Pathological Grade Research Articles

Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors

ObjectivesThe objective is to develop and validate intratumoral and peritumoral ultrasomics models utilizing endoscopic ultrasonography (EUS) to predict pathological grading in pancreatic neuroendocrine tumors (PNETs).MethodsEighty-one patients, including 51 with grade 1 PNETs and 30 with grade 2/3 PNETs, were included in this retrospective study after confirmation through pathological examination. The patients were randomly allocated to the training or test group in a 6:4 ratio. Univariate and multivariate logistic regression were used for screening clinical and ultrasonic characteristics. Ultrasomics is ultrasound-based radiomics. Ultrasomics features were extracted from both the intratumoral and peritumoral regions of conventional EUS images. Subsequently, the dimensionality of these radiomics features was reduced using the least absolute shrinkage and selection operator (LASSO) algorithm. A machine learning algorithm, namely multilayer perception (MLP), was employed to construct prediction models using only the nonzero coefficient features and retained clinical features, respectively.ResultsOne hundred seven ultrasomics features based on EUS were extracted, and only features with nonzero coefficients were ultimately retained. Among all the models, the combined ultrasomics model achieved the greatest performance, with an AUC of 0.858 (95% CI, 0.7512 - 0.9642) in the training group and 0.842 (95% CI, 0.7061 - 0.9785) in the test group. A calibration curve and a decision curve analysis (DCA) also demonstrated its accuracy and utility.ConclusionsThe integrated model using EUS ultrasomics features from intratumoral and peritumoral tumors accurately predicts PNETs' pathological grades pre-surgery, aiding personalized treatment planning.Trial registrationChiCTR2400091906.

Value of [18F]AlF-NOTA-FAPI-04 PET/CT for predicting pathological response and survival in patients with locally advanced pancreatic ductal adenocarcinoma receiving neoadjuvant chemotherapy.

This study aimed to evaluate the predictive value of [18F]AlF-NOTA-FAPI-04 PET/CT for pathological response to neoadjuvant chemotherapy (NCT) and prognosis in patients with locally advanced pancreatic ductal adenocarcinoma (LAPDAC). This study included 34 patients with histopathologically and radiologically confirmed LAPDAC who received [18F]AlF-NOTA-FAPI-04 PET/CT scans before NCT. After 4-6 cycles of NCT, these patients underwent radical resection. Pathological response to NCT was assessed by pathological tumor regression grades (TRG) based on the Evans system. PET/CT parameters were evaluated for their association with TRG, recurrence-free survival (RFS) and overall survival (OS) after NCT, including the maximum standardized uptake value (SUVmax), FAPI-avid tumor volume (FTV), total lesion FAP expression (TLF) of primary tumor, total FAPI-avid pancreatic volume (FPV) and total pancreatic FAP expression (TPF) of total pancreas. Of 34 patients with LAPDAC, 14 patients had a pathologic good response (PGR, Evans III-IV), and 20 patients had a pathologic poor response (PPR, Evans I-II). Both the primary tumor SUVmax, FTV and TLF, and total pancreas FPV and TPF in the PGR groups were significantly lower than those in the PPR groups. Furthermore, SUVmax and TLF were higher in poorly differentiated LAPDAC than in well-moderately differentiated neoplasms. The FTV, TLF, FPV and TPF were closely associated with RFS and OS. On multivariate analysis, patients with FTV > 54.21 and TLF > 290.21 had a worse RFS and OS, respectively (HR = 3.24, P = 0.014 and HR = 3.35, P = 0.019) and OS (HR = 7.35, P = 0.002 and HR = 7.09, P = 0.004) in LAPDAC after NCT. The parameters of [18F]AlF-NOTA-FAPI-04 PET/CT had the excellent performance for predicting pathologic TRG after NCT in LAPDAC. FTV and TLF were independent postoperative prognostic factors for RFS and OS for LAPDAC.

