Performances of preoperative CT scan to predict the pTN stage for MSI/dMMR localized colon cancers.

BACKGROUND: Neoadjuvant immunotherapy emerges as a promising strategy for patients with localized colon cancer (CC) harboring microsatellite instability/mismatch repair deficiency (MSI/dMMR). The aim of this study is to evaluate the concordance between clinical cTN stage assessed by preoperative computed tomography (CT) scan and pTN stage of MSI/dMMR CC. PATIENTS AND METHODS: Consecutive patients diagnosed for localized MSI/dMMR CC and treated with upfront surgery between 2013 and 2022 in two French centers were eligible. Two independent radiologists, blinded to pathological findings, reviewed all preoperative CT scans and assessed cTN stage, with a third radiologist reviewing discordant cases. Radiological predictive diagnostic accuracy for pT4 and pN+ (N+ = N1 or N2) were calculated. RESULTS: One hundred and thirteen patients were included (right CCs = 79%). CT scan diagnostic performances for pT4 were sensitivity (Se) = 33.3%; specificity (Sp) = 94.0%; positive predictive value (PPV) = 66.7%; and negative predictive value (NPV) = 79.6% and for pN+ were Se = 70.3%; Sp = 59.2%; PPV = 45.6%; and NPV = 80.4%. When pT-pN were combined, 37.5% of tumors identified as cT4 and/or cN+ were actually pT1-3 and pN0, and 23.1% of the pT4 and pN+ population was not identified as such radiologically. CONCLUSION: The ability of preoperative CT scan to predict pT and pN stages is limited for localized MSI/dMMR CCs. Reassessing neoadjuvant strategies' benefit-risk balance in this population is needed.

Identification of biomarkers associated with pathological tumor staging and their utility in the diagnosis and prognosis of prostate cancer.

OBJECTIVE: Pathological tumor (pT) staging plays a crucial role in prostate cancer (PCa) diagnosis. This study aimed to identify pT stage-associated biomarkers and explored their utility in PCa prognosis. METHODS: GSE69223 was used to identify potential targets differentially expressed between level 2 of pT staging (pT2) and level 3 of pT staging (pT3). Quantitative reverse transcriptase-polymerase chain reaction and immunohistochemistry were performed on tissues from patients with PCa to screen the pT stage-associated targets and to explore the prognostic value of these targets in PCa. RESULTS: CENPI and SLC38A11 were most significantly upregulated, whereas ANO6 and KANK2 were mostly decreased in pT3 tumors compared with pT2 staging. ANO6 levels were negatively associated with preoperative prostate-specific antigen (PSA) levels, lymph node staging (N staging), Gleason score, and overall survival (OS); CENPI was positively associated with preoperative PSA levels, N staging, and OS, but was not associated with the Gleason score; SLC38A11 and KANK2 were not associated with OS. ANO6 and KANK2 were correlated with neutrophil markers, whereas CENPI was correlated with macrophage M2 types. CONCLUSION: We identified 4 reliable PCa biomarkers associated with pT staging that would be valuable for diagnosing and determining PCa prognosis.

Are there features that can predict the unresectability of pleural mesothelioma?

INTRODUCTION: The current clinical staging of pleural mesothelioma (PM) is often discordant with the pathologic staging. This study aimed to identify clinical and radiological features that could help predict unresectability in PM. METHODS: Twenty-two descriptive radiologic features were retrospectively evaluated on preoperative computed tomography (CT) and/or positron emission tomography/CT (PET/CT) performed in patients with presumably resectable PM who underwent surgery. Measurements of maximum and sum pleural thickness at three levels of the thorax (upper, middle, and lower) were taken and stratified based on the cutpoints provided by the International Association for the Study of Lung Cancer (IASLC). Clinical and radiological features, including clinical-stage, were compared between resectable and unresectable tumors by univariate analysis and logistic regression modeling. RESULTS: Of 133 patients, 69/133 (52%) had resectable and 64/133 (48%) had unresectable PM. Asbestos exposure (p = 0.005), neoadjuvant treatment (p = 0.001), clinical T-stage (p < 0.0001), all pleural thickness measurements (p < 0.05), pleural thickness pattern (p < 0.0001) and degree (p = 0.033), lung invasion (p = 0.004), extrapleural space obliteration (p < 0.0001), extension to subphrenic space (p = 0.0004), and two combination variables representing extensive diaphragmatic contact and/or chest wall involvement (p = 0.002) and mediastinal invasion (p < 0.0001) were significant predictors at univariate analysis. At multivariable analysis, all models achieved a strong diagnostic performance (area under the curve (AUC) > 0.8). The two best-performing models were one that included the upper-level maximum pleural thickness, extrapleural space obliteration, and mediastinal infiltration (AUC = 0.876), and another that integrated clinical variables and radiological assessment through the clinical T-stage (AUC = 0.879). CONCLUSION: Selected clinical and radiologic features, including pleural thickness measurements, appear to be strong predictors of unresectability in PM. CLINICAL RELEVANCE STATEMENT: A more accurate prediction of unresectability in the preoperative assessment of patients with pleural mesothelioma may avoid unnecessary surgery and prompt initiation of nonsurgical treatments. KEY POINTS: About half of pleural mesothelioma patients are reported to receive an incorrect disease stage preoperatively. Eleven features identified as predictors of unresectability were included in strongly performing predictive models. More accurate preoperative staging will help clinicians and patients choose the most appropriate treatments.

