant less alcohol consumption (p = 0.011) and decreased DSS (p = 0.003) and DMFS (p = 0.023). On multivariate analysis, younger age (30 years or younger) was an independent prognostic factor for worse OS and DSS, whereas histologic grade was an independent prognostic factor for DSS. In summary, most OSCC in young patients occurred in non-smokers and did not occur in association with Fanconi anemia. Independent prognostic factors included age at presentation (30 years or younger) for OS and DSS, and histologic grade for DSS. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to determine the oncological outcomes of mixed-grade tumors by comparing them with pure low-grade and high-grade tumors. Methods: We retrospectively reviewed the medical records of patients with primary non-muscle-invasive bladder cancer. Patients were categorized into three groups according to the histological grade of their tumors: low-grade, mixed-grade, and high-grade. Clinicopathological characteristics and oncological outcomes, such as recurrence-free survival (RFS), progression-free survival (PFS), and cancer-specific survival (CSS), were compared between the three groups. Results: A total of 369 patients (190 low, 40 mixed, and 139 high-grade) were included in our study, with a mean follow-up of 55.94±41.73 months. Patients with mixed-grade tumors had lower rates of pT1 stage diseases than those with high-grade tumors (42.5% vs. 64.0%, respectively) and higher rates than those with low-grade tumors (14.7% vs. 42.5%, respectively) (p=0.001). There was no significant difference in RFS between low-, mixed-, and high-grade tumor patients (p=0.887). Patients with mixed-grade tumors had worse PFS and CSS outcomes than those with low-grade tumors (199.84±23.22 vs. 214.94±15.92 for PFS and 202.07±19.86 vs. 233.61±9.84 for CSS, respectively) and better PFS and CSS outcomes than those with highgrade tumors (199.84±23.22 vs. 163.28±16.18 for PFS and 202.07±19.86 vs. 180.81±15.89 for CSS, respectively), although these comparisons were not statistically significant. Conclusions: Patients with mixed-grade tumors had worse PFS and CSS outcomes than patients with low-grade tumors and better PFS and CSS outcomes than patients with high-grade tumors, although these comparisons were not statistically significant. Our results should be verified by future studies. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To develop and validate a radiomics model based on contrast-enhanced spectral mammography (CESM), and preoperatively discriminate low-grade (grade I/II) and high-grade (grade III) invasive breast cancer. METHOD: A total of 205 patients with CESM examination and pathologically confirmed invasive breast cancer were retrospectively enrolled. We randomly divided patients into two independent sets namely, training set (164 patients) and test set (41 patients) with a ratio of 8:2. Radiomics features were extracted from the low-energy and subtracted images. The least absolute shrinkage and selection operator (LASSO) logistic regression were established for feature selection, which were then utilized to construct three classification models namely, low energy, subtracted images and their combined model to discriminate high- and low-grade invasive breast cancer. Receiver operator characteristic (ROC) curves were used to confirm performance of three models in training set. The clinical usefulness was evaluated by using decision curve analysis (DCA). An independent test set was used to confirm the discriminatory power of the models. To test robustness of the result, we used 100 times LGOCV (leave group out cross validation) to validate three models. RESULTS: From initial radiomics feature pool, 17 and 11 features were selected for low-energy image and subtracted image, respectively. The combined model using 28 features showed the best performance for preoperatively evaluating the histologic grade of invasive breast cancer, with an area under the curve, AUC = 0.88, and 95%confidence interval [CI] 0.85 to 0.92 in the training set and AUC = 0.80 (95%CI 0.67 to 0.92) in the test set. The mean AUC of LGOCV is 0.82. CONCLUSIONS: CESM-based radiomics model is a non-invasive predictive tool that demonstrates good application prospects in preoperatively predicting histological grade of invasive breast cancer. [ABSTRACT FROM AUTHOR]

