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This study developed an innovative biosensor strategy for the sensitive and selective detection of canine mammary tumor biomarkers, cancer antigen 15–3 (CA 15–3) and mucin 1 (MUC-1), integrating green silver nanoparticles (GAgNPs) with machine learning (ML) algorithms to achieve high diagnostic accuracy and potential for noninvasive early detection. The GAgNPs-enhanced electrochemical biosensor demonstrated selective detection of CA 15–3 in serum and MUC-1 in tissue homogenates, with limits of detection (LODs) of 0.07 and 0.11 U mL−1, respectively. The nanoscale dimensions of the GAgNPs endowed them with electrochemically active surface areas, facilitating sensitive biomarker detection. Experimental studies targeted CA 15–3 and MUC-1 biomarkers in clinical samples, and the biosensor exhibited ease of use and good selectivity. Furthermore, ML algorithms were employed to analyze the electrochemical data and predict biomarker concentrations, enhancing the diagnostic accuracy. The Random Forest algorithm achieved 98% accuracy in tumor presence prediction, while an Artificial Neural Network attained 76% accuracy in CA 15–3-based tumor grade classification. The integration of ML techniques with the GAgNPs-based biosensor offers a promising approach for noninvasive, accurate, and early detection of canine mammary tumors, potentially revolutionizing veterinary diagnostics. This multilayered strategy, combining eco-friendly nanomaterials, electrochemical sensing, and ML algorithms, holds significant potential for advancing both biomedical research and clinical practice in the field of canine mammary tumor diagnostics. [ABSTRACT FROM AUTHOR]

Precise diagnosis of benign and malignant breast cancer plays an important role in the effective treatment of breast cancer patients. Several classification models with different characteristics have been developed and used in a wide range of breast cancer domains to improve classification accuracy. Although the classification models differ in different aspects, they all have the same logic in their learning processes and use a continuous distance-based cost function. However, using a continuous distance-based function as a cost function in the learning processes of the traditional classification models is unreasonable or at least insufficient; since the goal function of the classification, is discrete. Hence, developing a discrete cost function for learning the classification problems, due to more consistency, may improve the classification rate; but, it has been neglected in the literature. In this paper, in contrast to all traditional continuous distance-based learning processes, a novel discrete learning-based process is proposed and implemented on a multilayer perceptron to yield a more consistent intelligent classifier. Then, the proposed discrete learning-based multilayer perceptron (DIMLP) is used for breast cancer classification. Empirical results of the breast cancer datasets indicate that the proposed DIMLP model can averagely achieve the classification rate of 94.70%, while the classification rate for the traditional MLP model is only equal to 88.54%. Therefore, the proposed DIMLP can be an appropriate and efficient alternative model for intelligent breast cancer classification, especially when more accurate results and/or a more reasonable model are required. [ABSTRACT FROM AUTHOR]

Atypical cells (Atyp.C), as a new parameter determined by an automated urine analyzer, can be suspected of being malignant tumor cells. We evaluated the extent to which the Atyp.C can predict the existence of malignant tumor cells.A total of 3,315 patients (1,751 in the training cohort and 1,564 in the testing cohort) were recruited and divided into five groups, namely, primary bladder cancer (BCa), recurrent BCa, post-treatment monitoring of BCa, other urological tumors, and controls. Urine Atyp. C, bacteria, white blood cell, and red blood cell were measured by a Sysmex UF-5000 analyzer. We compared the Atyp.C values across the different groups, sexes, and tumor stages. The diagnostic performance of Atyp.C alone and in combination with other parameters for detecting BCa was evaluated using receiver operating characteristic (ROC) curve analysis.The Atyp.C value of the primary BCa group was significantly higher than that in the other groups, except recurrent BCa group. The Atyp.C value was closely related to tumor staging. Atyp.C combined with bacteria had the highest diagnostic performance for primary BCa [training cohort AUC: 0.781 (95 % CI: 0.761–0.801); testing cohort AUC: 0.826 (95 % CI: 0.806–0.845)]. The AUC value of diagnosed recurrent BCa by Atyp.C plus bacteria for the training cohort was 0.784 (95 % CI: 0.762–0.804).Atyp.C was high in primary BCa patients and the combination of bacteria and Atyp.C showed high predictive value for primary BCa, suggesting that Atyp.C may be a useful objective indicator for the early detection of BCa. [ABSTRACT FROM AUTHOR]

The ever-growing 1.15 million new cases of cancer on a yearly basis alone in India is a major cause of concern for the experts and researchers working in various biomedical organizations. The advent of modern text engineering strategies and NLP techniques can play a crucial role in the discovery and analysis of pre-existing knowledge present in the cancer related biomedical archives. The available 10 Cancer hallmarks can provide key insights and make significant impact in the ongoing cancer research. It is extremely important to identify and classify required information due to time and resource crunch which needs to be quickly accessed. This article introduces a novel machine learning framework called Cancer Hallmark Classification and Topic Modeling (CHCTM), designed for supervised learning. The CHCTM framework is capable of semantically learning, categorizing, and extracting significant topics and their combinations related to the hallmarks of cancer (HoC) from a dataset comprising 1499 PubMed documents. The key contributions of this research include the creation of an innovative ensemble classification model using a meta-classifier based on Random Forest (RF). Additionally, it introduces an Enhanced Latent Dirichlet Allocation (ELDA) topic modeling strategy to generate relevant mixtures of topics. The performance of the CHCTM framework is evaluated using precision, recall, accuracy, and F-score parameters. Comparative analysis with other biomedical baseline methods reveals an 8% improvement in F-score. The coherence values acquired for ELDA are tallied and weighted against PLSA and LDA models to demonstrate the effectiveness of this approach. [ABSTRACT FROM AUTHOR]

Aims: This evaluation combines clinical and non-clinical collaborative breast referral triage to gain an understanding relating to the value of triage, by identifying 'suspected cancer' and 'cancer not suspected' populations, improve the patient pathway, and facilitate optimised resource availability. Method: An iterative service improvement method was used, with distinct phases of the process outlined to facilitate testing of ideas. The evaluation ran for 13 weeks in 2022. Regular team member meetings were arranged to discuss and agree improvement aims and outcomes. Findings: A triage flowchart was developed collaboratively, and subsequently adopted by the non-clinical booking team. Bespoke clinics were established, demonstrating no evidence of increased risk to patients, and meeting 28-day Faster Diagnosis Standard (FDS) requirements. Conclusion: breast referral triage of 'suspected cancer' and 'cancer not suspected' patients, using a clinical and non-clinical collaborative approach facilitates improved service visibility, prioritisation, management, and measurement. This also supports delivery of the 2019 NHS Long Term Plan to enhance earlier and faster cancer diagnosis by optimising access to diagnostic resources where required. [ABSTRACT FROM AUTHOR]

According to the survey of World Health Organization (WHO), in 2020 there are 2.3 million women found with breast cancer and 685,000 deaths in world wide. 81% women get affected with cancer over the age of 50 at the time of detection. Breast cancer is the world's number 2 cancer and number 1 cancer in India and 66% survival rate in India is very low if compare to 90% in U.S and 90.2% in Australia. However, treatment for this cancer has possibility of 90% or more. So that, it need to be detect the cancer at very early stage to overcome the death rate. Main objective of this research to design a Breast Cancer diagnose system using image processing and deep learning which can be helpful for radiologist and physician for treating the diagnosis. Basically, Deep learning is a fast-developing fashion inside the health care enterprise and facilitates medical experts to examine records and pick out trends. And image processing plays vital role for enhancing the quality of image by removing noise which is very helpful for better abnormality classification. Now a days Convolution Neural Networks (CNNs) are very popular due to its better performance. In this work, we have used transfer learning with pre-trained VGG16 model. At initial testing stage, the model shows the over-fitting and after that performance improved. Hence we achieved better results by using this approach on DDSM and UPMC data-sets for breast cancer classification. Classifier classify the images into four classes as asymmetry, calcification, carcinoma and mass. Initially 2276 images were taken and divided into 80%-20% ratio. The accuracy achieved by this approach varied from 92% to 95%. We have also used transfer learning with VGG19 and ResNet50 for comparison and found VGG16 much powerful among them. We found, transfer learning with VGG16 giving better results on DDSM and UPMC data-sets. However, breast cancer divided into different categories according to its type, grade or stage of abnormalities, severity of cancer, aggressiveness of cancerous cells, presence/absence of gene etc. Hence classification can be done basis on other types of abnormalities. [ABSTRACT FROM AUTHOR]

Background: Appropriate staging of lung cancer is of paramount importance, as it customizes treatment and predicts prognosis. Both Fludeoxyglucose-18 (FDG) positron emission tomography (PET) combined with contrast computed tomography (CT) and endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) are two widely used diagnostic modalities in the field of staging & diagnosis of lung malignancies, the former depends on image analysis while the later enables real-time sampling of lymph nodes under sonographic guidance. Objective: To compare the diagnostic and staging accuracy of convex probe EBUS-TBNA versus FDG – PET/CT as two modalities in diagnosis & mediastinal staging of lung cancer patients. Methods: This prospective, observational (daignostic accuracy) research was performed on 40 cases with lung malignancies. All cases were examined via FDG-PET/CT followed by convex probe EBUS-TBNA for diagnosis & staging of concurrent mediastinal lymphadenopathy (MLN). Results: The diagnostic yield of EBUS-TBNA reached 92.5% (37/40) compared to 70% (28/40) for FDG-PET/CT. There was poor agreement between EBUS-TBNA & FDG-PET/CT regarding (MLN) staging (k = 0.043), in 16/40 patients (40%), EBUS MLN staging matched that of FDG-PET/CT, while in 24/40(60%) there were discrepancies between the two diagnostic modalities; 18/40(45%) were up-staged after EBUS while 6/40(15%) were down staged after EBUS. In addition, EBUS-TBNA confirmed occult mediastinal nodal involvement in 9/10 FDG-PET/CT negative scans (N0). The overall diagnostic accuracy of EBUS-TBNA was significantly greater than FDG-PET/CT in staging of lung cancer (97.37% & 70% respectively, p < 0.001). Conclusion: EBUS-TBNA is a minimally invasive procedure that we currently recommend as a first choice for MLN staging. Trial registration: ClinicalTrials.gov, NCT06479798. Registered 26 June 2024—Retrospectively registered, https://clinicaltrials.gov/study/NCT06479798. [ABSTRACT FROM AUTHOR]