Development and validation of nomograms for predicting pentafecta outcomes before and after robot-assisted radical prostatectomy: a retrospective study

Prostate cancer (PCa) is one of the most common cancers among men worldwide, and robot-assisted radical prostatectomy (RARP) is a widely used treatment for localized PCa. Achieving pentafecta outcomes, which include continence, potency, cancer control, free surgical margins, and no major complications, is a critical measure of surgical success and long-term prognosis. However, predicting these outcomes remains challenging. In this retrospective, single-center study, we analyzed data from 1,752 patients who underwent RARP for localized prostate adenocarcinoma between August 2009 and April 2023. The pentafecta outcome was achieved in 290 patients (16.6%). Multivariate analysis revealed that bilateral nerve sparing significantly increased the likelihood of achieving the pentafecta outcome (odds ratio 10.36, 95% CI: 5.75–18.66; p < 0.001). Preoperative potency and bilateral nerve sparing were also identified as key predictors. Nomograms were developed using preoperative and postoperative variables, including age, PSA level, biopsy Gleason score, clinical stage, pathological tumor stage, tumor grade, nerve sparing, and preoperative potency. Internal validation of the nomograms was performed using bootstrapping methods, demonstrating robust predictive performance. These nomograms provide valuable tools for personalized surgical planning and patient counseling and may be applicable to broader populations, given the inclusion of universally recognized predictive factors and rigorous validation. This study presents the development and validation of nomograms to predict pentafecta outcomes before and after RARP. These nomograms provide valuable tools for clinicians to estimate the likelihood of achieving postoperative pentafecta outcomes. Incorporating these nomograms into clinical practice may improve patient counseling and shared decision-making.

Area of Residual Tumor Measurement After Preoperative Chemotherapy as an Objective and Quantitative Method for Predicting the Prognosis of Gastric Cancer: A Single-Center Retrospective Study.

Pathological regression grade after chemotherapy evaluated by surgically resected specimens is closely related with prognosis. Since usefulness of measuring the area of the residual tumor (ART) has been reported, this study aimed to evaluate the utility of ART in predicting the prognosis of patients with gastric cancer (GC) who received preoperative chemotherapy. This single-center retrospective study examined the relationship between ART and survival outcomes. We included 92 patients who underwent preoperative chemotherapy followed by radical surgery for GC. Digital images were used to measure the ART in the largest pathological slice of each patient's surgical tumor specimen. We simply subclassified the patients as either ART-0 (<0.1mm2 or carcinoma in situ) or non-ART-0 to compare the prognoses. Significant differences were noted in overall survival and recurrence-free survival (RFS) between ART-0 (n=19) and non-ART-0 (n=73). The survival curves were similar to those of major pathological response (MPR) (n=24) or non-MPR (n=68), which are commonly used as surrogate endpoint presently. Multivariate analysis revealed ART and ypN independent prognostic factors for RFS. Survival curves stratified using ART and ypN to indicate risk grades (low-, moderate-, or high-) were not significantly different from those stratified using the other three existing pathological regression grade systems and ypN. ART-based pathological assessment is a simple and useful method for predicting the prognosis in patients with GC who underwent radical surgery after chemotherapy.

Spatial Distribution of Tumor Cells in Clear Cell Renal Cell Carcinoma Is Associated with Metastasis and a Matrisome Gene Expression Signature

Background/Objectives: Predicting the behavior of clear cell renal cell carcinoma (ccRCC) is challenging using standard-of-care histopathologic examination. Indeed, pathologic RCC tumor grading, based on nuclear morphology, performs poorly in predicting outcomes of patients with International Society of Urological Pathology/World Health Organization grade 2 and 3 tumors, which account for most ccRCCs. Methods: We applied spatial point process modeling of H&amp;E-stained images of patients with grade 2 and grade 3 ccRCCs (n = 72) to find optimum separation into two groups. Results: One group was associated with greater spatial randomness and clinical metastasis (p &lt; 0.01). Notably, spatial analysis outperformed standard pathologic grading in predicting clinical metastasis. Moreover, cell-to-cell interaction distances in the metastasis-associated group were significantly greater than those in the other patient group and were also greater than expected by the random distribution of cells. Differential gene expression between the two spatially defined groups of patients revealed a matrisome signature, consistent with the extracellular matrix’s crucial role in tumor invasion. The top differentially expressed genes (with a fold change &gt; 3) stratified a larger, multi-institutional cohort of 352 ccRCC patients from The Cancer Genome Atlas into groups with significant differences in survival and TNM disease stage. Conclusions: Our results suggest that the spatial distribution of ccRCC tumor cells can be extracted from H&amp;E-stained images and that it is associated with metastasis and with extracellular matrix genes that are presumably driving these tumors’ aggressive behavior.