Major pathology guidelines often mandate stating the histologic grade as a component of the pathology report for various types of cancer. However, the prognostic value of histologic grade in head and neck squamous cell carcinoma (HNSCC) is controversial at best, and there is a need for more reliable prognostic histologic factors to better stratify and manage patients with HNSCC. In this study, we compared three relevant histopathologic features (histologic grade, worst pattern of invasion (WPOI), and tumor budding) in a large single-center retrospective cohort of early oral tongue squamous cell carcinoma (OTSCC) with tumor greatest dimension ≤ 4 cm. Only histologic grade predicted distant metastasis free survival (DMFS) on univariate analysis. Tumor budding was associated with nodal metastasis, overall survival (OS), regional recurrence-free survival (RRFS), and DMFS and was a significant predictor for nodal metastasis on the multivariable logistic regression model. WPOI 5 was associated with high frequency of nodal metastasis and shortened OS and was an independent adverse prognostic factor for OS on multivariate analysis using the Cox proportional hazards model. WPOI and tumor budding were prognostically more relevant than histologic grade. Consideration should be given to include WPOI and tumor budding in the pathology reporting of OTSCC. [ABSTRACT FROM AUTHOR]

Purpose: The large variation in histologic grading of invasive breast cancer (IBC) that has been reported likely influences tailoring adjuvant therapy. The role of grading in therapeutic decision-making in daily practice, was evaluated using the Dutch national guidelines for IBC-management. Methods: Synoptic reports of IBC resection-specimens, obtained between 2013 and 2016, were extracted from the nationwide Dutch Pathology Registry, and linked to treatment-data from the Netherlands Cancer Registry. The relevance of grading for adjuvant chemotherapy (aCT) was quantified by identifying patients for whom grade was the determinative factor. In addition, the relation between grade and aCT-administration was evaluated by multivariate logistic regression for patients with a guideline-aCT-indication. Results: 30,843 patients were included. Applying the guideline that was valid between 2013 and 2016, grade was the determinative factor for the aCT-indication in 7744 (25.1%) patients, a percentage that even increased according to the current guideline where grade would be decisive for aCT in 10,869 (35.2%) patients. Also in current practice, the indication for adjuvant endocrine therapy (aET) would be based on grade in 9173 (29.7%) patients. Finally, as patients with lower-grade tumors receive aCT significantly less often, grade was also decisive in tailoring aCT de-escalation. Conclusions: In the largest study published so far we illustrate the increasing importance of histologic grade in tailoring adjuvant systemic breast cancer therapy. Next to playing a key-role in aCT-indication and de-escalation, the role of grading has expanded to the indication for aET. Optimizing histologic grading by pathologists is urgently needed to diminish the risk of worse patient outcome due to non-optimal treatment. [ABSTRACT FROM AUTHOR]