AbstractAn early detection of lung tumors is critical for better treatment results, and CT scans can reveal lumps in the lungs which are too small to be picked up by conventional X-rays. CT imaging has advantages, but it also exposes a person to radiation from ions, which raises the possibility of malignancy, particularly when the imaging procedure is done. Access to expensive-quality CT scans and the related sophisticated analytic tools might be restricted in environments with fewer resources due to their high cost and limited availability. It will need an array of creative technological innovations to overcome such weaknesses. This paper aims to design a heuristic and deep learning-aided lung cancer classification using CT images. The collected images are undergone for segmentation, which is performed by Shuffling Atrous Convolutional (SAC) based ResUnet++ (SACRUnet++). Finally, the lung cancer classification is performed by the Adaptive Residual Attention Network (ARAN) by inputting the segmented images. Here the parameters of ARAN are optimally tuned using the Improved Garter Snake Optimization Algorithm (IGSOA). The developed lung cancer classification performance is compared to conventional lung cancer classification models and it showed high accuracy. [ABSTRACT FROM AUTHOR]

High-grade B-cell lymphoma with 11q aberration (HGBL-11q) is a distinct lymphoma entity according to the 5th edition of the WHO classification of hematolymphoid tumors. It lacks MYC translocation but carries proximal gains and/or telomeric losses of chromosome 11q. This rare type of B-cell lymphoma is less frequently reported in people living with HIV (PLWH), and its exact frequency remains unclear. Our goal was to retrospectively analyze its frequency in a cohort of aggressive B-cell lymphomas in PLWH, including Burkitt lymphoma (BL, n = 35), diffuse large B-cell lymphoma (DLBCL, n = 48), high-grade B-cell lymphoma, not otherwise specified (HGBL-NOS, n = 13), which was diagnosed as AIDS-related lymphoma (ARL) at our institution. In total, 10/96 (10.4%) cases harbored the typical 11q aberration pattern, predominantly those that had been classified as BL (6/35, 17.1%), DLBCL (2/48, 4.2%), and HGBL, NOS (2/13, 15.4%). We also evaluated 7 cases of AIDS-related HGBL-11q (AR-HGBL-11q) reported in the literature. The median age of our cohort was 35 years, and all the patients were male. Most cases (70%) had a history of HIV infection for over 1 year, and all were involved in lymph nodes (100%), frequently involved extranodal sites (60%), and Ann Arbor stage III/IV. In histomorphology, the cases exhibited diverse cytological features, reminiscent of BL (6 cases), DLBCL (2 cases), and HGBL (2 cases). A comparison of the combined cohort of 17 AR-HGBL-11q cases with 11 ARL cases that lacked both MYC rearrangement and 11q aberration at our institution showed that HGBL-11q cases were characterized by strikingly coarse apoptotic debris (P < 0.001), background rich in eosinophils (P = 0.002), higher expression of the germinal centre marker LMO2 (P = 0.080), lower expression of MUM1 (P = 0.004), BCL2 (P = 0.007), and LEF1 (P = 0.080), and lower positivity for EBER in situ hybridisation (P = 0.027). Notably, one case in our series was EBV-positive, a finding not previously reported in the literature. Furthermore, comparing the prognosis between these two groups, AR-HGBL-11q showed a relatively favorable prognosis (P = 0.15), although the difference was not statistically significant. We analyzed this rare lymphoma entity in the HIV setting and highlighted the importance of integrating histomorphological and immunophenotypic features in its diagnosis and classification. [ABSTRACT FROM AUTHOR]

Background: It is accepted that tumor stage and size can influence response to neoadjuvant therapy in locally advanced rectal cancer (LARC). Studies on organ preservation to date have included a wide variety of size and TNM stage tumors. The aim of this study was to report tumor response based on each relevant TNM stage and tumor size. Methods: Patients treated with LARC from 2014 to 2021 with cT2–3NxM0 tumors who received neoadjuvant chemoradiotherapy with or without induction chemotherapy were included. Tumors were staged and tumor size calculated on pelvic MRI at the time of diagnosis (cTNM). Tumor size was based on the largest dimension taken on the longest axis of each tumor. Clinical response was defined on the basis of post-treatment pelvic MRI and pathological response following surgery, when performed. Statistical analysis was performed using IBM SPSS Statistics™, version 20. Data from 432 patients were analyzed as follows: cT2N0 (n = 51), cT2N+ (n = 36), cT3N0 (n = 76), cT3N+ (n = 270). Results: The rate of complete or near-complete response (cCR or nCR) varied from 77% in cT2N0 ≤ 3 cm to 20% in cT3N+ > 4 cm. Organ preservation without recurrence at 2 years was achieved in 86% of patients with cT2N0, 50% in cT2N+, 39% in cT3N0, and 12% in cT3N+. Conclusion: There is significant variation in tumor response according to tumor stage and size. Tumor response appears inversely proportional to increasing TNM stage and tumor size. This data can support both refinement of selective patient recruitment to organ preservation programs and shared decision-making. [ABSTRACT FROM AUTHOR]

Deep learning applications have witnessed significant advancements across diverse domains, revolutionizing tasks such as image recognition, disease classification, cancer detection, natural language processing, and autonomous decision-making. However, striking a balance between performance and cost remains a fundamental challenge. Performance, which encompasses accuracy, efficiency, and effectiveness, is crucial for the real-world applicability of deep learning models. Attaining high performance often involves using resource-intensive models with intricate architectures, extensive datasets, and hyperparameter tuning. While these factors lead to improved performance, they also result in increased costs, including computational resources, time, and energy consumption. This research addresses this challenge by proposing a novel low-cost deep learning model based on Sharpened Cosine Similarity (LC-SCS) for breast cancer classification using thermal images. In our study on a DMR-IR dataset, we also utilized pre-trained models: ResNet-101, VGG-16, Inception-V3, ResNet-50, VGG-19, and Xception. The proposed LC-SCS model achieved an impressive accuracy of 94%, trailing just 4% behind the leading VGG-19 model, while maintaining a low computational cost. It achieved recall and precision scores of 0.95 each, with an F1-score of 0.94. The LC-SCS model excels in computational efficiency, demanding only 1.85 GFLOPs and 1.2 million parameters. The memory requirement is minimal at 865.35 MB, and it exhibits a latency of just 0.003 s. Additionally, the CPU execution time for prediction is 3.59 s. Comparatively, the best-performing pre-trained VGG-19 model achieved 98% accuracy but incurred significantly higher costs. The proposed LC-SCS model showcases a remarkable 298.63 times reduction in GFLOPs, a 116.31 times reduction in total parameters, a 4.57 times reduction in memory requirements for model weights, a 5 times reduction in latency, and a 3.33 times reduction in CPU execution time for prediction, thus making it as an exceptionally resource-efficient model, particularly in scenarios with limited computational resources. [ABSTRACT FROM AUTHOR]

Introduction: Pathologists rely on whole slide images (WSIs) to diagnose cancer by identifying tumor cells and subtypes. Deep learning models, particularly weakly supervised ones, classify WSIs using image tiles but may overlook false positives and negatives due to the heterogeneous nature of tumors. Both cancerous and healthy cells can proliferate in patterns that extend beyond individual tiles, leading to errors at the tile level that result in inaccurate tumorlevel classifications. Methods: To address this limitation, we introduce NATMIL (Neighborhood Attention Transformer Multiple Instance Learning), which utilizes the Neighborhood Attention Transformer to incorporate contextual dependencies among WSI tiles. NATMIL enhances multiple instance learning by integrating a broader tissue context into the model. Our approach enhances the accuracy of tumor classification by considering the broader tissue context, thus reducing errors associated with isolated tile analysis. Results: We conducted a quantitative analysis to evaluate NATMIL’s performance against other weakly supervised algorithms. When applied to subtyping non-small cell lung cancer (NSCLC) and lymph node (LN) tumors, NATMIL demonstrated superior accuracy. Specifically, NATMIL achieved accuracy values of 89.6% on the Camelyon dataset and 88.1% on the TCGA-LUSC dataset, outperforming existing methods. These results underscore NATMIL’s potential as a robust tool for improving the precision of cancer diagnosis using WSIs. Discussion: Our findings demonstrate that NATMIL significantly improves tumor classification accuracy by reducing errors associated with isolated tile analysis. The integration of contextual dependencies enhances the precision of cancer diagnosis using WSIs, highlighting NATMILs´ potential as a robust tool in pathology [ABSTRACT FROM AUTHOR]