Impact of ISUP grade group on cancer-specific mortality in radical prostatectomy-treated prostate cancer patients with organ-confined disease

Introduction: We aimed to test the impact of International Society of Urological Pathology (ISUP) grade group (GG) on cancer-specific mortality (CSM) in organ-confined (pT2) prostate cancer (PCa) at radical prostatectomy (RP). Methods: RP organ-confined prostate cancer (PCa) patients were identified (Surveillance, Epidemiology, and End Results 2004−2015). Cancer-specific survival (CSS) rates were tested in Kaplan-Meier plots and multivariable Cox regression (MCR) models according to GG: 1–3 vs. 4 vs. 5. Sensitivity analyses addressed GG4 and GG5 patients with available primary and secondary Gleason score (GS). Results: Overall, 61 172 patients with RP organ-confined PCa were identified. Of these, 57 715 (94.4%), 2036 (3.3%) and 1421 (2.3%) harbored GG1–3, 4, and 5, respectively. In Kaplan-Meier analyses, seven-years’ CSS estimates were 99.6 vs. 98.2 vs. 93.8% for GG1–3 vs. 4 vs. 5, respectively (p&lt;0.001). In MCR models, GG4 (hazard ratio [HR] 2.72, p&lt;0.001) and 5 (HR 9.95, p&lt;0.001) independently predicted higher CSM, relative to GG1–3. Furthermore, GG5 also independently predicted higher CSM (HR 3.72, p&lt;0.001) vs. GG4. In sensitivity analyses, 1.2, 1.6, and 2.4 CSM events per 1000 person-years of followup were respectively recorded for GS 4+4, 3+5, and 5+3 patients. Conversely, 4.8 vs. 5.3 CSM events per 1000 person-years of followup were respectively recorded for GS 4+5 vs. 5+4/5+5 patients. Conclusions: In organ-confined PCa, at RP, a small proportion of patients harbor GG4–5. These patients exhibit higher CSM than their GG1–3 counterparts. Moreover, detectable mortality rate differences indicate a dose-response effect according to primary and secondary GS. This phenomenon applies in both GG4 and GG5, as well as between GG4 and GG5.

Prospective validation study of a combined urine and plasma test for predicting high-grade prostate cancer in biopsy naïve men.

Early and accurate diagnosis of prostate cancer (PC) is crucial for effective treatment. Diagnosing clinically insignificant cancers can lead to overdiagnosis and overtreatment, highlighting the importance of accurately selecting patients for further evaluation based on improved risk prediction tools. Novel biomarkers offer promise for enhancing this diagnostic process. In this study, we aimed to externally validate a previously developed urine and plasma biomarker test in a biopsy-naïve population. Urine and blood samples were prospectively collected from 362 biopsy-naïve men with suspected PC before they underwent transrectal prostate biopsies. The expression levels of a 10-gene mRNA panel were quantified using reverse transcription/quantitative polymerase chain reaction of both urine and plasma. These gene expression levels, combined with clinical features and plasma prostate-specific antigen (PSA) levels, were used to predict the presence of International Society of Urological Pathology grade group ≥ 2 PC. Complete data were available for 314 patients. The sensitivity and specificity of the biomarker test were 87% (95% CI: 79-93%) and 42% (95% CI: 36-49%), respectively. The area under the curve was 0.76 (95% CI: 0.7-0.82) for the biomarker test probability and 0.65 (95% CI: 0.59-0.72) for PSA (p = 0.02). The test's negative predictive value was 89% (CI: 81-94%). This study did not replicate the previously reported high accuracy of the biomarker test, highlighting the need for further refinement and robust external validation to ensure reliable performance across diverse patient populations.

Survival and prognostic factors among different types of liposarcomas based on SEER database

The aim of this study is to elucidate the disparities in survival and risk factors among different subtypes of liposarcoma, through analysis of epidemiological and prognostic data. The study cohort consisted of 12,822 patients diagnosed with liposarcoma in the United States between 2000 and 2021, whose data were retrieved from the Surveillance, Epidemiology, and End Results (SEER) program. The prognosis for different subtypes of liposarcoma and the associated factors such as age, tumor stage, intervention, gender, tumor grade, location, size, chemotherapy and radiotherapy, were retrieved from the database. Well-differentiated liposarcoma demonstrated the most favorable prognosis, with 5-year and 10-year survival rates of 82% and 68%, respectively, followed by myxoid liposarcoma, pleomorphic liposarcoma and dedifferentiated liposarcoma, which exhibited the poorest prognosis. Advanced age, higher tumor stage, and the absence of surgical intervention were associated with inferior survival outcomes across all subtypes. Male gender, higher pathological grade, and primary tumor sites outside the extremities were identified as risk factors for the prognosis of subtypes other than pleomorphic liposarcoma. Larger tumor size was an indicator of a worse prognosis in subtypes other than well-differentiated liposarcoma. Chemotherapy was a risk factor for the prognosis of well-differentiated and myxoid liposarcomas but had no significant correlation with the prognosis of pleomorphic and dedifferentiated liposarcomas. Radiotherapy served as a protective factor for the prognosis of subtypes other than well-differentiated liposarcoma. Survival and prognostic factors vary among the major subtypes of liposarcoma, necessitating individualized analysis for each subtype. Poorer outcomes can be anticipated in the dedifferentiated and pleomorphic subtypes, while well-differentiated and myxoid liposarcomas exhibit relatively favorable prognoses.