• In the present study IASLC/ATS/ERS classification was useful to identify a high risk population of developing brain metastases in advanced lung adenocarcinoma. • The solid predominant histologic subtype consistently had a significantly higher probability of developing brain metastases even after adjusting by the histological grade and cofounding variables. • According to the histologic grade, moderately differentiated tumors had the highest risk of brain affection irrespective of the lung predominant adenocarcinoma subtype. • IASLC/ATS/ERS classification might suggest more aggressive clinical approaches and closer monitoring in patients with increased hazards for brain metastases development, integrating this classification for risk stratification. Brain metastases (BM) are frequent among lung cancer patients, affecting prognosis and quality of life. The International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS) and European Respiratory Society (ERS) lung adenocarcinoma (LADC) classification (IASLC/ATS/ERS) has prognostic impact in early-stage disease; however, its role in the advanced setting is not precise. This study aims to determine the correlation between the predominant histological subtype and the risk of developing brain metastases (BM) in locally advanced and metastatic (stages IIIB-IV) LADC. A total of 710 patients with LADC were treated at our institution from January 2010 to December 2017. After excluding patients with brain metastases at diagnoses (n = 151), they were categorized according to the IASLC/ATS/ERS LADC classification to estimate the risk of developing brain metastases. A competing risk analysis was employed, considering death a competing risk event. From 559 patients, the mean age was 59 ± 13.2 years, women (52.4 %), and clinical-stage IV (79.2 %). LADC subtypes distribution was lepidic (11.6 %), acinar (37.9 %), papillary (10.2 %), micropapillary (6.8 %), and solid (33.5 %). A total of 27.0 % of patients developed BM, 32.9 % died without brain affection, and 40.0 % did not progress. The predominantly solid subtype showed the greatest probability of all subtypes for developing BM [HR 4.0; 95 % CI (1.80−8.91), p = 0.0006], followed by micropapillary [HR1.11; 95 % CI (0.36−3.39), p = 0.85). The solid subtype, moderately differentiated tumors, age, and ECOG PS (>2) were associated with increased hazards in the multivariate analysis. According to the IASLC/ATS/ERS classification, the predominantly solid pattern was significantly associated with an increased risk of developing BM in patients with locally advanced and metastatic LADC. Its prognostic value might help explore novel clinical approaches, modify monitoring for earlier detection, prevent complications, and reduce morbidity. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate whether the IVIM parameters (D, D *, f) helps to determine the molecular subtypes and histological grades of breast cancer. Fifty-one patients with breast cancer were included in the study. All subjects were examined by 3 T Magnetic Resonance Imaging (MRI). Diffusion-weighted imaging (DWI) was undertaken with 16 b-values. IVIM parameters [D (true diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction)] were calculated. Histopathological reports were reviewed to histological grade, histological type, and immunohistochemistry. IVIM parameters of tumors with different histological grades and molecular subtypes were compared. D* and f were significantly different between molecular subtypes (p = 0.019, p = 0.03 respectively). D* and f were higher in the HER-2 group and lower in Triple negative (−) group (D*:36.8 × 10−3 ± 5.3 × 10−3 mm2/s, f:29.5%, D*:29.8 × 10−3 ± 5.6 × 10−3 mm2/s, f:21.5% respectively). There was a significant difference in D* and f between HER-2 and Triple (−) subgroups (p = 0,028, p = 0.024, respectively). D* was also significantly different between the HER-2 group and the Luminal group (p = 0,041). While histological grades increase, D and f values tend to decrease, and D* tends to increase. While the Ki-67 index increases, D* and f values tend to increase, and D tend to decrease. D* and f values measured with IVIM imaging were useful for assessing breast cancer molecular subtyping. IVIM imaging may be an alternative to breast biopsy for sub-typing of breast cancer with further research. [ABSTRACT FROM AUTHOR]

Background: Histologic grade assessment plays an important part in the clinical decision making and prognostic evaluation of squamous cell carcinoma (SCC) of the oral tongue and floor of mouth (FOM).Purpose: To assess the value of apparent diffusion coefficient (ADC)-based radiomics in discriminating between low- and high-grade SCC of the oral tongue and FOM.Material and Methods: We included data from 88 patients (training cohort: n = 59; testing cohort: n = 29) who underwent diffusion-weighted imaging with a 3.0-T magnetic resonance imaging scanner before treatment. A total of 526 radiomics features were extracted from ADC maps to construct a radiomics signature with least absolute shrinkage and selection operator logistic regression. Receiver operating characteristic curves and areas under the curve (AUCs) were used to evaluate the performance of radiomic signature.Results: Five features were selected to construct the radiomics signature for predicting histologic grade. The ADC-based radiomics signature performed well for discriminating between low- and high-grade tumors, with AUCs of 0.83 in both cohorts. Based on the cut-off value of the training cohort, the radiomics signature achieved accuracies of 0.78 and 0.79, sensitivities of 0.65 and 0.71, and specificities of 0.85 and 0.82 in the training and testing cohorts, respectively.Conclusion: ADC-based radiomics can be a useful and promising non-invasive method for predicting histologic grade of SCC of the oral tongue and FOM. [ABSTRACT FROM AUTHOR]