Background: Prostate cancer is well known as the commonest cancer in men and the second leading cause of cancer-related death. CT, MRI and bone scintigraphy are considered the commonly widely used imaging diagnostic tools for detection, staging and follow-up of prostate cancer. Prostate-specific membrane antigen (PSMA) is a membrane glycoprotein, that can be concentrated in prostate cancer cells up to 100 times higher than in normal cells. PSMA-targeted imaging modalities have now proven their efficacy in diagnosis, staging and follow-up of prostate cancer. The use of 68Ga PSMA PET-CT has efficiently improved the detection of loco-regional and metastatic disease. 68Ga PSMA PET-CT also has an effective role in the primary diagnosis, staging, and detecting biochemical recurrence after curative treatment and in metastasis-targeted therapy. This work aims to review the role of 68Ga PSMA PET-CT in anatomical staging of prostate cancer in correlation with histopathological staging. Results: Zonal correlation between 68Ga PSMA findings and biopsy results showed sensitivity ranging between 76.9 and 90.6% and specificity ranging from 85.7 to 100%. There was high significant correlation between the SUVmax uptake and the biopsy results, between the SUVmax uptake and the local staging as well as between the Gleason score and 68Ga PSMA PET/CT findings. Conclusions: 68Ga PSMA PET/CT is a highly promising imaging modality with an effective role in detection of prostate cancer showing high sensitivity and specificity in prediction of zonal histopathological results and loco-regional Gleason score staging with significant positive correlation between the SUV uptake results, Gleason score and the PSA levels. [ABSTRACT FROM AUTHOR]

Objective: We conducted this study to summarize the results of studies reporting the role of NLR (neutrophil to lymphocyte ratio) in PSCC (penile squamous cell carcinoma). Methods: This meta-analysis was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria. A systematic search was conducted on PubMed, Scopus, and web of science up to March 10, 2023. Fourteen studies were included in the review. The NOS (Newcastle–Ottawa Scale) was used to determine the quality of the included studies. This meta-analysis was conducted on the studies reporting the relationship between NLR and survival using HR (hazard ratio) and 95% CI (confidence interval). Results: There was a significant association between NLR levels and the prognosis, nodal stage, and anatomical tumor stage of PSCC patients. In the meta-analysis of the association of NLR with survival, NLR level was significantly associated with lower cancer-specific survival (HR = 3.51, 95% CI = 2.07–5.98, p < 0.001) and lower disease-free survival (HR = 2.88, 95% CI = 1.60–5.20, p < 0.001). However, NLR was found to have no association with the stage, grade, location, and size of the tumor. Conclusion: NLR has a significant diagnostic and prognostic value in PSCC. [ABSTRACT FROM AUTHOR]

This article discusses a new method for diagnosing brain lymphoma using nanopore sequencing of cerebrospinal fluid (CSF). The study demonstrates the clinical application of this method in two cases of CNS lymphoma. The researchers adapted their fast-track unsupervised machine learning approach for cases with a differential diagnosis of lymphoma and other malignant brain tumors. The results showed that nanopore sequencing-derived methylation patterns can be used for next-day diagnosis and treatment initiation. This point-of-care protocol has the potential to significantly reduce neurological impairment through timely and non-invasive testing. [Extracted from the article]

Background: Patients with gastric cancer (GC) who underwent radical surgery require long-term follow-up (usually 5 years). The purpose of this study was to explore individualized follow-up strategies for patients with GC. Methods: This is a retrospective cohort study that established a clinicopathologic database of patients who underwent gastrectomy from January 2010 to December 2020 at Ningbo No. 2 Hospital. Follow-up was performed until March 2023. The rate of new-onset recurrence of patients with GC was explored annually according to different pTNM stages, defining a recurrence rate of less than 1% as adequate follow-up time. Results: Of the 1606 patients who were eligible, the total number of patients who completed the 5- and 10-year follow-up was 1107 and 586, respectively. A total of 444 cases were diagnosed with recurrence. The recurrence rate for stage IA patients was consistently less than 1% during the follow-up time. The adequate follow-up time (the rate of new-onset recurrence less than 1%) was 5 years for stage IB and IIA patients, and 8 years for stage IIB and IIIA patients, respectively. In contrast, stage IIIB patients were always at risk of recurrence during the follow-up time (>1%). Time to a new recurrence rate for stage IIIC patients was 6 years. Conclusion: Among patients who underwent radical gastrectomy, the rate of new-onset recurrence varied among patients with different pTNM stages. This study suggests that the follow-up of GC can be individualized and refer to pTNM stage. [ABSTRACT FROM AUTHOR]

Skin cancer (SC) is an important medical condition that necessitates prompt identification to ensure timely treatment. Although visual evaluation by dermatologists is considered the most reliable method, its efficacy is subjective and laborious. Deep learning-based computer-aided diagnostic (CAD) platforms have become valuable tools for supporting dermatologists. Nevertheless, current CAD tools frequently depend on Convolutional Neural Networks (CNNs) with huge amounts of deep layers and hyperparameters, single CNN model methodologies, large feature space, and exclusively utilise spatial image information, which restricts their effectiveness. This study presents SCaLiNG, an innovative CAD tool specifically developed to address and surpass these constraints. SCaLiNG leverages a collection of three compact CNNs and Gabor Wavelets (GW) to acquire a comprehensive feature vector consisting of spatial–textural–frequency attributes. SCaLiNG gathers a wide range of image details by breaking down these photos into multiple directional sub-bands using GW, and then learning several CNNs using those sub-bands and the original picture. SCaLiNG also combines attributes taken from various CNNs trained with the actual images and subbands derived from GW. This fusion process correspondingly improves diagnostic accuracy due to the thorough representation of attributes. Furthermore, SCaLiNG applies a feature selection approach which further enhances the model's performance by choosing the most distinguishing features. Experimental findings indicate that SCaLiNG maintains a classification accuracy of 0.9170 in categorising SC subcategories, surpassing conventional single-CNN models. The outstanding performance of SCaLiNG underlines its ability to aid dermatologists in swiftly and precisely recognising and classifying SC, thereby enhancing patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Circulating tumour DNA (ctDNA) is a subset of cell free DNA (cfDNA) released by tumour cells into the bloodstream. Circulating tumour DNA has shown great potential as a biomarker to inform treatment in cancer patients. Collecting ctDNA is minimally invasive and reflects the entire genetic makeup of a patient's cancer. ctDNA variants in NGS data can be difficult to distinguish from sequencing and PCR artefacts due to low abundance, particularly in the early stages of cancer. Unique Molecular Identifiers (UMIs) are short sequences ligated to the sequencing library before amplification. These sequences are useful for filtering out low frequency artefacts. The utility of ctDNA as a cancer biomarker depends on accurate detection of cancer variants. Results: In this study, we benchmarked six variant calling tools, including two UMI-aware callers for their ability to call ctDNA variants. The standard variant callers tested included Mutect2, bcftools, LoFreq and FreeBayes. The UMI-aware variant callers benchmarked were UMI-VarCal and UMIErrorCorrect. We used both datasets with known variants spiked in at low frequencies, and datasets containing ctDNA, and generated synthetic UMI sequences for these datasets. Variant callers displayed different preferences for sensitivity and specificity. Mutect2 showed high sensitivity, while returning more privately called variants than any other caller in data without synthetic UMIs – an indicator of false positive variant discovery. In data encoded with synthetic UMIs, UMI-VarCal detected fewer putative false positive variants than all other callers in synthetic datasets. Mutect2 showed a balance between high sensitivity and specificity in data encoded with synthetic UMIs. Conclusions: Our results indicate UMI-aware variant callers have potential to improve sensitivity and specificity in calling low frequency ctDNA variants over standard variant calling tools. There is a growing need for further development of UMI-aware variant calling tools if effective early detection methods for cancer using ctDNA samples are to be realised. [ABSTRACT FROM AUTHOR]

PURPOSE: Cancer of unknown primary (CUP) is a syndrome comprising metastatic cancers without a clinically identified primary site. Although patients with CUP have an unfavorable prognosis, treatment with site-specific therapies guided by clinical features, standard pathology, and molecular assays can improve overall survival. The 92-gene assay (CancerTYPE ID) is a gene expression–based classifier that helps identify the tissue of origin for metastatic cancers with unknown or uncertain diagnoses. This study reports the frequency of selected molecular aberrations of oncogenes, including KRAS , IDH1/2 , BRCA1/2 , and BRAF , in patients with CUP in the MOSAIC database to highlight potential treatment options. METHODS: MOSAIC is a database of patients with CUP submitted for CancerTYPE ID testing and NeoTYPE biomarker testing. Tumor biopsy samples were analyzed by CancerTYPE ID for tumor type identification and further tested for molecular aberrations of oncogenes, including KRAS , IDH1/2 , BRCA1/2 , and BRAF. RESULTS: CancerTYPE ID identified a specific tumor type in 92.5% (2,929 of 3,168) of CUP cases in the MOSAIC database. The most commonly identified histological type was adenocarcinoma (75.4%), with pancreaticobiliary being the most common molecularly diagnosed cancer (24.9%). Aberrations in KRAS , IDH1/2 , BRCA , and BRAF genes were identified in 18.8% (n = 597) of biopsies. A cancer-specific US Food and Drug Administration (FDA)–approved or investigational targeted therapy was potentially available for 24.6% (n = 147) of these patients. CONCLUSION: This retrospective analysis supports incorporating CancerTYPE ID into the evaluation for patients with CUP to help determine the tissue of origin and identify actionable genetic alterations. This approach may allow more patients with CUP to benefit from site-specific FDA-approved targeted therapies or enrollment into clinical trials. Enabling Precision Site-Specific Therapies in CUP Patients with CancerTYPE ID [ABSTRACT FROM AUTHOR]