Silencing GRHL3 promotes multiple organ distant metastasis of lung squamous cell carcinoma cells by enhancing SOX2 stability via SIRT1.

Aberrant expression of grainyhead-like transcription factor 3 (GRHL3) has been extensively reported in the development and progression of several squamous cell carcinomas, such as cutaneous, head and neck, and esophageal squamous cell carcinoma. However, the clinical significance and biological roles of GRHL3 in lung squamous cell (LUSC) carcinoma are largely unclear. Herein, we report that GRHL3 was significantly upregulated in lung squamous epithelium of LUSC tissues, bronchiole, and bronchus. Moreover, expression levels of GRHL3 were decreased with the advance of pathological grade, and low GRHL3 level presented poor overall survival and short progression-free and distant metastasis-free survival in LUSC patients but had no prognostic significance in LUAD patients. Functional experiments in vivo showed that downregulating GRHL3 promoted not only lung colonization and growth but also multiple organ distant metastasis of LUSC cells, including bone, brain, and liver. Moreover, silencing GRHL3 promoted anoikis resistance and cancer stem cell (CSCs) characteristics of LUSC cells in vitro. Mechanistically, silencing GRHL3 stabilized SOX2 via SIRT1-mediated decreasing acetylation and subsequent ubiquitination-dependent degradation in LUSC cells. Thus, in-depth understanding of the underlying mechanism of GRHL3 in the progression of LUSC will facilitate the development of prognostic biomarker and therapeutic avenues against LUSC, which will present favorable prospects in improving outcomes of LUSC patients. © 2025 The Pathological Society of Great Britain and Ireland.

Comparative analysis of imaging and pathological features in diagnosis of endometrial carcinosarcoma based on multimodal MRI.

This case report aims to present a rare case of endometrial carcinosarcoma, a highly malignant tumor with a poor prognosis. The primary objective is to describe this unique case's clinical presentation, multimodal magnetic resonance imaging (MRI) features, typical histopathological characteristics and surgical treatment. A detailed analysis of the patient's medical history, preoperative imaging evaluation, and treatment approach was conducted. This case report includes high-resolution images and figures, showcasing MRI scans, surgical treatment, and histopathology slides related to the case. The case report outlines imaging findings of a rare case of endometrial carcinosarcoma. Multimodal imaging such as T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) and multi-b-value diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and dynamic contrast-enhanced (DCE) scanning could accurately identify the histopathological features of the case. Surgical resection is the best treatment, and preoperative imaging evaluation should be particularly important. This case report highlights endometrial carcinosarcoma's rarity and diagnostic challenges. Multimodal MRI has significant value in diagnosing endometrial carcinosarcoma. This technology not only improves the sensitivity, specificity, and accuracy of diagnosis, but also helps to more accurately evaluate the staging and grading of tumors. By comparing imaging features and pathological results, studies have found that multimodal MRI can clearly show the anatomical structure, pathological nature, and extent of the tumor, with a high degree of consistency with the pathological diagnosis. In particular, when differentiating endometrial carcinosarcoma from low-risk endometrial cancer, multimodal MRI combined with serum carbohydrate antigen 125 (CA125) and E-box binding zinc finger protein 1 (ZEB1) detection can further improve the sensitivity and specificity of differential diagnosis. In addition, research has found that the ADC value of the tumor tissue in different pathological grades is related to the multimodal MRI, which helps to better understand the biological behavior and prognosis of the tumor. In summary, multimodal MRI is an effective diagnostic tool that can provide important evidence for the precise diagnosis and treatment of endometrial carcinosarcoma.

The correlation histopathological and conventional/advanced MRI techniques in glial tumors.