GTN Diagnosis and Staging.

Majority of gestational trophoblastic neoplasia (GTN) follows molar pregnancies where diagnosis is mostly based on persistent or rising serum human chorionic gonadotrophin (hCG). Diagnosis of GTN could be based on clinical presentation, serum hCG measurement, imaging, histology, and genotyping. A high index of suspicion in women of reproductive age presenting with abnormal vaginal bleeding or unusual systematic presentation is important. An accurate staging and classification system for GTN is crucial to evaluate the risk and the prognosis of patients, and to optimize treatment. GTN is staged using the International Federation of Gynecology and Obstetrics 2000 staging and the modified World Health Organization prognostic scoring system.

A Comprehensive Review of Advancements in Diagnostic Imaging: Unveiling Oral Cavity Malignancies Using Computed Tomography.

Early detection of oral cavity malignancies is essential for improving treatment outcomes and patient survival rates. Diagnostic imaging, particularly computed tomography (CT), plays a pivotal role in the early identification and detailed assessment of these malignancies. This comprehensive review explores the advancements in CT imaging and its application in diagnosing oral cavity cancers. It discusses the anatomy and physiology of the oral cavity, the clinical characteristics of common malignancies, and the principles and protocols of CT imaging. The review highlights the diagnostic features of oral malignancies on CT, including distinguishing benign from malignant lesions and staging criteria. Emerging technologies, such as higher-resolution imaging, integration with other modalities, and the potential of artificial intelligence, are examined for their role in enhancing diagnostic accuracy. The clinical implications, challenges, and future directions in the use of CT imaging for oral cavity malignancies are also discussed. This review underscores the importance of continued research and technological advancements in optimizing the use of CT for early detection and effective management of oral cavity cancers.

Thymic Lymphoepithelial Carcinoma: A Rare Aggressive Mediastinal Mass.

Primary thymic lymphoepithelial carcinoma is a rare neoplasm of the mediastinum. The recognition of clinical, radiologic, and pathologic features can help in making an accurate diagnosis of this aggressive tumor at the earliest.Here, we present the radiologic and pathologic findings of an anterior mediastinal mass in a 44-year-old man, which turned out to be a poorly differentiated squamous cell carcinoma of thymic origin, also known as lymphoepithelioma-like thymic carcinoma.

Incidence and Pitfalls of Adipose Tissue Encountered in Prostatic Transurethral Resections and Related Specimens.

While the presence of adipose tissue and its involvement by prostatic cancer (extraprostatic extension) is well-recognized in prostate biopsies, adipose tissue in transurethral resections of the prostate (TURP) is largely unexplored. Herein, 200 consecutive TURPs and related specimens were reviewed, including a separate 3-year analysis of specimens containing prostatic cancer, with the following data collected: presence of fat, presence of cancer within fat, and quantity of fat. For specimens with both fat and prostatic cancer, specimen weight and tumor volume were recorded. Within the 200 consecutive TURPs and related specimens, adipose tissue was identified in 20%; 55% had 2.5 mm of adipose tissue; the number of fragments with adipose tissue ranged from 1 to 14. No correlation between specimen weight and measured extent of adipose tissue or number of fragments with adipose tissue was identified. Of all the specimens with prostatic cancer, 15/56 (27%) involved adipose tissue, with two specimens with large cancer volume (>90%) demonstrating extensive involvement of adipose tissue. Adipose tissue is frequently present within TURP and related specimens with variability in extent. The etiology behind encountering adipose tissue is uncertain, and it could represent resection into peri-prostatic fat, intraprostatic fat, or bladder neck fat sampling. Although encountering adipose tissue involved by cancer in TURP and related specimens may imply extraprostatic extension (pT3a), further studies are needed to corroborate these findings as well as to determine if these should be included in reported synoptics.