Motivation: There exists an unexplained diverse variation within the predefined colon cancer stages using only features from either genomics or histopathological whole slide images as prognostic factors. Unraveling this variation will bring about improved staging and treatment outcomes. Hence, motivated by the advancement of Deep Neural Network (DNN) libraries and complementary factors within some genomics datasets, we aggregate atypia patterns in histopathological images with diverse carcinogenic expression from mRNA, miRNA and DNA methylation as an integrative input source into a deep neural network for colon cancer stages classification, and samples stratification into low or high-risk survival groups. Results: The genomics-only and integrated input features return Area Under Curve–Receiver Operating Characteristic curve (AUC-ROC) of 0.97 compared with AUC-ROC of 0.78 obtained when only image features are used for the stage's classification. A further analysis of prediction accuracy using the confusion matrix shows that the integrated features have a weakly improved accuracy of 0.08% more than the accuracy obtained with genomics features. Also, the extracted features were used to split the patients into low or high-risk survival groups. Among the 2,700 fused features, 1,836 (68%) features showed statistically significant survival probability differences in aggregating samples into either low or high between the two risk survival groups. Availability and Implementation:https://github.com/Ogundipe-L/EDCNN [ABSTRACT FROM AUTHOR]

Background: Carcinosarcoma is a rare esophageal tumor, accounting for approximately 0.27-2.8% of malignant esophageal tumors. This study aims to investigate the clinical pathological characteristics, surgical treatment outcomes, and analysis of prognostic factors in esophageal carcinosarcoma (ECS). Methods: Clinical data from sixteen patients diagnosed with esophageal sarcomatoid carcinoma who underwent surgical interventions were retrospectively analyzed. Clinical and pathological features, treatment modalities, and postoperative outcomes were systematically examined. Results: Out of the 1261 patients who underwent surgical treatment for esophageal cancer, 16 cases were pathologically confirmed as carcinosarcoma. Among them, two underwent neoadjuvant chemotherapy, six received postoperative chemotherapy. Carcinosarcomas predominantly occurred in the middle (43.75%) and lower (50%) segments of the esophagus. Among the 16 cases, 10 presented as polypoid, 4 as ulcerative, and 2 as medullary types. Microscopic examination revealed coexistence and transitional transitions between sarcomatous and carcinoma components. Pathological staging showed 5 cases in stage T1, 2 in stage T2, and 9 in stage T3, with lymph node metastasis observed in 8 cases (50%). TNM staging revealed 2 cases in stage I, 9 in stage II, and 5 in stage III. The overall 1, 3, and 5-year survival rates were 86.67%, 62.5%, and 57.14%, respectively. Univariate analysis indicated that pathological N staging influenced survival rates, while multivariate analysis demonstrated that pathological N staging was an independent prognostic factor. Conclusions: Carcinosarcoma is a rare esophageal tumor, accounting for approximately 0.27-2.8% of malignant esophageal tumors. Histologically, the biphasic pattern is a crucial diagnostic feature, although the carcinomatous component may not always be evident, especially in limited biopsies, leading to potential misclassification as pure sarcoma or squamous cell carcinoma. Despite its large volume and cellular atypia, carcinosarcoma carries a favorable prognosis. Complete surgical resection of the tumor and regional lymph node dissection is the preferred treatment approach for esophageal carcinosarcoma. [ABSTRACT FROM AUTHOR]

Aim: This study aimed to determine which factors improve the quality of dying and death from the point of view of patients with cancer who are nearing the end of their lives. The goal was to find out what they think are necessary conditions for a good death and how they would like to be cared for and supported at the end of their lives. Methods: This study used an exploratory research approach. Purposive sampling was used to select 21 participants from two hospices in Bengaluru and Hyderabad (Karunashraya and Sparsh), and Karnataka Cancer Hospital in Bangalore, India. Semi-structured interviews were undertaken to obtain data from the patients. Thematic analysis was used to examine the data. Results: Four themes were identified: 1) Spirituality and religiosity, 2) socioemotional support, 3) Breaking silence about the stage of the disease and 4) Preparation for and embracing death. There were distinct sub-themes within some of these that were highlighted using quotes from the participants. Conclusions: The study provided a comprehensive understanding of end-of-life care, the criteria for a high-quality end of life, strategies for achieving it, and the quality of the dying process and death in advanced cancer patients. Studying patients' experiences will help inform a more robust intervention strategy and action plan to improve the quality of end-of-life care in the Indian community. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to examine the prevalence of cognitivecommunication deficits in adult cancer survivors who reported experiencing cancer-related cognitive impairment (CRCI). The study also aimed to determine how these problems impact their ability to engage socially and find satisfaction in their social roles. Method: This study employed a cross-sectional survey to collect data from adult cancer survivors. The survey included questions on demographic characteristics, self-perceived cognitive-communication abilities, social engagement, and satisfaction with social participation. Data analysis included descriptive statistics, Spearman rank-order correlation, Mann-Whitney U tests, and Kruskal-Wallis H tests. Results: Of 172 participants, 78% completed the survey, with 109 selfreporting CRCI. The participants predominantly had breast cancer, and most were diagnosed with Stage II cancers. The results indicated self-perceived impairment in various cognitive-communication domains, with functional daily communication being the most affected. Participants reported more difficulty participating in social roles and activities than their overall satisfaction with social participation. This study explored the relationships between cognitivecommunication scores and social engagement, considering variables such as education, cancer type, stage, age, and treatment. Conclusions: This study underscores the multidimensional nature of CRCI, emphasizing the importance of addressing both cognitive-communication and social aspects in interventions and support services. It highlights the clinical implications for speech-language pathology, suggesting a potential role in identifying and addressing cognitive-communication deficits. Future research needs are discussed. [ABSTRACT FROM AUTHOR]

Endometrial cancer (EC) is a complex disease with various subtypes. Although it is considered a treatable disease due to early diagnosis and symptoms, the advanced stage, which represents approximately 8% of cases, is associated with poor outcomes, reflecting the absence of efficient systemic therapy. There are various molecular classifications available and many pathways involved in EC pathogenesis. Advances in understanding its biology have led to the development of a classification system to help tailor treatment strategies depending on both patients and disease features. Currently, immunotherapy and targeted therapies are key treatments for EC, whether recurrent or advanced. In this review, we aim to summarize the molecular classification of EC briefly and its impact on treatment strategies, as well as the proposed targeted therapy. The data collection is based on searches on scientific websites, clinical trials (ClinicalTrials.gov), and international guidelines from Europe's leading medical oncology society (ESMO) and the National Comprehensive Cancer Network (NCCN). [ABSTRACT FROM AUTHOR]

Endometrial cancer (EC) is a complex disease with various subtypes. Although it is considered a treatable disease due to early diagnosis and symptoms, the advanced stage, which represents approximately 8% of cases, is associated with poor outcomes, reflecting the absence of efficient systemic therapy. There are various molecular classifications available and many pathways involved in EC pathogenesis. Advances in understanding its biology have led to the development of a classification system to help tailor treatment strategies depending on both patients and disease features. Currently, immunotherapy and targeted therapies are key treatments for EC, whether recurrent or advanced. In this review, we aim to summarize the molecular classification of EC briefly and its impact on treatment strategies, as well as the proposed targeted therapy. The data collection is based on searches on scientific websites, clinical trials (ClinicalTrials.gov), and international guidelines from Europe's leading medical oncology society (ESMO) and the National Comprehensive Cancer Network (NCCN). [ABSTRACT FROM AUTHOR]

Macrophages, pivotal components of the immune system, orchestrate host defense mechanisms in humans and mammals. Their polarization into classically activated macrophages (CAMs or M1) and alternatively activated macrophages (AAMs or M2) dictates distinct functional roles in immunity and tissue homeostasis. While the negative regulatory role of CD32b within the FC gamma receptor (FCγR) family is recognized across various immune cell types, its influence on macrophage polarization remains elusive. This study aimed to elucidate the regulatory role of CD32b in macrophage polarization and discern the differential expression markers between the M1 and M2 phenotypes following CD32b siRNA transfection. The results revealed a decrease in the CD32b levels in lipopolysaccharide (LPS)-treated M1 and an increase in interleukin-4 (IL-4)-treated M2 macrophages, as observed in macrophage Raw264.7 cells. Furthermore, CD32b siRNA transfection significantly downregulated the M2 markers (IL-10, VEGF, Arg-1, and STAT6), while upregulating the M1 markers (IL-6, NF-κB, NOS2, and STAT1) in the Raw264.7 cells. Similar findings were recapitulated in macrophage-rich adherent cells isolated from mouse spleens. Additionally, the cytopathological analysis of pleural effusions and ascitic fluids from patients with cancer revealed a positive correlation between advanced tumor stages, metastasis, and elevated CD32b levels. In conclusion, this study highlights the regulatory influence of CD32b in suppressing M1 expression and promoting M2 polarization. Moreover, heightened M2 activation and CD32b levels appear to correlate with tumor progression. A targeted CD32b blockade may serve as a novel therapeutic strategy to inhibit M2 macrophage polarization and is promising for anti-tumor intervention. [ABSTRACT FROM AUTHOR]

Invasive cribriform carcinoma (ICC) is a type of malignant tumor with slow growth and good prognosis. The study was a single center retrospective study. The percentage of ICC among patients diagnosed with breast cancer was 0.3% (8/2454 patients). All patients tested positive for estrogen or progesterone receptors and 12.5% (1/8) patients tested positive for human epidermal growth factor receptor type2 (HER2). The present study suggests that the clinicopathological features of ICC are low-grade hormone receptor-positive luminal type with a good prognosis. However, some patients were HER2-positive and require careful follow-up. [ABSTRACT FROM AUTHOR]