We aimed to elucidate the histopathological pre-diagnosis of cranial gliomas with magnetic resonance imaging (MRI) techniques in gliomas. A total of 82 glioma patients were enrolled to our study. Pre-operative conventional MRI images (non-contrast T1/T2/flair/contrast-enhanced T1) and advanced MRI images (DAG and ADC mapping, MRI spectroscopy and perfusion MRI [PMRI]) were analyzed. Conventional MRI alone is useful in radiological pre-evaluation in low-grade glioma in 54.8% and 86.3% in high-grade glioma. Additional advanced MRI techniques were beneficial in comparing low-grade gliomas in 98% and 83.9% in high-grade glioma. On ROC analysis, ADC cutoff value 0.905 mm2/s (p = 0.001), rCBV cutoff value 1.77 (p = 0.001), Cho/NAA cut-off value 2.20 (p = 0.001), and Cho/Cr cutoff value 2.01 (p = 0.001) were achieved. Significant results were obtained when ADC, Cho/NAA, and Cho/Cr were analyzed into four histopathologically grade groups besides (p = 0.001). NAA/Cr values were not significant in pathological grading. rCBV measurements were statistically significant between Grades I and IV and between II and IV. Using additional advanced MRI techniques such as PMRI, magnetic resonance spectroscopy, and DWI with conventional MRI could enhance the accuracy of histopathological grading in cranial glioma.

Non-coding RNAs in urinary bladder cancer microenvironment: Diagnostic, therapeutic, and prognostic perspective.

Urinary bladder cancer (UBC) is the ninth most common cancer worldwide. Despite the reliance of UBC therapy on definite pathological grading and classifications, the clinical response among patients varies widely. The molecular basis of this type of cancer appeals to considerable research; hence, new diagnostic and therapeutic options are introduced. Convenient keywords were searched in Google Scholar, PubMed, the Egyptian Knowledge Bank (EKB), and Web of Science. The recent era of UBC research is concerned with non-coding RNAs (ncRNAs), predominantly, microRNAs (miRNAs) and long non-coding RNA (lncRNAs). In addition, snoRNAs, PIWI-interacting RNAs, mitochondrial RNAs, circular, and Schistosoma haematobium-related ncRNAs appeared to contribute to the pathogenesis of the UBC. This review underscored the recently studied ncRNAs and their importance in the pathogenesis of UBC. Besides, we introduced the prospectives regarding their diagnostic, therapeutic, and prognostic significance in UBC clinical settings. Conclusion. Oncogenic and oncosuppressor ncRNAs' definite balances and interaction within the TME of UBC are key players in the fate of the tumor. Thus, profiling ncRNA in-depth inspects the TME of the UBC for better clinical insights.

Anti-inflammatory effect of sea buckthorn in an HCl-induced cystitis rat model.

Although the mechanism underlying interstitial cystitis/bladder pain syndrome (IC/BPS) remains unclear, oxidative stress is suggested to be implicated in IC/BPS development. Sea buckthorn (SB; Hippophae rhamnoides L.) contains several compounds with antioxidant properties. In addition, intravesical application of hydrochloric acid (HCl) in rats induces histological changes similar to those observed in humans with IC. Therefore, the aim of this study was to evaluate the anti-inflammatory effects of SB in an HCl-induced rat cystitis model. Twenty 8-week-old female Sprague-Dawley rats were instilled with HCl in their bladders to create an IC/BPS model. The model rats were divided into three groups and orally administrated distilled water (control, n=4), concentrated SB (n=8), or pentosan polysulfate (PPS, n=8) daily. Pathologic inflammation grade (H&E staining), number of mast cells per square millimeter (toluidine blue staining), fibrotic changes (Masson's trichrome staining), and apoptosis (terminal deoxynucleotidyl transferase dUTP nick end labeling staining) of bladder tissue samples were compared among the groups. Compared to the control group, the SB and PPS groups showed reduced edema (5.25±0.96 vs. 2.25±0.46 vs. 2.50±0.54, p=0.004, p=0.005, respectively), number of mast cells (12.5±3.6 vs. 6.8±1.9 vs. 6.6±1.8, p=0.010, p=0.002, respectively), ratio of fibrotic submucosal tissue (63.9%±7.0% vs. 43.6%±9.9% vs. 40.5%±5.2%, p<0.001, p<0.001, respectively), and ratio of apoptotic nucleus (40.7%±11.7% vs. 7.7%±6.5% vs. 5.1%±4.9%, p<0.001, p<0.001, respectively). SB exhibited anti-inflammatory effects comparable to those of PPS in the HCl-induced chemical cystitis model.

LncRNA GATA3-AS1 Promotes Bladder Uroepithelial Cancer Progression by Stabilizing DDX5.