Background: Although pathologic tumor grade is a well‐established prognostic risk factor that impacts staging and treatment decisions across multiple cancer types, its role in head and neck squamous cell carcinoma (HNSCC) is less certain. Methods: HNSCC patients diagnosed from 2010 to 2015 and undergoing primary surgery in the National Cancer Data Base were identified. Propensity score matching and multivariable Cox regression were performed. Results: Among 27 041 HNSCC patients, 13 941 had oral cavity cancers (OCC). Intermediate‐grade (hazard ratio [HR] 1.16, 95% CI 1.07‐1.26, P <.001) and high‐grade (HR 1.38, 95% CI 1.26‐1.52, P <.001) tumors had worse survival than low‐grade tumors. This magnitude was comparable to other well‐established prognostic factors, including margin positivity, extranodal extension, and lymphovascular invasion. By contrast, there was no association between grade and survival in larynx/hypopharynx or HPV(−) oropharynx cancer. Conclusions: The prognostic impact of pathologic grade is highly variable across head and neck subsites and is the strongest among OCC patients. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: To evaluate the results of 18F-FDG PET/MRI in relation to the histopathologic subtypes and histologic grades of mass-forming primary intrahepatic neoplasms.Materials and Methods: We retrospectively evaluated 18F-FDG positron emission tomography/magnetic resonance imaging (PET/MRI) results for 39 patients with histopathologically confirmed primary hepatic neoplasms, 15 with mass-forming intrahepatic cholangiocarcinoma (ICC) and 24 with hepatocellular carcinoma (HCC). The apparent diffusion coefficient (ADC) and standardized uptake value (SUV) were analyzed in relation to the histopathologic diagnosis and histologic grade, including calculating the sensitivity and specificity of the imaging findings.Results: The median SUV of ICC (6.0 [interquartile range, 5-10]) was significantly higher than that of HCC (4.0 [2.62-6.50]) (p = 0.002). An area under the curve (AUC) of 0.79 (95% confidence interval 0.649-0.932) had a sensitivity of 86.7% and a specificity of 67% at the best cut-off SUV of 4.41 to differentiate between ICC and HCC. ADC values did not differ significantly between HCCs and ICCs (p = 0.283). Both SUV and ADC values differed significantly between low-grade (well- and moderately differentiated) and high-grade (poorly differentiated) HCCs. Combining ADC and SUV further improved differentiation of low- from high-grade HCCs to a significant level (0.929). The SUV did not differ significantly between ICC histologic grades (p = 0.280), while the ADC differed significantly only between well and poorly differentiated ICCs (p = 0.004).Conclusion: Assessing primary hepatic neoplasms with 18F-Fluorodeoxyglucose PET/MRI may help to predict tumor grade and differentiate between types of intrahepatic neoplasms. [ABSTRACT FROM AUTHOR]

Background: Preoperative grading of hepatocellular carcinoma (HCC) is an important factor associated with prognosis after liver resection. The promising prediction of the differentiation of HCC remains a challenge. The purpose of our study was to investigate the value of amide proton transfer (APT) imaging in predicting the histological grade of HCC, compared with the intravoxel incoherent motion (IVIM) imaging.Methods: From September 2018 to February 2020, 88 patients with HCC were enrolled and divided into four groups (G1, G2, G3, and G4) based on the histologic grades. Preoperative APT signal intensity (SI), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f ) of HCC were independently measured by two radiologists. The averaged values of those parameters were compared using an analysis of variance. The Spearman rank analysis was used to compare the correlation between those imaging parameters and the histological grades. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance.Results: There were significant differences in APT SI, ADC, D, and f among the four grades of HCC (all P < 0.001). A moderate to good relationship was found between APT SI and the histologic grade of HCC (r = 0.679, P < 0.001). APT SI had an area under the ROC curve (AUC) of 0.890 (95% CI: 0.805–0.947) for differentiating low- from high-grade HCC, and the corresponding sensitivity and specificity were 85.71% and 82.05%, respectively. Comparison of ROC curves demonstrated that the AUC of APT SI was significantly higher than those of IVIM-derived parameter (Z = 2.603, P = 0.0092; Z = 2.099, P = 0.0358; Z = 4.023, P = 0.0001; Z = 2.435, P = 0.0149, compared with ADC, D, D*, and f , respectively). Moreover, the combination of both techniques further improved the diagnostic performance, with an AUC of 0.929 (95% CI: 0.854–0.973).Conclusion: APT imaging may be a potential noninvasive biomarker for the prediction of histologic grading of HCC and complements IVIM imaging for the more accurate and comprehensive characterization of HCC.