Establishment of a nomogram model for predicting distant metastasis in pancreatic ductal adenocarcinoma: a comparative analysis of different lymph node staging systems based on the SEER database.

The purpose of this study was to compare the predictive value of different lymph node staging systems and to develop an optimal prognostic nomogram for predicting distant metastasis in pancreatic ductal adenocarcinoma (PDAC). Our study involved 6364 patients selected from the Surveillance, Epidemiology, and End Results (SEER) database and 126 patients from China. Independent risk factors for distant metastasis were screened by univariate and multivariate logistic regression analyses, and a model-based comparison of different lymph node staging systems was conducted. Furthermore, we developed a nomogram for predicting distant metastasis using the optimal performance lymph node staging system. The lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), age, primary site, grade, tumor size, American Joint Committee on Cancer (AJCC) 7th Edition T stage, and radiotherapy recipient status were significant predictors of distant metastasis in PDAC patients. The model with the LODDS was a better fit than the model with the LNR. We developed a nomogram model based on LODDS and six clinical parameters. The area under the curve (AUC) and concordance index (C-index) of 0.753 indicated that this model satisfied the discrimination criteria. Kaplan-Meier curves indicate a significant difference in OS among patients with different metastasis risks. LODDS seems to have a superior ability to predict distant metastasis in PDAC patients compared with the AJCC 8th Edition N stage, PLN and LNR staging systems. Moreover, we developed a nomogram model for predicting distant metastasis. Clinicians can use the model to detect patients at high risk of distant metastasis and to make further clinical decisions.

What Does N2 Lymph Node Involvement Mean for Patients with Non-Small Cell Lung Cancer (NSCLC)?-A Review of Implications for Diagnosis and Treatment.

Patients with stage III NSCLC with N2 lymph node involvement carry a complex and diverse disease entity. Challenges persist in the areas of diagnosis, staging, multimodal management, and the determination of surgical indications and resectability criteria. Therefore, this review focuses on the latest updates in N2 disease staging and its prognostic and treatment implications. Emphasis is placed on the importance of accurate staging using imaging modalities such as [18F]FDG-PET/CT as well as minimally invasive mediastinal staging endoscopic techniques. The evolving role of surgery in the management of N2 disease is also explored. The benefits of neoadjuvant and adjuvant treatments have been demonstrated, along with the efficacy of a combined multimodal approach with chemo-immunotherapy in the perioperative setting, reigniting the debate of N2 disease subsets and optimal treatment options. Furthermore, this review addresses the controversies surrounding surgical approaches in upfront "borderline" resectable stage III NSCLC as well as the benefits of combined chemoradiotherapy with consolidation immunotherapy for patients with unresectable tumors. In conclusion, personalized diagnostic and treatment approaches tailored to individual patient characteristics, resource availability, and institutional expertise are essential for optimizing outcomes in patients with stage III-N2 NSCLC.

Long-Term Oncologic Outcomes of Omitting Axillary Surgery in Breast Cancer Patients with Chest Wall Recurrence after Mastectomy.