Objective: Exploration of molecular markers is an ongoing focus in the field of bladder cancer research. Based on data from public databases, GATA3-AS1 was identified as upregulated in bladder urothelial carcinoma (BLCA); however, its exact function and regulatory mechanism in this context remain unclear. Methods: To investigate the clinical implications of GATA3-AS1, we examined its levels in 90 BLCA and adjoining normal tissue samples. Functional assays were conducted to assess the effects of GATA3-AS1 on BLCA cell proliferation, migration, and invasion. Animal assays were employed to determine the effects of GATA3-AS1 on BLCA tumorigenicity in vivo. Immunoblotting, RNA pull-down, RNA immunoprecipitation, TOP/FOP luciferase reporter gene, and coimmunoprecipitation assays were used to explore the molecular mechanism underlying the effects of GATA3-AS1 on BLCA progression. Results: GATA3-AS1 expression was significantly up-regulated in BLCA tissues and correlated with pathological stage, grade, and poor patient outcome. Altered GATA3-AS1 levels promoted BLCA proliferation, migration, and invasion. Mechanistic studies suggested that GATA3-AS1 interacts with DDX5 protein, enhances its stability, and ultimately leads to BLCA progression through Wnt/β-catenin signaling pathway activation. Conclusion: GATA3-AS1 overexpression increases the aggressiveness of BLCA by activating the Wnt/β-catenin pathway through binding to DDX5. GATA3-AS1 has potential as a new molecular predictor of poor prognosis in patients with BLCA.

Development and Validation of a Deep Learning Model Based on MRI and Clinical Characteristics to Predict Risk of Prostate Cancer Progression.

Purpose To validate a deep learning (DL) model for predicting the risk of prostate cancer (PCa) progression based on MRI and clinical parameters and compare it with established models. Materials and Methods This retrospective study included 1607 MRI scans of 1143 male patients (median age, 64 years; IQR, 59-68 years) undergoing MRI for suspicion of clinically significant PCa (csPCa) (International Society of Urological Pathology grade > 1) between January 2012 and May 2022 who were negative for csPCa at baseline MRI. A DL model was developed using baseline MRI and clinical parameters (age, prostate-specific antigen [PSA] level, PSA density, and prostate volume) to predict the time to PCa progression (defined as csPCa diagnosis at follow-up). Internal and external testing was performed. The model's ability to predict progression to csPCa was assessed by Cox regression analyses. Predictive performance of the DL model up to 5 years after baseline MRI in comparison with the European Randomized Study of Screening for Prostate Cancer (ERSPC) future-risk calculator, Prostate Cancer Prevention Trial (PCPT) risk calculator, and Prostate Imaging Reporting and Data System (PI-RADS) was assessed using the Harrell C-index. Optimized follow-up intervals were derived from Kaplan-Meier curves. Results DL scores predicted csPCa progression (internal cohort: hazard ratio [HR], 1.97 [95% CI: 1.61, 2.41; P < .001]; external cohort: HR, 1.32 [95% CI: 1.14, 1.55; P < .001]). The model identified a subgroup of patients (approximately 20%) with risks for csPCa of 3% or less, 8% or less, and 18% or less after 1-, 2-, and 4-year follow-up, respectively. DL scores had a C-index of 0.68 (95% CI: 0.63, 0.74) at internal testing and 0.56 (95% CI: 0.51, 0.61) at external testing, outperforming ERSPC and PCPT (both P < .001) at internal testing. Conclusion The DL model accurately predicted PCa progression and provided improved risk estimations, demonstrating its ability to aid in personalized follow-up for low-risk PCa. Keywords: MRI, Prostate Cancer, Deep Learning Supplemental material is available for this article. ©RSNA, 2025.

CT Multidimensional Radiomics Combined with Inflammatory Immune Score For Preoperative Prediction of Pathological Grade in Esophageal Squamous Cell Carcinoma.