Background: The National Comprehensive Cancer Network (NCCN)-recommended treatment for patients with borderline-resectable pancreatic cancer (BRPC) and locally advanced pancreatic cancer (LAPC) involves a combination of neoadjuvant FOLFIRINOX chemotherapy and the curative surgical resection of the tumor. This study seeks to identify the clinical, radiological, laboratory, and pathologic predictors that can anticipate the oncological outcomes of patients. Methods: In this study, we conducted a retrospective analysis of patients who had undergone curative surgical resection for BRPC, LAPC, or resectable disease with high-risk features after receiving neoadjuvant FOLFIRINOX at two institutions. We evaluated by means of multivariate analysis whether clinical and laboratory response, tumor markers, radiological response, and pathologic tumor response grade correlated with overall survival (OS) and disease-free survival (DFS). Results: The study enrolled a total of 70 patients with BRPC, LAPC, and resectable disease with high-risk features who underwent resection after neoadjuvant FOLFIRINOX. Age above 65 years and fewer than nine cycles of chemotherapy (OR 4.2; 95% CI 1.4–12.0; p-value 0.007); locally advanced tumors after neoadjuvant treatment (NAT) (OR 7.0; 95% CI 1.9–25.7; p-value 0.003); and lymph node disease and histological tumor regression grade 2 and 3 (OR 4.3; 95% CI 0.9–19.2; p-value 0.05) were risk factors linked to adverse OS and DFS. The median OS and DFS were 33 (22–43.9) months and 16.5 (11.3–21.6) months, respectively. Conclusions: Classification as a LA tumor after NAT was the only preoperative radiological factor that predicted adverse survival in patients undergoing curative surgery after NAT. Other clinical, biochemical, and radiological measures of response were not found to predict OS. Patient age, the cumulative administration of more than eight cycles of chemotherapy, and a significant pathological response were associated with better OS. The results of this study are important for treatment decision-making and prognostication in patients with BRPC and LAPC. [ABSTRACT FROM AUTHOR]

Simple Summary: This study focuses on Stage IIIA-N2 non-small cell lung cancer (NSCLC), which occurs when lung cancer has spread to lymph nodes in the centre of the chest but not to distant parts of the body. This type of cancer is difficult to treat, and survival rates remain low despite advances in therapy. The research is based on real-world data from Guy's Thoracic Cancer Database and aims to enhance our understanding of patient outcomes and identify important factors that impact survival and disease progression. By examining various treatment strategies, the study aims to offer insights that could help tailor treatment approaches to individual patients. The findings underscore the need for personalised care and the potential benefits of incorporating newer therapeutic options, ultimately leading to better survival outcomes for patients with this challenging form of lung cancer. Background: Stage IIIA-N2 non-small cell lung cancer (NSCLC) poses a significant clinical challenge, with low survival rates despite advances in therapy. The lack of a standardised treatment approach complicates patient management. This study utilises real-world data from Guy's Thoracic Cancer Database to analyse patient outcomes, identify key predictors of overall survival (OS) and disease-free survival (DFS), and address the limitations of randomised controlled trials. Methods: This observational, single-centre, non-randomised study analysed 142 patients diagnosed with clinical and pathological T1/2 N2 NSCLC who received curative treatment from 2015 to 2021. Patients were categorised into three groups: Group A (30 patients) underwent surgery for clinical N2 disease, Group B (54 patients) had unsuspected N2 disease discovered during surgery, and Group C (58 patients) received radical chemoradiation or radiotherapy alone (CRT/RT) for clinical N2 disease. Data on demographics, treatment types, recurrence, and survival rates were analysed. Results: The median OS for the cohort was 31 months, with 2-year and 5-year OS rates of 60% and 30%, respectively. Group A had a median OS of 32 months, Group B 36 months, and Group C 25 months. The median DFS was 18 months overall, with Group A at 16 months, Group B at 22 months, and Group C at 17 months. Significant predictors of OS included ECOG performance status, lymphovascular invasion, and histology. No significant differences in OS were found between treatment groups (p = 0.99). Conclusions: This study highlights the complexity and diversity of Stage IIIA-N2 NSCLC, with no single superior treatment strategy identified. The findings underscore the necessity for personalised treatment approaches and multidisciplinary decision-making. Future research should focus on integrating newer therapeutic modalities and conducting multi-centre trials to refine treatment strategies. Collaboration and ongoing data collection are crucial for improving personalised treatment plans and survival outcomes for Stage IIIA-N2 NSCLC patients. [ABSTRACT FROM AUTHOR]

Simple Summary: Plasmacytoid urothelial carcinoma (PUC) is a rare and aggressive histologic subtype of urothelial carcinoma of the bladder (BC) with high rates of upstaging and metastases. The aim of our study was to characterize treatment patterns and outcomes using a large national database and our institutional experiences, combating the challenge posed by the rarity of this variant. We demonstrated that, despite an improved pT0 rate associated with NAC, there remains an inconclusive overall survival increase. Additionally, PUC demonstrated a high predilection for peritoneal metastasis, further highlighting the need for investigation into more effective and subtype-tailored treatment options. Background: Plasmacytoid urothelial carcinoma (PUC) is a rare histologic subtype of urothelial carcinoma of the bladder (BC). Our objective was to characterize treatment patterns and outcomes of PUC in the NCDB and our recent institutional experience. Methods: The NCDB was queried for localized PUC cases between 2004 and 2020. Patients with PUC from a single institution (Yale School of Medicine) were also incorporated from 2021 onwards to not double-count patients. The primary outcomes were overall survival and treatment trends. Results: A total of 146 patients were included, 123 from NCDB and 23 from Yale. The median overall survival (mOS) was 28 [IQR 7.5, 50.3] months, 23 [IQR 8.4, 46.3] months for the NCDB patients, and 36 [IQR 4.3, 68.1] for the Yale patients. The mOS for patients receiving neoadjuvant chemotherapy (NAC) was 60.0 [28.0, 91.9] vs. 14.8 months [0, 34.3] for patients without NAC, p = 0.038, though the benefit was not preserved in a Cox proportional hazard analysis incorporating the clinical stage, receipt of NAC, and age. The peritoneum was the most common site of metastasis (78.3%), followed by the liver and bones. Conclusion: Our findings underscore the formidable challenge posed by PUC, emphasizing its limited response to current therapies. Despite higher pT0 rates with NAC, the OS benefit remains inconclusive, highlighting the need for more effective treatments. [ABSTRACT FROM AUTHOR]

Simple Summary: We aimed to evaluate the role of adjuvant chemotherapy in patients who undergo pneumonectomy for pN1 NSCLC. We found no significant differences after 5 years between two cohorts (adjuvant CT and no adjuvant CT) in terms of the overall survival (p: 0.31), cancer-specific survival (p: 0.59), disease-free survival (p: 0.94), and relapse rate (p: 0.76). Patients with pN1 NSCLC that was completely resected through pneumonectomy and radical lymphadenectomy may represent a particular cohort, which could be strictly followed up without adjuvant chemotherapy. Introduction: We aimed to assess our 25-year experience in order to evaluate the role of adjuvant chemotherapy in patients who undergo pneumonectomy for pN1 NSCLC. Materials and Methods: We retrospectively reviewed the outcomes and medical records of patients undergoing pneumonectomy for NSCLC with pathological diagnosis of pN1, excluding all patients who underwent neoadjuvant treatment. We compared patients treated with adjuvant chemotherapy with patients who did not undergo neoadjuvant treatment during a follow-up soon after surgery. Gray's test was used to assess differences in the cumulative incidence of relapse or CSS between the different groups. Kaplan–Meier methods were used for drawing overall survival (OS) plots. In order to assess differences in survival between the groups, the log-rank test was used. The cumulative incidence of relapse, CSS, and OS were calculated at 1, 2, 3, 4, and 5 years of follow-up. Results: The 30-day and 90-day mortality rates of our cohort were 6% and 11,6%. Excluding the first three months after surgery (deaths linked to postoperative comorbidity), after 5 years we found no significant differences between the two cohorts (adjuvant CT and no adjuvant CT) in terms of the overall survival (OS) (p: 0.31), cancer-specific survival (CSS) (p: 0.59), disease-free survival (DFS) (p: 0.94), and relapse rate (p: 0.76). Conclusions: Patients with pN1 NSCLC that was completely resected through pneumonectomy and radical lymphadenectomy may represent a particular cohort, which could be strictly followed up without adjuvant chemotherapy. [ABSTRACT FROM AUTHOR]

Simple Summary: This research aims to explore the role of the TSGA10 protein in cancer development, specifically in how it might influence the growth and spread of cancer cells. Scientists are particularly interested in TSGA10 because it is found in both normal reproductive tissues and cancer cells, yet seems to slow down cancer progression. The key question is why cancer cells would produce a protein that could hinder their own survival. To investigate this, the authors propose several hypotheses about how TSGA10 might be involved in carcinogenesis. They will analyze both published and unpublished studies and data to understand how TSGA10 functions at different stages of cancer. By uncovering these mechanisms, this research could lead to new targeted therapies that use TSGA10 to combat cancer more effectively, offering fresh insights and potential breakthroughs in cancer treatment. Cancer-specific antigens have been a significant area of focus in cancer treatment since their discovery in the mid-twentieth century. Cancer germline antigens are a class of antigens specifically overexpressed in germline tissues and cancer cells. Among these, TSGA10 (testis-specific gene antigen 10) is of great interest because of its crucial impact on cancer progression. Early studies explored TSGA10 expression in a variety of cancer types. More recent studies revealed that TSGA10 can suppress tumor progression by blocking cancer cell metabolism, angiogenesis, and metastasis. An open question regarding the TSGA10 is why cancer cells must express a protein that prevents their progression. To answer this question, we conducted a comprehensive review to engage the TSGA10 in the context of the current understanding of "malignant transformation". This review demonstrated that TSGA10 expression level in cancer cells depends on the cancer stage across malignant transformation. In addition, we evaluated how TSGA10 expression can prevent the "cancer hallmarks". Given this information, TSGA10 can be of great interest in developing effective targeted anti-cancer therapies. [ABSTRACT FROM AUTHOR]