BACKGROUND: The management of the axilla in breast cancer patients with isolated chest wall recurrence (CWR) after mastectomy remains controversial. Although sentinel lymph node biopsy (SLNB) for restaging is feasible, its role is unclear. We aimed to determine if the omission of axillary restaging surgery in female patients with operable presumably isolated CWRs could result in an increased risk of second recurrences. METHODS: In this retrospective multicentre study, patients who developed CWRs were reviewed. We excluded patients with suspected or concomitant regional/distant metastases, bilateral cancers and patients without CWR surgery. Patients' demographics, pathological data and subsequent recurrences were collected from a prospective database and were compared between patients with axillary lymph node dissection (ALND) and/or SLNB versus no axillary operation at CWR. FINDINGS: A total of 194 patients with CWRs were eligible. The median age at CWR was 56.0 (IQR 47.0-67.0) years old. At recurrence, 8 (4.1%), 5 (2.6%) and 181 (93.3%) patients had ALND, SLNB and no axillary operation, respectively. Patients with no axillary surgery during CWR were associated with, at primary cancer, a lower incidence of ductal carcinoma in situ as diagnosis (p = 0.007) and older age (p = 0.022). Subsequent ipsilateral axillary (p = 0.768) and second recurrences (p = 0.061) were not statistically different between patients with and without axillary surgery at CWR on median follow-up of 59.5 (IQR 27.3-105) months. INTERPRETATION: In patients without evidence of concomitant regional or distant metastasis at CWR diagnosis, omission of axillary restaging surgery was not associated with an increased ipsilateral axillary or second recurrences on long-term follow-up.

The Sensitivity and Specificity of Multiparametric Magnetic Resonance Imaging and Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Predicting Seminal Vesicle Invasion in Clinically Significant Prostate Cancer: A Multicenter Retrospective Study.

Background/Objectives: The presence of seminal vesicle invasion (SVI) in prostate cancer (PCa) is associated with poorer postoperative outcomes. This study evaluates the predictive value of magnetic resonance imaging (MRI) and prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) for SVI in PCa. Methods: This cohort study included consecutive robotic prostatectomy patients for PCa at three Australian tertiary referral centres between April 2016 and September 2022. MRI and PSMA PET/CT results, clinicopathological variables, including age, BMI, prostate-specific antigen (PSA), PSA density, DRE, Biopsy Gleason score, Positive biopsy cores, PIRADS v2.1 score, MRI volume and MRI lesion size were extracted. The sensitivity, specificity, and accuracy of MRI and PSMA PET/CT for predicting SVI were compared with the histopathological results by receiver operating characteristic (ROC) analysis. Subgroup univariate and multivariate analysis was performed. Results: Of the 528 patients identified, 86 had SVI on final pathology. MRI had a low sensitivity of 0.162 (95% CI: 0.088-0.261) and a high specificity of 0.963 (95% CI: 0.940-0.979). The PSMA PET/CT had a low sensitivity of 0.439 (95% CI: 0.294-0591) and a high specificity of 0.933 (95% CI: 0.849-0.969). When MRI and PSMA PET/CT were used in combination, the sensitivity and specificity improved to 0.514 (95%CI: 0.356-0.670) and 0.880 (95% CI: 0.813-0.931). The multivariate regression showed a higher biopsy Gleason score (p = 0.033), higher PSA (p < 0.001), older age (p = 0.001), and right base lesions (p = 0.003) to be predictors of SVI. Conclusions: MRI and PSMA PET/CT independently underpredicted SVI. The sensitivity and AUC improved when they were used in combination. Multiple clinicopathological factors were associated with SVI on multivariate regression and predictive models incorporating this information may improve oncological outcomes.

Association between Ovarian Endometriomas and Stage of Endometriosis.

Objectives: To determine the association between ovarian endometriomas and stage of endometriosis. Methods: A total of 222 women aged 18-55 years old, who underwent minimally invasive surgery between January 2016 and December 2021 for treatment of endometriosis were included in the study. Patients underwent laparoscopic and/or robotic treatment of endometriosis by a single surgeon (FRN) and were staged using the ASRM revised classification of endometriosis. Pre-operative imaging studies, and operative and pathology reports were reviewed for the presence of endometriomas and the final stage of endometriosis. Using univariate analyses for categorical variables and the two-sample t-test or Mann-Whitney test for continuous data, association between endometriomas, stage of endometriosis, type of endometrioma, and other patient parameters such as age, gravidity, parity, laterality of endometriomas, prior medical treatment, and indication for surgery was analyzed. Results: Of the 222 patients included in the study, 86 patients had endometrioma(s) and were found to have stage III-IV disease. All 36 patients with bilateral endometriomas and 70% of patients with unilateral endometriomas had stage IV disease. Conclusions: The presence of ovarian endometrioma(s) indicates a higher stage of disease, correlating most often with stage IV endometriosis. Understanding the association between endometriomas and anticipated stage of disease can aid in appropriate pre-operative planning and patient counseling.

Enhancing prognostic guidance in renal light-chain amyloidosis: a new staging system incorporating pathological characters.