Inflammation and immune biomarkers can promote angiogenesis and proliferation and metastasis of esophageal squamous cell carcinoma (ESCC). The degree of pathological grade reflects the tumor heterogeneity of ESCC. The purpose is to develop and validate a nomogram based on enhanced CT multidimensional radiomics combined with inflammatory immune score (IIS) for predicting poorly differentiated ESCC. A total of 266 ESCC patients from the retrospective study were included and randomly divided into a training set (N=186) and a validation set (N=80), and a complete data set (N=266), and overall survival was determined to follow up after surgery. The tumor imaging was segmented to form intratumoral and peritumoral 3mm areas of 3D volume of interest (VOI) on CT arterial and venous phases, and 3404 radiomics features were extracted. Finally, the radiomics scores were calculated for arterial phase intratumoral (aInRads), peritumoral 3mm (aPeriRads3), and venous phase intratumoral (vInRads), peritumoral 3mm (vPeriRads3). Logistic regression was used to fuse the four cohorts of scores to form a Stacking. Additionally, sixteen inflammatory-immune biomarkers were analyzed, including aspartate aminotransferase to lymphocyte ratio (ALRI), aspartate aminotransferase to alanine aminotransferase ratio (AAR), neutrophil times gamma-glutamyl transpeptidase to lymphocyte ratio (NγLR), and albumin plus 5 times lymphocyte sum (PNI), etc. Finally, IIS was constructed using ALRI, AAR, NγLR and PNI. Model performance was evaluated by area under receiver operating characteristic curve (AUC), calibration curve, and decision curve analyse (DCA). Stacking and IIS were independent risk factors for predicting poorly differentiated ESCC (P<0.05). Ultimately, three models of the IIS, Stacking, and nomogram were developed. Compared with the Stacking and IIS models, nomogram achieved better diagnostic performance for predicting poorly differentiated ESCC in the training set (0.881vs 0.835 vs 0.750), validation set (0.808 vs 0.796 vs 0.595), and complete data set (0.857 vs 0.823 vs 0.703). The nomogram achieved an AUC of 0.881(95%CI 0.826-0.924) in the training set, and was well verified in the validation set (AUC: 0.808[95%CI 0.705-0.888]) and the complete data set (AUC: 0.857[95%CI 0.809-0.897]). Moreover, calibration curve and DCA showed that nomogram achieved good calibration and owned more clinical net benefits in the three cohorts. KaplanMeier survival curves indicated that nomogram achieved excellent stratification for ESCC grade status (P<0.0001). The nomogram that integrates preoperative inflammatory-immune biomarkers, intratumoral and peritumoral CT radiomics achieves a high and stable diagnostic performance for predicting poorly differentiated ESCC, and may be promising for individualized surgical selection and management. The original manuscript contained in the research is included in the article. Further inquiries can be made directly to the corresponding author.

Study of histopathological characteristics and hormonal receptors biomarkers of breast cancer in Benghazi medical Centre in the period between (2019-2024)

Background: Breast cancer is considered as the most frequently diagnosed cancer worldwide accounting for 11.7% of new cancer cases in 2020. Thus, breast cancer remains a significant global health concern despite the rapid advances in this field. Material and methods: Study data were collected and medical records of patients at Benghazi Medical Centre were reviewed to obtain data on age, sex, tumour site, nationality, family history, year of diagnosis, site, pathological grade and tumour markers. Result: The results showed that the highest number recorded was 23 cases in 2020 and 22 cases in 2023, the mean age was 53 years, while the age group was from 31 to 80 years, in a geographical area of Benghazi 43%, there were 68 cases from Libya and one case from Egypt, 68% showed a negative family history, and most of the cases were between stage II and stage III. Regarding site of the tumour 49% are in the left side of the tumour site and 47.8% in the right side, and 2.9% were bilateral. Most of the cases were negative for Her2, positive for ER, and positive for PR, regarding expression of Ki-67 level values in 12 cases expression was (20-40%) and in10 cases expression was&gt;80%. Most of the cases 91% the histopathological report reported invasive ductal carcinoma. Conclusion: Early detection and diagnosis using new technologies, improved access to affordable treatment, more palliative care and support for breast cancer research are all important measures that must be addressed to reduce morbidity and mortality.

Using apparent diffusion coefficient maps and radiomics to predict pathological grade in upper urinary tract urothelial carcinoma