Abstract Hepatocellular carcinoma (HCC) is one of the most common human solid malignancies worldwide. Although the MRI is the technique that is best adapted to characterize HCC, there is not an agreement regarding the study protocol and even what the role of Diffusion-weighted imaging (DWI). The possibility that imaging study can correlate to histologic grade to selecting the therapeutic strategy would be valuable in helping to direct the proper management of HCC. Apparent Diffusion Coefficient (ADC) and IVIM-derived perfusion fraction (fp) and tissue diffusivity (Dt) values of HCC showed significantly better diagnostic performance in differentiating high-grade HCC from low-grade HCC, and significant correlation was observed between ADC, fp, Dt and histological grade.

Background: Preoperative grading of hepatocellular carcinoma (HCC) is an important factor associated with prognosis after liver resection. The promising prediction of the differentiation of HCC remains a challenge. The purpose of our study was to investigate the value of amide proton transfer (APT) imaging in predicting the histological grade of HCC, compared with the intravoxel incoherent motion (IVIM) imaging. Methods: From September 2018 to February 2020, 88 patients with HCC were enrolled and divided into four groups (G1, G2, G3, and G4) based on the histologic grades. Preoperative APT signal intensity (SI), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) of HCC were independently measured by two radiologists. The averaged values of those parameters were compared using an analysis of variance. The Spearman rank analysis was used to compare the correlation between those imaging parameters and the histological grades. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance. Results: There were significant differences in APT SI, ADC, D, and f among the four grades of HCC (all P < 0.001). A moderate to good relationship was found between APT SI and the histologic grade of HCC (r = 0.679, P < 0.001). APT SI had an area under the ROC curve (AUC) of 0.890 (95% CI: 0.805–0.947) for differentiating low- from high-grade HCC, and the corresponding sensitivity and specificity were 85.71% and 82.05%, respectively. Comparison of ROC curves demonstrated that the AUC of APT SI was significantly higher than those of IVIM-derived parameter (Z = 2.603, P = 0.0092; Z = 2.099, P = 0.0358; Z = 4.023, P = 0.0001; Z = 2.435, P = 0.0149, compared with ADC, D, D*, and f , respectively). Moreover, the combination of both techniques further improved the diagnostic performance, with an AUC of 0.929 (95% CI: 0.854–0.973). Conclusion: APT imaging may be a potential noninvasive biomarker for the prediction of histologic grading of HCC and complements IVIM imaging for the more accurate and comprehensive characterization of HCC. [ABSTRACT FROM AUTHOR]

Background: Diffusion-weighted magnetic resonance imaging (DW-MRI) with apparent diffusion coefficient (ADC) measurement provides additional information about tumor microstructure with potential relevance for staging and predicting aggressive disease in patients with endometrial cancer (EC).Purpose: To determine whether ADC values in EC diverge according to the tumor's histologic grade and myometrial invasion depth.Material and Methods: A sample of 48 pathologically confirmed cases of EC were reviewed retrospectively. The sample was distributed as follows: G1 (n = 9); G2 (n = 18); G3 (n = 21); with myometrial invasion <50% (n = 31); and with myometrial invasion ≥50% (n = 17). DW images were performed at 3.0T with b factors of 0-1000/mm2. The region of interest (ROI) was defined within the tumor with T1-weighted and T2-weighted imaging and copied manually to an ADC map. The tumor's grade and myometrial invasion's depth were determined by postoperative histopathological tests.Results: The means of ADCmin and ADCmean values were significantly lower for patients with G2 and G3 endometrial tumors than G1. The same tendency was observed in myometrial invasion, as both ADCmin and ADCmean values were lower for patients with deep than for those with superficial myometrial invasion. The cut-off values of the ADCmin and ADCmean that predicted high-grade tumors were 0.69 × 10-3 mm2/s and 0.82 × 10-3 mm2/s, respectively, while those for myometrial infiltration were 0.70 × 10-3 mm2/s (ADCmin) and 0.88 × 10-3 mm2/s (ADCmean).Conclusion: ADCmin and ADCmean values correlated with histologic tumor grade and myometrial invasion depth; therefore, it is suggested that ADC on MRI may be a useful indicator to predict malignancy of ECs. [ABSTRACT FROM AUTHOR]