Simple Summary: The YAP/TAZ signaling pathways, which is involved in tumor development and proliferation in a variety of solid tumors, inhibits hypoxia-induced cell death, increases and stabilizes angiogenesis, and activates tumor proliferation, both independently and in conjunction with HIF in hypoxic tumors. It also promotes tumor metastasis by regulating different TME environments. Therefore, understanding the activity of YAP/TAZ as a mechanism of tumor development may lead to the development of novel therapeutic strategies. In solid tumors such as hepatocellular carcinoma (HCC), hypoxia is one of the important mechanisms of cancer development that closely influences cancer development, survival, and metastasis. The development of treatments for cancer was temporarily revolutionized by immunotherapy but continues to be constrained by limited response rates and the resistance and high costs required for the development of new and innovative strategies. In particular, solid tumors, including HCC, a multi-vascular tumor type, are sensitive to hypoxia and generate many blood vessels for metastasis and development, making it difficult to treat HCC, not only with immunotherapy but also with drugs targeting blood vessels. Therefore, in order to develop a treatment strategy for hypoxic tumors, various mechanisms must be explored and analyzed to treat these impregnable solid tumors. To date, tumor growth mechanisms linked to hypoxia are known to be complex and coexist with various signal pathways, but recently, mechanisms related to the Hippo signal pathway are emerging. Interestingly, Hippo YAP/TAZ, which appear during early tumor and normal tumor growth, and YAP/TAZ, which appear during hypoxia, help tumor growth and proliferation in different directions. Peculiarly, YAP/TAZ, which have different phosphorylation directions in the hypoxic environment of tumors, are involved in cancer proliferation and metastasis in various carcinomas, including HCC. Analyzing the mechanisms that regulate the function and expression of YAP in addition to HIF in the complex hypoxic environment of tumors may lead to a variety of anti-cancer strategies and combining HIF and YAP/TAZ may develop the potential to change the landscape of cancer treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Studies analyzing specific treatment-related prognostic factors can provide important information about disease biology and improve the use of biomarkers to optimize treatment decisions. The aim of our retrospective study was to determine the prognostic performance of clinicopathological factors and blood biomarkers in patients with unresectable metastatic melanoma treated with BRAF and MEK inhibitors. A total of 199 patients were included in the multivariate analysis of the risk of progression and death. We found that primary tumor localization on the limbs, Clark invasion level V, M1c stage or M1d stage at the start of therapy, and elevated baseline serum S100B level were independently and significantly associated with poor outcomes. The present study suggests that clinicopathological factors, including primary tumor characteristics and stage of metastatic disease, as well as serum markers may provide information on the probability of survival in patients with advanced melanoma treated with BRAF and MEK inhibitors. Prognostic studies can provide important information about disease biology and improve the use of biomarkers to optimize treatment decisions. Methods: A total of 199 patients with advanced melanoma treated with BRAF + MEK inhibitors were included in our single-center retrospective study. We analyzed the risk of progression and death using multivariate Cox proportional hazard models. The predictive effect of prognostic factors on progression-free survival (PFS) was evaluated in ROC analysis. Results: We found that primary tumor localization, Clark level, pT category, baseline M stage and baseline serum S100B are independent and significant prognostic factors for PFS. The discriminative power of the combination of these factors was excellent for predicting 18 month PFS (AUC 0.822 [95% CI 0.727; 0.916], p < 0.001). Primary tumor localization on the extremities, Clark level V, baseline M1c stage or M1d stage, and elevated baseline serum S100B and LDH levels were independently and significantly associated with unfavorable overall survival (OS). Conclusion: Baseline M stage and serum S100B appear to be independent prognostic factors for both PFS and OS in melanoma patients treated with BRAF + MEK inhibitors. We newly identified significant and independent prognostic effects of primary tumor localization and Clark level on survival that warrant further investigation. [ABSTRACT FROM AUTHOR]

Simple Summary: Total thyroidectomy and dissection of cervical lymph node compartments, depending on serum calcitonin levels and ultrasound findings, is standard treatment for patients with medullary thyroid cancer. The aim of this study was to evaluate whether pre-operative calcitonin and CEA levels can be useful as biomarkers of the extent of lymph node metastases at diagnosis. Results indicate that pre-operative serum calcitonin and CEA levels can predict presence, number, and site of lymph node metastases and, more specifically, values of 90 pg/mL for calcitonin and 17 ng/mL for CEA accurately indicate the N1b status. Since surgery is the only curative treatment for medullary thyroid cancer and there is not a strong indication regarding the extent of lymphadenectomy, these findings may help in the choice of the extent of neck dissection. Background: In medullary thyroid cancer (MTC), lymph node metastases are often present at diagnosis and the extent of surgery is usually based upon pre-operative calcitonin and CEA levels as well as ultrasound findings. The aim of this study was to evaluate the role of pre-operative calcitonin and CEA levels as predictive markers of the burden of lymph node metastases at diagnosis. Methods: we conducted a retrospective study analyzing 87 MTC patients. Results: The median levels of calcitonin and CEA were 88.4 pg/mL and 7.0 ng/mL, respectively, in patients with no lymph nodes metastases; 108.0 pg/mL and 9.6 ng/mL, respectively, in patients with metastases to 1–5 lymph nodes; 520.5 pg/mL and 43.2 ng/mL, respectively, in patients with metastases to >5 lymph nodes. There were no significant differences in pre-operative calcitonin and CEA values between N0 and N1a patients, whereas they were significantly higher in N1b patients. Pre-operative cut-off levels distinguishing N0/N1a from N1b patients were 90 pg/mL for calcitonin (sensitivity 100%, specificity 59.3%, AUC = 0.82) and 17 ng/mL for CEA (sensitivity 100%, specificity 75%, AUC = 0.89). Conclusions: in patients with MTC, pre-operative serum calcitonin and CEA levels may drive the decision-making process to better define the extent of surgery. [ABSTRACT FROM AUTHOR]

Simple Summary: With the aim of offering precision medicine to our patients, accurate lymph node staging of head and neck (HN) cancer patients is a major challenge, as it determines whether neck dissection is indicated. For many years, the indication for this surgery has been histological predictors from the primary tumor only, and efforts are converging to develop non-invasive techniques to exclude occult metastases with certainty. FDG PET-CT plays a dominant role in this respect. The aim of our systematic review and meta-analysis was to determine the overall diagnostic performance of FDG PET-CT for the detection of LN metastases from HN squamous cell carcinoma (HNSCC) in patients with clinically node-negative necks. Because of an estimated 20–30% prevalence of occult lymph node (LN) metastases in patients with head and neck squamous cell carcinoma (HNSCC), neck dissection is often proposed, despite its potential morbidity. In this systematic review and meta-analysis, the diagnostic performance of FDG PET-CT in detecting occult LN metastases was evaluated in patients with clinically negative necks (cN0) and in whom histopathology of a neck dissection specimen served as gold standard. Overall, 16 studies out of 2062 screened on PubMed and EMBASE fulfilled the inclusion criteria (n = 1148 patients). Seven of these sixteen studies were split into two or three studies because they contained data that could be processed distinctly in our meta-analysis. For this reason, a total of 25 studies were identified and included in the analysis (n total = 1918 patients). The overall prevalence of metastatic nodes per patient was 22.67%. The pooled sensitivity, specificity, diagnostic odds ratios, and negative predictive value (NPV) were 0.71 (95%CI: 0.66–0.75), 0.90 (95%CI: 0.84–0.93), 20.03 (95%CI: 13.51–29.70), and 0.92 (95%CI: 0.89–0.95), respectively. The main causes of inter-study heterogeneity included different reference standards (evaluation per patient, per neck side, or per neck level). The current meta-analysis showed that FDG PET-CT has a high specificity and NPV for ruling out nodal involvement in cN0 necks, but a limited sensitivity. [ABSTRACT FROM AUTHOR]

Simple Summary: Definitive radiotherapy (RT) with androgen deprivation therapy is the standard of care for high- or very high-risk locoregional prostate cancer. Despite various randomized trials, the optimal RT strategy is undefined. Practices in the selection for whole pelvic radiotherapy (WPRT), RT doses and techniques are considerably heterogeneous. Image-guided radiotherapy (IGRT) techniques have emerged to allow for precise dose prescription. The current study reports on the 5-year institutional experience of definitive volumetric modulated arc therapy using a standardized strategy of WPRT based on the estimated nodal risk, as well as simultaneous integrated boost to the involved nodes in the context of contemporary staging and RT techniques. An analysis of 209 patients demonstrated excellent clinical outcomes. Initial PSMA PET-CT compared to conventional imaging staging was associated with better biochemical relapse-free survival in patients with ISUP grade group 5 disease. These results suggest the approach of modern IGRT and the risk-adapted use of PSMA PET-CT staging and nodal irradiation in real-world clinical practice. This study retrospectively evaluates the clinical outcomes of definitive volumetric modulated arc therapy (VMAT) for high-risk or very high-risk locoregional prostate cancer patients from an Asian institution. Consecutive patients who received VMAT (76 Gy in 38 fractions) between January 2017 and June 2022 were included. Whole pelvic radiotherapy (WPRT) (46 Gy in 23 fractions) was employed for clinically node-negative disease (cN0) and a Roach estimated risk of ≥15%, as well as simultaneous integrated boost (SIB) of 55–57.5 Gy to node-positive (cN1) disease. The primary endpoint was biochemical relapse-free survival (BRFS). Secondary endpoints included radiographic relapse-free survival (RRFS), metastasis-free survival (MFS) and prostate cancer-specific survival (PCSS). A total of 209 patients were identified. After a median follow-up of 47.5 months, the 4-year actuarial BRFS, RRFS, MFS and PCSS were 85.2%, 96.8%, 96.8% and 100%, respectively. The incidence of late grade ≥ 2 genitourinary (GU) and gastrointestinal (GI) toxicity were 15.8% and 11.0%, respectively. No significant difference in cancer outcomes or toxicity was observed between WPRT and prostate-only radiotherapy for cN0 patients. SIB to the involved nodes did not result in increased toxicity. International Society of Urological Pathology (ISUP) group 5 and cN1 stage were associated with worse RRFS (p < 0.05). PSMA PET-CT compared to conventional imaging staging was associated with better BRFS in patients with ISUP grade group 5 (p = 0.039). Five-year local experience demonstrates excellent clinical outcomes. PSMA PET-CT staging for high-grade disease and tailored pelvic irradiation based on nodal risk should be considered to maximize clinical benefit. [ABSTRACT FROM AUTHOR]