BACKGROUND: Advancements in treatment regimens have led to improved outcomes in renal Immunoglobulin light-chain amyloidosis. Nevertheless, a subset of patients may still experience renal adverse events despite achieving hematologic very good partial response or better. This discrepancy may be attributed to the deposition pattern of amyloid in renal tissue. To enhance prognostic assessment, a staging system that incorporates both pathological characteristics and clinical indicators should be developed. METHODS: Patients newly diagnosed through renal biopsy between January 1, 2017, and December 31, 2022, were included. The renal pathology of patients was evaluated according to amyloid score (AS). Risk factors for end-stage renal disease or renal progression were identified by the competing risk model, then to develop a renal staging system. The Concordance index (C-index), internal cross-validation and Decision Curve Analysis (DCA) were used to evaluate the performance of the new staging system. RESULTS: 74 patients were included, and 16 (21.6%) patients had end-stage renal disease or renal progression within 24.7 (11.9, 50.7) months. AS and estimated glomerular filtration rate (eGFR) were identified as independent risk factors and the staging system based on them, which the C-index was 0.81 (95%CI, 0.73-0.89), had greater improvement than previous staging systems. The internal cross-validation and DCA also confirmed its great clinical benefits. CONCLUSION: The AS demonstrated its prognostic significance in Chinese patients, and the novel renal staging system based on AS and eGFR may provide great prognostic guidance for these patients.

Incorporation of Biologic Variables Into the Staging for Canine Cutaneous and Subcutaneous Mast Cell Tumours: Proposal of the UBo pTNM System.

Canine cutaneous mast cell tumours (MCTs) are currently staged based on the World Health Organization (WHO) classification, which has remained unchanged since its initial formulation. Our study aimed to assess the reliability of a novel pTNM staging system, which incorporates tumour extent (T), lymph node involvement (N), presence of distant metastases (M) and the two-tier histologic grade. We analysed medical records of dogs with one or more cutaneous/subcutaneous completely staged MCT, undergoing tumour excision with lymphadenectomy, unless distant metastases were present, in which cases, medical therapy was administered. Dogs were categorized into three stages: I (T1-2N0M0), II (T1-2N1M0) and III (distant metastases). Stages I and II were further divided based on histologic grade into 'low' and 'high'. Substage b was defined as the presence of tumour diameter of ≥3 cm and/or ulceration. Of 226 dogs, 87 (38.5%) were in Stage I (I-low, n = 75; I-high, n = 12), 107 (47.3%) in Stage II (II-low, n = 59; II-high, n = 48), and 32 (14.2%) in Stage III. The newly proposed staging system was able to significantly stratify the population for both time to progression and tumour-specific survival. Compared to Stage I-low, the risk of progression increased significantly for Stage I-high (18.3 times), Stage II-low (8.5 times), Stage II-high (41.5 times) and Stage III (110.3 times). The staging system was highly prognostic for both cutaneous and subcutaneous MCTs. Prospective validation studies are essential to compare this new system with the current WHO staging and further validate its accuracy and clinical utility.

Automated remote sleep monitoring needs uncertainty quantification.

Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage classification, but trust and reliability issues have hampered its adoption in clinical applications. Estimating uncertainty is a crucial factor in enhancing reliability by identifying regions of heightened and diminished confidence. In this study, we used an uncertainty-centred machine learning pipeline, U-PASS, to automate sleep staging in a challenging real-world dataset of single-channel electroencephalography and accelerometry collected with a wearable device from an elderly population. We were able to effectively limit the uncertainty of our machine learning model and to reliably inform clinical experts of which predictions were uncertain to improve the machine learning model's reliability. This increased the five-stage sleep-scoring accuracy of a state-of-the-art machine learning model from 63.9% to 71.2% on our dataset. Remarkably, the machine learning approach outperformed the human expert in interpreting these wearable data. Manual review by sleep specialists, without specific training for sleep staging on wearable electroencephalography, proved ineffective. The clinical utility of this automated remote monitoring system was also demonstrated, establishing a strong correlation between the predicted sleep parameters and the reference polysomnography parameters, and reproducing known correlations with the apnea-hypopnea index. In essence, this work presents a promising avenue to revolutionize remote patient care through the power of machine learning by the use of an automated data-processing pipeline enhanced with uncertainty estimation.