Aim: Gastric carcinoma is the fourth most common carcinoma worldwide. The relationships established between the tumor morphology and the prognosis have not been very effective until recent times. Poorly Differentiated Clusters (PDCs); are structures those can be easily identified in H&E sections. A new grading system based on PDC count has been studied in colorectal carcinoma; and found to be associated with prognosis. We have aimed to investigate this concept in gastric carcinoma. Material and Methods: Our study included 80 cases, consisting of 16 females and 64 males having gastric carcinoma with intestinal morphology. For each case; conventional grade, PDC grade and prognostic parameters to be applied in the study were determined, and statistically compared. Results: Significant discrepancy was found between the two grading systems. PDC tumor grades were statistically related to; median metastatic lymph node counts, metastatic lymph node ratios, lymph node stages (pN) and the presence of perineural invasion. Conclusion: In stomach carcinoma; PDC grading system was found to be related to a significant part of the expected parameters and may have a prognostic value. [ABSTRACT FROM AUTHOR]

Objective: Histologic grade and Ki-67 proliferation status are important clinical indictors for breast cancer prognosis and treatment. The purpose of this study is to improve prediction accuracy of these clinical indicators based on tumor radiomic analysis. Methods: We jointly predicted Ki-67 and tumor grade with a multitask learning framework by separately utilizing radiomics from tumor MRI series. Additionally, we showed how multitask learning models (MTLs) could be extended to combined radiomics from the MRI series for a better prediction based on the assumption that features from different sources of images share common patterns while providing complementary information. Tumor radiomic analysis was performed with morphological, statistical and textural features extracted on the DWI and dynamic contrast-enhanced MRI (DCE-MRI) series of the precontrast and subtraction images, respectively. Results: Joint prediction of Ki-67 status and tumor grade on MR images using the MTL achieved performance improvements over that of single-task-based predictive models. Similarly, for the prediction tasks of Ki-67 and tumor grade, the MTL for combined precontrast and apparent diffusion coefficient (ADC) images achieved AUCs of 0.811 and 0.816, which were significantly better than that of the single-task- based model with p values of 0.005 and 0.017, respectively. Conclusion: Mapping MRI radiomics to two related clinical indicators improves prediction performance for both Ki-67 expression level and tumor grade. Significance: Joint prediction of indicators by multitask learning that combines correlations of MRI radiomics is important for optimal tumor therapy and treatment because clinical decisions are made by integrating multiple clinical indicators. [ABSTRACT FROM AUTHOR]

Background: The aim of this retrospective analysis is to understand the natural history of myxofibrosarcoma (MFS), in particular whether the prognosis can be influenced by histologic grade. Methods: We reviewed 229 adult patients with primary MFS of the limbs. We analyzed disease-specific survival (overall survival [OS]) and local recurrence (LR). Results: Median age was 70 years (range, 19–92). Sixteen (7.0%) were grade 1, 38 (16.6%) grade 2, and 175 (76.4%) grade 3. A worse OS was found in grade 3 MFS (73.1%) than in grade 2 and 1 MFS (91.9 and 100%, respectively) at 5 years (p = 0.031). Locally recurred MFS had a worse OS (p = 0.018). A better LR-free rate (100% at 5 years) was observed in grade 1 MFS; however, a similar rate was observed between grade 2 and 3 tumors (77.1 and 80.0% at 5 years, respectively, p = 0.412). Conclusions: Grade 3 MFS has the worst prognosis. Grade 1 MFS have the lowest risk of LR. These data could help identify a high-risk patient group, thus selecting a more careful follow-up for higher-risk patients. Since MFS mostly affects the elderly population, it might be useful to reserve adjuvant treatments (radiotherapy and chemotherapy) to higher-risk patients. [ABSTRACT FROM AUTHOR]