Simple Summary: This study examined the outcomes of patients with gallbladder cancer over 20 years in Saskatchewan, Canada, focusing on geographic, demographic, and clinical factors. A total of 331 patients diagnosed between 2000 and 2019 were included. The majority (64%) had advanced stage 4 disease, with a significant proportion (66%) being rural residents. Key factors associated with poorer overall survival included stage 4 disease, lack of surgery, older age, a higher neutrophil-to-lymphocyte ratio, and no referral to a regional cancer center. Among early-stage patients, stage III disease and urban residence were associated with worse disease-free survival. The findings highlight the late-stage diagnosis and referral challenges impacting the outcomes of gallbladder cancer. Background: Gallbladder cancer (GBC) is an uncommon cancer. This study aimed to determine the outcomes of GBC in relation to geographic, demographic, and clinical factors in a Canadian province from 2000 to 2019. Methods: This population-based retrospective cohort study included all patients diagnosed with gallbladder cancer (GBC) in Saskatchewan, Canada, from 2000 to 2019. Cox proportional multivariate regression analysis was conducted to identify factors associated with poorer outcomes. Results: In total, 331 patients with a median age of 74 years and male–female ratio of 1:2 were identified. Of these patients, 305 (92%) had a pathological diagnosis of GBC. Among patients with documented staging data, 64% had stage IV disease. A total of 217 (66%) patients were rural residents, and 149 (45%) were referred to a cancer center. The multivariate analysis for patients with stage I–III GBC showed that stage III disease [hazard ratio (HR), 2.63; 95% confidence interval (CI), 1.09–6.34)] and urban residence (HR, 2.20; 95% CI, 1.1–4.39) were correlated with inferior disease-free survival. For all patients, stage IV disease (HR, 3.02; 95% CI, 1.85–4.94), no referral to a cancer center (HR, 2.64; 95% CI, 1.51–4.62), lack of surgery (HR, 1.63; 95% CI, 1.03–2.57), a neutrophil–lymphocyte ratio of >3.2 (HR, 1.57; 1.05–2.36), and age of ≥70 years (HR, 1.51; 95% CI, 1.04–2.19) were correlated with inferior overall survival. Conclusions: In this real-world context, the majority of patients with GBC were diagnosed at a late stage and were not referred to a cancer center. For those with early-stage GBC, living in an urban area and having stage III disease were linked to worse outcomes. Across all stages of GBC, stage IV disease, older age, absence of surgery, lack of referral to a cancer center, and a high neutrophil-to-lymphocyte ratio were associated with poorer survival. [ABSTRACT FROM AUTHOR]

Simple Summary: Magnetic resonance imaging (MRI) plays a crucial role in rectal cancer management, offering valuable information for staging, treatment response, and patient prognosis. MRI biomarkers, such as circumferential resection margin (CRM), extramural venous invasion (EMVI), tumour deposits, and MRI tumour regression grade (mrTRG) alongside functional imaging techniques such as diffusion-weighted imaging (DWI) and dynamic contrast enhancement (DCE) are essential in clinical decision-making. Additionally, emerging technologies like radiomics and artificial intelligence (AI) are showing promise in improving the precision of rectal cancer care. As the focus increasingly shifts toward non-invasive management, such as 'watch-and-wait' approach, this review discusses the role of predictive and prognostic MRI biomarkers in rectal cancer and how they integrate into everyday clinical practice. The role of magnetic resonance imaging (MRI) in rectal cancer management has significantly increased over the last decade, in line with more personalized treatment approaches. Total neoadjuvant treatment (TNT) plays a pivotal role in the shift from traditional surgical approach to non-surgical approaches such as 'watch-and-wait'. MRI plays a central role in this evolving landscape, providing essential morphological and functional data that support clinical decision-making. Key MRI-based biomarkers, including circumferential resection margin (CRM), extramural venous invasion (EMVI), tumour deposits, diffusion-weighted imaging (DWI), and MRI tumour regression grade (mrTRG), have proven valuable for staging, response assessment, and patient prognosis. Functional imaging techniques, such as dynamic contrast-enhanced MRI (DCE-MRI), alongside emerging biomarkers derived from radiomics and artificial intelligence (AI) have the potential to transform rectal cancer management offering data that enhance T and N staging, histopathological characterization, prediction of treatment response, recurrence detection, and identification of genomic features. This review outlines validated morphological and functional MRI-derived biomarkers with both prognostic and predictive significance, while also exploring the potential of radiomics and artificial intelligence in rectal cancer management. Furthermore, we discuss the role of rectal MRI in the 'watch-and-wait' approach, highlighting important practical aspects in selecting patients for non-surgical management. [ABSTRACT FROM AUTHOR]

Simple Summary: Sentinel lymph node (SLN) mapping is a crucial technique in the surgical treatment of cervical cancer, helping to identify the first lymph nodes that cancer may spread to. Indocyanine green (ICG) is a dye commonly used to make these lymph nodes visible during surgery, but there is no agreement on the best amount to use. This research reviews different amounts of ICG used in previous studies to determine the most effective dose for detecting these lymph nodes. By identifying the best practices, this study aims to improve the accuracy and safety of surgeries for cervical cancer patients. The findings could help standardize the use of ICG in clinical practice, leading to better outcomes for patients and providing clearer guidelines for surgeons. Over the past decade, SLN mapping has become increasingly important in cervical cancer surgery. ICG is the most commonly used tracer due to its high bilateral detection rates, ease of use, and safety. However, there is no consensus on the optimal ICG dose, leading to variability in outcomes. This systematic review aims to evaluate the impact of different ICG doses on SLN detection in early-stage cervical cancer, identifying the most effective and safe dose for clinical practice. A comprehensive search was conducted in MEDLINE/PubMed up to May 2024. Studies included assessed SLN mapping using ICG in stage IA2-IIA/IIB cervical cancer. Exclusions were applied to studies not reporting ICG dose or using multiple tracers without dose-specific results. Twelve studies were included, with ICG concentrations ranging from 0.25 mg/mL to 25 mg/mL and injection volumes from 1 to 10 mL. Overall SLN detection rates ranged from 88% to 100%, while bilateral detection rates varied between 74.1% and 98.5%. The most consistent results were obtained with an ICG concentration of 1.25 mg/mL and a 4 mL injection volume. In conclusion, an ICG concentration of 1.25 mg/mL with a 4 mL injection volume is recommended for effective SLN mapping in cervical cancer, achieving high detection rates with minimal variability. Standardizing this dose in clinical practice is suggested to improve reproducibility and outcomes. [ABSTRACT FROM AUTHOR]

Simple Summary: Adjuvant therapy with targeted therapy or immunotherapy has become the standard of care for fully resected stage III–IV melanoma. In this scenario, real-world data are needed to relate the actual effectiveness and safety of these regimens with the evidence provided in the clinical trials. This study provides clinicians and researchers with the results of an Italian single-center real-world experience on the use of adjuvant therapy in resected stage III–IV melanoma patients. Our findings confirm the real-world effectiveness and safety of adjuvant regimens, yet underscores the need for further research to explore biomarker-based predictors for relapse and to assess the translation of improved relapse-free survival into long-term overall survival benefit. This study was carried out at the Dermatologic Clinic of the University of Turin, Italy, to assess the effectiveness and safety of adjuvant therapy in patients who received either targeted therapy (TT: dabrafenib + trametinib) or immunotherapy (IT: nivolumab or pembrolizumab) for up to 12 months. A total of 163 patients participated, including 147 with stage III and 19 with stage IV with no evidence of disease. The primary outcomes were relapse-free survival (RFS), distant metastasis-free survival (DMFS), and overall survival (OS). At 48 months, both TT and IT approaches yielded comparable outcomes in terms of RFS (55.6–55.4%, p = 0.532), DMFS (58.2–59.8%, p = 0.761), and OS (62.4–69.5%, p = 0.889). Whilst temporary therapy suspension was more common among TT-treated patients compared to IT-treated individuals, therapy discontinuation due to adverse events occurred at comparable rates in both groups. Predictors of relapse included mitoses, lymphovascular invasion, ulceration, and positive sentinel lymph nodes. Overall, the proportion of BRAF-mutated patients receiving IT stood at 7.4%, lower than what was observed in clinical trials. [ABSTRACT FROM AUTHOR]