Outcomes and Survival for Early-Stage Non-Small Cell Lung Cancer Following Wedge Resection or Lobectomy: A Propensity Score-Matched Analysis Using a Novel Peruvian Registry.

Background: Using a previously unreported Peruvian registry of patients treated for early-stage non-small cell lung cancer (NSCLC), this study explored whether wedge resection and lobectomy were equivalent regarding survival and impact on radiologic-pathologic variables. Methods: This observational, analytical, longitudinal study used propensity score-matched (PSM) analysis of a single-center retrospective registry of 2,570 patients with pathologic stage I-II NSCLC who were treated with wedge resection (n=1,845) or lobectomy (n=725) during 2000-2020. After PSM, 650 cases were analyzed (resection, n=325; lobectomy, n=325) through preoperative and clinical variables, including patients with ≥1 lymph node removed. Kaplan-Meier curves and multivariable Cox proportional hazard models were created for 5-year overall survival (OS), disease-free survival (DFS), and locoregional-recurrence-free survival (LRFS). Results: The principal complication was operative pain persisting >7 days for lobectomy versus wedge resection (58% vs. 23%, p=0.034) and shorter hospital stays for resection than for lobectomy (5.3 days vs. 12.8 days, p=0.009). The 5-year OS (84.3% vs. 81.2%, p=0.09) and DFS (79.1% vs. 74.1%, p=0.07) were similar and statistically insignificant between resections and lobectomies, respectively. LRFS was worse overall following wedge resection than lobectomy (79.8% vs. 91.1%, p<0.02). Nevertheless, in the PSM analysis, both groups experienced similar LRFS when the resection margin was >10 mm (90.9% vs. 87.3%, p<0.048) and ≥4 lymph nodes were removed (82.8% vs. 79.1%, p<0.011). Conclusion: Both techniques led to similar OS and DFS at 5 years; however, successful LRFS required a wedge resection with a surgical margin and adequate lymph node removal to obtain outcomes similar to lobectomy.

GRU-powered sleep stage classification with permutation-based EEG channel selection.

We present a new approach to classifying the sleep stage that incorporates a computationally inexpensive method based on permutations for channel selection and takes advantage of deep learning power, specifically the gated recurrent unit (GRU) model, along with other deep learning methods. By systematically permuting the electroencephalographic (EEG) channels, different combinations of EEG channels are evaluated to identify the most informative subset for the classification of the 5-class sleep stage. For analysis, we used an EEG dataset that was collected at the International Institute for Integrative Sleep Medicine (WPI-IIIS) at the University of Tsukuba in Japan. The results of these explorations provide many new insights such as the (1) drastic decrease in performance when channels are fewer than 3, (2) 3-random channels selected by permutation provide the same or better prediction than the 3 channels recommended by the American Academy of Sleep Medicine (AASM), (3) N1 class suffers the most in prediction accuracy as the channels drop from 128 to 3 random or 3 AASM, and (4) no single channel provides acceptable levels of accuracy in the prediction of 5 classes. The results obtained show the GRU's ability to retain essential temporal information from EEG data, which allows capturing the underlying patterns associated with each sleep stage effectively. Using permutation-based channel selection, we enhance or at least maintain as high model efficiency as when using high-density EEG, incorporating only the most informative EEG channels.

Preoperative prediction of rectal Cancer staging combining MRI deep transfer learning, radiomics features, and clinical factors: accurate differentiation from stage T2 to T3.

BACKGROUND: This study evaluates the efficacy of integrating MRI deep transfer learning, radiomic signatures, and clinical variables to accurately preoperatively differentiate between stage T2 and T3 rectal cancer. METHODS: We included 361 patients with pathologically confirmed stage T2 or T3 rectal cancer, divided into a training set (252 patients) and a test set (109 patients) at a 7:3 ratio. The study utilized features derived from deep transfer learning and radiomics, with Spearman rank correlation and the Least Absolute Shrinkage and Selection Operator (LASSO) regression techniques to reduce feature redundancy. Predictive models were developed using Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), and Support Vector Machine (SVM), selecting the best-performing model for a comprehensive predictive framework incorporating clinical data. RESULTS: After removing redundant features, 24 key features were identified. In the training set, the area under the curve (AUC)values for LR, RF, DT, and SVM were 0.867, 0.834, 0.900, and 0.944, respectively; in the test set, they were 0.847, 0.803, 0.842, and 0.910, respectively. The combined model, using SVM and clinical variables, achieved AUCs of 0.946 in the trainingset and 0.920 in the test set. CONCLUSION: The study confirms the utility of a combined model of MRI deep transfer learning, radiomic features, and clinical factors for preoperative classification of stage T2 vs. T3 rectal cancer, offering significant technological support for precise diagnosis and potential clinical application.