Background: In the molecular era, the relevance of tumor grade for prognostication of IDH1/2‐wildtype (WT) gliomas has been debated. It has been suggested that histologic grade II and III astrocytomas with molecular features of glioblastoma, IDH1/2‐WT have a similar prognosis to glioblastoma and should be considered for the same clinical trials. Methods: We integrated prospective clinical sequencing from 564 patients with IDH1/2‐WT gliomas (26 grade II, 71 grade III and 467 grade IV) with clinical and radiographic data to assess associations between molecular features, grade and outcome. Results: Compared to histologic grade IV IDH1/2‐WT astrocytomas, histologic grade II astrocytomas harbor fewer chromosome 7/10 alterations (P = 0.04), EGFR amplifications (P = 0.022) and alterations in cell‐cycle effectors (P = 1.9e‐11), but a similar frequency of TERT promoter mutations. In contrast, there is no difference in the frequency of these canonical molecular features in histologic grade III vs. IV IDH1/2‐WT disease. Progression‐free (PFS) and overall survival (OS) for histologic grade II tumors were significantly longer than grade III tumors (P = 0.02 and P = 0.008, respectively), whereas there was no difference in PFS and OS for histologic grade III compared to grade IV tumors. Median PFS for histologic grade II, III and IV tumors was 19, 11 and 9 months, respectively. Median OS for the same tumors was 44, 23 and 23 months, respectively. In histologic grade II and III IDH1/2 WT tumors, gliomatosis is associated with the absence of cell‐cycle alterations (P = 0.008) and enriched in grade II features (P = 0.1) and alterations in the PI3K‐AKT pathway (P = 0.09). Conclusions: Grade II histology has genotypic and phenotypic associations with prognostic implications in IDH1/2‐WT astrocytomas. [ABSTRACT FROM AUTHOR]

Accurate, consistent and reproducible grading by pathologists is of key‐importance for identification of individual patients with invasive breast cancer (IBC) that will or will not benefit from adjuvant systemic treatment. We studied the laboratory‐specific grading variation using nationwide real‐life data to create insight and awareness in grading variation. Synoptic pathology reports of all IBC resection‐specimens, obtained between 2013 and 2016, were retrieved from the nationwide Dutch Pathology Registry (PALGA). Absolute differences in laboratory‐proportions of Grades I–III were compared to the national reference. Multivariable logistic regression provided laboratory‐specific odds ratios (ORs) for high‐ vs. low‐grade IBC. 33,792 IBC pathology reports of 33,043 patients from 39 laboratories were included, of which 28.1% were reported as Grade I (range between laboratories 16.3–43.3%), 47.6% as Grade II (38.4–57.8%), and 24.3% as Grade III (15.5–34.3%). Based on national guidelines, the indication for adjuvant chemotherapy was dependent on histologic grade in 29.9% of patients. After case‐mix correction, 20 laboratories (51.3%) showed a significantly deviant OR. Significant grading differences were also observed among pathologists within laboratories. In this cohort of 33,043 breast cancer patients, we observed substantial inter‐ and intra‐laboratory variation in histologic grading. It can be anticipated that this has influenced outcome including exposure to unnecessary toxicity, since choice of adjuvant chemotherapy was dependent on grade in nearly a third of patients. Better standardization and training seems warranted. What's new? Histologic grade serves a critical prognostic role in invasive breast cancer (IBC) and is used to guide therapeutic decisions. Evidence indicates, however, that IBC grading varies considerably. Here, grading variation in clinical practice was evaluated using real‐life data from laboratories in the nationwide Dutch Pathology Registry. Laboratories varied in IBC grade I, II, and III reporting. Among grading components, nuclear polymorphism showed the greatest difference between laboratories. Within laboratories, one‐third of pathologists deviated significantly from national proportions for IBC grade I. Despite deployment of uniform guidelines across laboratories, IBC histologic grading is not necessarily performed in a consistent manner. [ABSTRACT FROM AUTHOR]