BackgroundThe apparent diffusion coefficient (ADC) has been reported as a quantitative biomarker for assessing the aggressiveness of upper urinary tract urothelial carcinoma (UTUC), but it has typically been used only with mean ADC values. This study aims to develop a radiomics model using ADC maps to differentiate UTUC grades by incorporating texture features and to compare its performance with that of mean ADC values.MethodsA total of 215 patients with histopathologically confirmed UTUC were enrolled retrospectively and divided into training and test sets. The optimum cutoff value for the mean ADC was derived using the receiver operating characteristic (ROC) curve. Radiomics features based on ADC maps were extracted and screened, and then a radiomics model was constructed. Both mean ADC values and the radiomics model were tested on the training and test sets. ROC curve and DeLong test were used to assess the diagnostic performance.ResultsThe training set consisted of 151 patients (median age: 68.0, IQR: [63.0, 75.0] years; 80 males), whereas the test set consisted of 64 patients (median age: 68.0, IQR: [61.0, 72.3] years; 31 males). The ADC values were significantly lower in high-grade versus low-grade UTUC (1310 × 10− 6mm2/s vs. 1480 × 10− 6mm2/s, p < 0.001). The area under the curve (AUC) values of the mean ADC values in the training and test sets were 0.698 [95% confidence interval [CI]: 0.625–0.772] and 0.628 [95% CI: 0.474–0.782], respectively. Compared with the mean ADC values, the ADC-based radiomics model, which incorporates features such as log-sigma-1-0-mm-3D_glcm_ClusterProminence and wavelet-LLL_firstorder_10Percentile, obtained a significantly greater AUC in the training set (AUC: 1.000, 95% CI: 1.000–1.000, p < 0.001), and a trend towards statistical significance in the test set (AUC: 0.786, 95% CI: 0.651–0.921, p = 0.071).ConclusionsThe ADC-based radiomics model showed promising potential in predicting the pathological grade of UTUC, outperforming the mean ADC values in classification accuracy. Further studies with larger sample sizes and external validation are necessary to confirm its clinical utility and generalizability.Clinical trial numberNot applicable.

Precise vesical wall staging of bladder cancer in the era of precision medicine: has it been fulfilled?

Urinary bladder cancer is a global disease that poses medical and socioeconomic challenges to patients and healthcare systems. Predicting detrusor invasiveness and pathological grade of bladder cancer by the radiologist is imperative for informed decision-making and effective patient-tailored therapy. Cystoscopy and TURBT are the current gold standard for preoperative histologic diagnosis and local pathological staging but are compromised by their intrusiveness, under-sampling, and staging inaccuracies. Over the last few decades, incredible imaging technology advancements have enabled radiologists to progress in these grading and staging tasks. MRI has become widely accepted as a noninvasive alternative. It supplements morphologic data with functional insights into the tumor microenvironment, enhancing tumor characterization and predicting the detrusor's histologic grade and invasiveness status. Radiomics is a promising field that helps radiologists achieve higher accuracies in bladder cancer staging, re-staging, and direct treating teams to potential management readjustments. Such knowledge leaps hold promise for personalized management of bladder cancer in a precision medicine era.

Clinicopathological significance of c-MET and HER2 altered expression in bladder cancer.

Tumor recurrence or metastasis after surgery is a significant factor influencing bladder cancer (BC) prognosis. Novel molecular biomarkers are necessary to determine each patient's specific outcome because current biomarkers have limited power for predicting prognosis. The proto-oncogene MET encodes c-MET, a tyrosine kinase receptor. When c-MET attaches to its ligand, it triggers several steps in the signal transduction cascade that control cell survival, proliferation, and invasion. c-MET is overexpressed in several carcinomas. The HER2 gene encodes another receptor tyrosine kinase (RTK). HER2 overexpression is linked to altered proliferation and increased aggressiveness in several malignancies. Identifying crosstalk partners of RTKs implicated in bladder cancer development may have a unique role in predicting aggressiveness. This study explored the expression status of c-MET and HER2 in human BC and their clinical significance in disease outcomes. A quantitative real-time polymerase chain reaction was done on 40 BC patients who had undergone transurethral resection (TUR) or radical cystectomy and had a pathologically verified diagnosis of primary tumor without prior chemoradiotherapy as well as 20 patients with benign diseases who served as controls. The c-MET and HER2 expression levels were investigated, and their relationship with clinicopathological features was analyzed. c-MET and HER2 gene expression were significantly higher, 6.1- and 4.5-fold, in the study group compared to the controls. The frequency of c-MET and HER2 overexpression in the study group was 80% (32/40) and 90% (36/40), respectively. c-MET overexpression was associated with pathological stage(P = 0.002), tumor grade (P = 0.019), muscle invasion (P = 0.008), and node involvement (P = 0.017), while HER2 overexpression was associated with pathological stage(P = 0.033), invasion to muscles (P = 0.003), and node involvement (P = 0.005). Based on the Log-rank test, patients expressing both c-MET and HER2 had the poorest disease-free survival rates among all studied patients (median = 10m, 3.0-16.9 95%CI). There is a possible correlation between c-MET and HER2 gene overexpression and poor clinical outcomes in patients with BC.