Omission of staging PET/CT linked to reduced survival in stage III non-small cell lung cancer: insights from the LUCAS project real-world data.

Background: Stage III non-small cell lung cancer (NSCLC) is a highly heterogeneous stage due to its subgroups (IIIA-IIIC) comprising both resectable and unresectable tumors. Accurate determination of the extent of the disease is essential for excluding stage IV and choosing the optimal treatment regimen. Whole body positron emission tomography and computed tomography scan (PET/CT) is recommended as an initial staging imaging in locally advanced NSCLC. Despite international guidelines for NSCLC diagnosis and treatment, they are not always adhered to due to various reasons. Even in such a groundbreaking study, the phase 3 trial PACIFIC investigating the efficacy of durvalumab as consolidation therapy in patients with stage III NSCLC PET/CT was not mandatory. With the premise that whole body PET/CT of the trunk is essential for diagnosing stage III NSCLC, we performed a retrospective study evaluating the relationship of the use of PET/CT versus conventional staging with CT of the chest and abdomen, in terms of survival. Methods: This retrospective study of stage III NSCLC patients used the Czech lung cancer registry LUCAS, which was established in June 2018. As of the data export (up to February 9, 2022), a total of 703 patients were eligible for the analysis. Overall survival (OS) was compared using Kaplan-Meier analysis and a Cox regression model. Continuous variables were tested using the Mann-Whitney test, and categorical variables using the Pearson's Chi-square or Fisher's exact test. Results: A total of 703 patients were included in the cohort with an average age of 69 years. PET/CT was performed on 354 patients, and conventional staging using chest and abdominal CT on 349 patients. The median OS among patients with PET/CT was 20.9 months [95% confidence interval (CI): 18.1-23.7], and it was statistically significantly higher (P<0.001) than among patients without PET/CT, where the median OS was 9.0 months (95% CI: 7.3-10.6). The observed effect of PET/CT was also statistically significant when comparing individual stages (IIIA, IIIB, IIIC). The multivariate Cox model confirmed the use of PET/CT as an independent prognostic factor. The most common reason for omission of PET/CT was the local or time unavailability of the examination. Conclusions: Omission of PET/CT can mean a significant decrement in survival for the patients in stage III NSCLC, likely due to poor staging and suboptimal treatment. Routine use of PET/CT is strictly recommended for the optimal management of stage III NSCLC patients even outside the high-income countries.

Assessment of Serum Cortisol Levels in Patients with Oral Squamous Cell Carcinoma and Its Correlation with Clinical Staging, Histopathological Grading and Nodal Metastasis: A Prospective Study.

Aims and Objectives: To assess the serum cortisol level in patients with oral squamous cell carcinoma and correlate this value with clinical staging of tumor using TNM staging, histopathological grading of the tumor using BRYNE'S (1992) invasive tumor front grading system and nodal metastasis using histopathology. Materials and Methods: In this prospective study a total of 25 patients who reported with biopsy proven oral squamous cell carcinoma from Dec 2012-Nov 2014 were included. Patient's clinical parameters were recorded. Clinical staging was assessed using TNM staging. Blood sample was collected from the patient in the early morning and was sent to department of biochemistry, SDM Medical College to assess the serum cortisol levels. The obtained results of serum cortisol levels was correlated with TNM staging, histopathologic grading of the excised tumor (using BRYNE'S grading system) and nodal metastasis (which was confirmed using histopathology of neck specimen). The data was then analyzed statistically. Results: Patients with oral SCC showed morning serum cortisol levels higher. Cortisol levels increased as the stage of the cancer advanced. There was a statistical significance between TNM and cortisol (p = 0.0001) but no significant correlation between TMS and PN status with cortisol. Conclusion: Patients with advanced stage oral SCC showed significantly higher levels of cortisol than those in an initial stage. This study provides strong evidence that OSSS cells are influenced by neurohormonal mediators and cortisol estimation can be used a biomarker associated with the disease clinical status.