Histological grade and depth of invasion are among the best outcome pathological predictors in penile cancer. The TNM system is based on a combination of both for some stages. It is assumed that high-grade and deep tumors carry the worst prognosis, and the opposite occurs with superficial and low-grade neoplasms. However, there is no systematic evaluation of the phenomenon. We studied 147 patients from the Hospital de Oncologia - Instituto Mexicano del Seguro Social (period 2000 to 2013). They were treated by total or partial penectomies. Lymph node involvement was evaluated by bilateral inguinal node dissection (126 cases) or ultrasonography (21 cases). Tumor thickness was measured in mm from tumor surface to deepest invasion point, using a cut-point for superficial (≤10 mm) vs deep (>10 mm) tumors. Histological grade was from 1 to 3 according to WHO and AFIP criteria and considering G1 and G2 as low-grade and G3 as high-grade. Average age was 62 (26-98) years old. Tumor thickness mean was 15 mm (2-30 mm). G1, G2 and G3 tumors corresponded to 19 (13 %), 48 (33 %), and 80 (54 %) cases, respectively. Follow-up ranged from 10 to 82 months (median: 57 months). Fifty-three (36 %) patients died of disease. There was an overall correlation of tumor thickness and grade in most of the cases. Low-grade tumors were encountered in 92 % (12/13 cases) of superficial tumors. Deep tumors showed high-grade in 75 % of cases (73/97 cases). Superficial tumors with low histological grade had negative inguinal nodes and no mortality whereas deep tumors showing high histological grade were associated with high metastatic risk to lymph nodes (62/73 cases) and mortality (52/73 cases). Out of 24 deep tumors with low histological grade, seven had nodal spread (29 %) but only one died of disease. No outcome difference was found in HPV associated vs HPV independent tumors. Tumor thickness and grade are important synergistic and predictive pathological factors in relation to prognosis., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: To compare the diagnostic value of apparent diffusion coefficient (ADC) and intravoxel incoherent motion metrics in discriminating histologic grades of hepatocellular carcinoma (HCC) in patients with hepatitis B virus (HBV) infection. Methods: 117 chronic HBV patients with 120 pathologically confirmed HCCs after surgical resection or liver transplantation were enrolled in this retrospective study. Diffusion-weighted imaging was performed using eleven b values (0–1500 s/mm2) and two b values (0, 800 s/mm2) successively on a 3.0 T system. ADC0, 800, ADCtotal, diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were calculated. The parameters of three histologically differentiated subtypes were investigated using Kruskal–Wallis test, Spearman rank correlation, and receiver-operating characteristic analysis. Interobserver agreement was assessed using the intraclass correlation coefficient. Results: There was excellent agreement for ADCtotal/D/f, good agreement for ADC0,800, and moderate agreement for D*. ADCtotal, ADC0, 800,D, and f were significantly different for well, moderately, and poorly differentiated HCCs (P < 0.001), and they were all inversely correlated with histologic grades: r = − 0.633, − 0.394, − 0.435, and − 0.358, respectively (P < 0.001). ADCtotal demonstrated higher performance than ADC0,800 in diagnosing both well and poorly differentiated HCCs (P < 0.001 and P = 0.04, respectively). ADCtotal showed higher performance than D and f in diagnosing well differentiated HCCs (P < 0.001) and similar performance in diagnosing poorly differentiated HCCs (P = 0.06 and 0.13, respectively). Conclusions: ADCtotal showed better diagnostic performance than ADC0,800, D, and f to discriminate histologic grades of HCC. [ABSTRACT FROM AUTHOR]

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