Background Soft tissue tumors are a diverse group of neoplasms that arise from the connective tissues, including muscles, fat, fibrous tissues, blood vessels, and peripheral nerves. These tumors can range from benign to malignant, and their accurate histopathological diagnosis is crucial for appropriate treatment planning and prognosis. The diversity in morphology and behavior of these tumors makes their histopathological evaluation both challenging and essential. Aim and Objectives The study aims to analyze the histopathological features of soft tissue tumors in order to classify them, determine their frequency, and correlate the findings with clinical parameters. Materials and Method This Observational study analyzed the histopathological records of patients diagnosed with soft tissue tumors over a period of one years at a tertiary care center. Specimens were obtained from surgical excisions and biopsies, followed by processing and staining using standard histological techniques. Tumors were classified according to the WHO classification of soft tissue tumors. Clinical data were reviewed, and correlations with histopathological findings were analyzed. Results A total of 60 cases of soft tissue tumors were reviewed, comprising 49 benign, 7 intermediate and 4 malignant tumors. The most common benign tumor was Adipocytic tumours, while the most frequent malignant tumor were undefferentiated. Histopathological analysis provided a definitive diagnosis in 95% of cases, with a significant correlation between histopathological findings and clinical presentation. Conclusion Histopathological analysis remains the gold standard for the diagnosis and classification of soft tissue tumors. Accurate histopathological evaluation is essential for effective clinical management and prognosis. [ABSTRACT FROM AUTHOR]

Introduction: Recurrence after microwave ablation (MWA) has not been extensively studied. We aimed to investigate the patterns, treatments, and survival of patients with hepatocellular carcinoma (HCC) who experienced early and late recurrence after MWA. Methods: This retrospective study included patients with HCC recurrence after MWA as the initial treatment from January 2008 to December 2021. Recurrence patterns, treatments, and outcomes between patients with early and late HCC recurrence were compared. Prognostic factors of post-recurrence survival (PRS) were identified by multivariable Cox regression analyses. Results: Among 222 patients, 128 developed early recurrence (≤2 years after MWA) and 94 had late recurrence (>2 years). Majority of the recurrent HCC were intrahepatic-only recurrence, within the Milan criteria, and received potentially curative treatment. No significant differences in the recurrence patterns, vascular invasion, tumor staging, post-recurrence treatments, or median PRS (35.0 vs. 33.0 months, p = 0.523) were identified between patients with early and late recurrence. Multivariable analyses suggested that multiple tumor number (hazard ratio [HR]: 1.54; 95% CI: 1.03–2.30, p = 0.038), extrahepatic recurrence (HR: 2.14, 95% CI: 1.16–3.92, p = 0.015), vascular invasion (HR: 2.37, 95% CI: 1.18–4.76, p = 0.038), and higher ALBI grade (HR: 2.18, 95% CI: 1.54–3.08, p < 0.001) were independent risk factors of worse PRS, while curative treatment after recurrence (HR: 0.59, 95% CI: 0.38–0.92, p = 0.020) was associated with better PRS. Conclusions: No differences in recurrence patterns, post-recurrence treatments, or PRS were found between HCC patients with early and late recurrence following MWA. Tumor burden and patients' liver function reserve should be considered to decide the optimal post-recurrence treatment after MWA. [ABSTRACT FROM AUTHOR]

Introduction: Few studies have investigated the prognostic factors for non-adenocarcinoma of the lung. We retrospectively evaluated the prognostic factors on the basis of histological type of non-adenocarcinoma of the lung treated by pulmonary resection. Methods: We enrolled 266 patients with non-adenocarcinoma of the lung in this retrospective study: 196 with squamous cell carcinoma (SCC) and 70 with non-SCC. Results: Relapse-free survival (RFS) did not differ significantly between SCC and non-SCC patients (p = 0.33). For SCC patients, RFS differed significantly between patients who underwent wedge resection and non-wedge resection (p < 0.01) and between patients with Clavien-Dindo grade ≥3a and 0–2 postoperative complications (p < 0.01). For non-SCC patients, RFS rates were significantly different in the groups divided at neutrophil-to-lymphocyte ratio = 2.40 (p = 0.02), maximum standardized uptake value (SUVmax) = 8.39 (p < 0.01), between patients with pathological stage (pStage) 0–I and with pStage more than II (p < 0.01). For SCC patients, male sex (p = 0.04), wedge resection (p = 0.01), and Clavien-Dindo grade ≥3a (p = 0.02) were significant factors for RFS in multivariate analysis. For non-SCC patients, neutrophil-to-lymphocyte ratio >2.40 (p < 0.01), SUVmax >8.39 (p = 0.01), and pStage ≥II (p = 0.03) were significant factors for RFS in multivariate analysis. Conclusion: RFS did not differ significantly differently between SCC and non-SCC patients. It is necessary to perform more than segmentectomy and to avoid severe postoperative complications for SCC patients. SUVmax might be an adaptation criterion of adjuvant chemotherapy for patients with non-adenocarcinoma and non-SCC of the lung. [ABSTRACT FROM AUTHOR]

Objective: We aimed to investigate the long-term surveillance outcomes (biochemical recurrance, survival) and adequacy of active surveillance criteria to detect low-risk prostate cancer patients who were eligible for active surveillance but underwent radical prostatectomy. Materials and Methods: Data of patients who underwent radical prostatectomy for prostate cancer between January 2005 and January 2019 were retrospectively evaluated. Upstaging, upgrading, surveillance periods, and survival status of patients with clinical stage T1c and T2a, serum prostate-specific antigen below 10 ng/mL, International Society of Urological Pathology grade 1, number of tumor-positive cores in biopsy 2 and below, tumor percentage in tumor-positive cores 50 and below were inclusion criteria for active surveillance. Results: The study included 606 patients. Of these patients, 184 (30.4%) met the inclusion criteria for active surveillance. Upgrading was detected in 77 (41.8%) patients and upstaging in 29 (15.8%) patients who met the criteria for active surveillance. The prostate-specific antigen (PSA) and PSA density values of the patients who met the active surveillance criteria were significantly lower than those of the other patients (p<0.05). The mean surveillance period was 127.6±49.6 (8-227) months, and 123 patients died during this period. Among them, 18 (3%) patients died because of related causes of prostate cancer. None of the patients who met the criteria for active surveillance died because of prostate cancer (p=0.018). Conclusion: No cancer-related deaths were observed in patients who is eligible for active surveillance but underwent radical prostatectomy. This may suggest that active surveillance criteria are suitable for detecting low-risk prostate cancer patients. [ABSTRACT FROM AUTHOR]

Objective: This paper aims to describe the 2023 update position paper on MRONJ developed by the Italian Societies of Oral Pathology and Medicine (SIPMO) and of Maxillofacial Surgery (SICMF). Methods: This is the second update following the 2013 and 2020 Italian position papers by the Expert panel, which is a representation of the two scientific societies (SIPMO and SICMF). The paper is based on an extensive analysis of the available literature from January 2003 to February 2020, and the subsequent review of literature conducted between March 2020 and December 2022 to include all new relevant published papers to confirm or modify the previous set of recommendations. Results: This position paper highlights the main issues of MRONJ on risk estimates, disease definition, diagnostic pathway, individual risk assessment, and the fundamental role of imaging in the diagnosis, classification, and management of MRONJ. Conclusion: The Expert Panel confirmed the MRONJ definition, the diagnostic work‐up, the clinical‐radiological staging system and the prophylactic drug holiday, as recognized by SIPMO‐SICMF; while, it presented novel indications regarding the categories at risk of MRONJ, the prevention strategies, and the treatment strategies associated with the therapeutic drug holiday. [ABSTRACT FROM AUTHOR]

Brain tumor classification is a significant issue in computer aided diagnosis to make a convenient treatment. Deep learning techniques are surpassing traditional brain tumor classification methods in the medical image field with advanced hardware technology. In this article, a novel classification framework has been proposed that includes pre-trained fine-tuned EfficientNet B7. The framework focuses on a multi-class classification problem to distinguish among three common types of brain tumors, i.e., gliomas, meningiomas, and pituitary tumors. The proposed classification framework is trained and tested using six optimization algorithms SGD, RMSProp, Adagrad, Adam, Adadelta, and Nadam using two classifiers softmax and support vector machine (SVM). The best performance achieved by Nesterov-accelerated adaptive moment estimation (Nadam) optimizer using softmax classifier with test accuracy 99 % , average precision 99.3 % , average recall 97.3 % and average F1-score 98 % which outperformed other state-of-the-art architectures on Figshare MRI image data set. The proposed framework has also been evaluated, and performance has been compared using two more publicly available standard four-class brain tumor MRI data sets. [ABSTRACT FROM AUTHOR]

Objective: To compare the peri‐operative outcomes of radical prostatectomy (RP) for locally advanced, node‐positive, and metastatic prostate cancer (PCa), as determined through pathological staging, using the American College of Surgeons National Surgical Quality Improvement Project. Methods: We identified RP procedures performed between 2019 and 2021. Patients were stratified by pathological staging to compare the effect of locally advanced disease (T3‐4), node positivity (N+) and metastasis (M+) vs localised PCa (T1‐2 N0 M0). Baseline demographics and 30‐day outcomes, including operating time, length of hospital stay (LOS), 30‐day mortality, readmissions, reoperations, major complications, minor complications and surgery‐specific complications, were compared between groups. Results: Pathological staging data were available for 9276 RPs. Baseline demographics were comparable. There was a slightly higher rate of minor complications in the locally advanced cohort, but no significant difference in major complications, 30‐day mortality, readmissions, or rectal injuries. Node positivity was associated with longer operating time, LOS, and some slightly increased rates of 30‐day complications. RP in patients with metastatic disease appeared to be similarly safe to RP in patients with M0 disease, although it was associated with a longer LOS and slightly increased rates of certain complications. Conclusions: For patients with pathologically determined locally advanced, node‐positive, and metastatic PCa, RP appears to be safe, and is not associated with significantly higher rates of 30‐day mortality or major complications compared to RP for localised PCa. This study adds to the growing body of literature investigating the role of RP for advanced PCa; further studies are needed to better characterise the risks and benefits of surgery in such patients. [ABSTRACT FROM AUTHOR]