Accurate Staging Research Articles

Predicting Axillary Metastasis of Breast Cancer Patients with MRI Relaxometry

Background: Breast cancer is a leading cause of cancer-related mortality among women worldwide. Accurate staging, including the detection of axillary metastases, is vital for treatment planning. This study evaluates the efficacy of MRI relaxometry as a diagnostic tool for axillary lymph node metastases in breast cancer patients. Methods: A prospective study was conducted on 67 consecutive breast cancer patients. Relaxometry parameters, including T2Max, T2Min, and 1HAv, were assessed using 1.5 Tesla MRI. All axillary metastases were histologically confirmed using core-needle biopsy or surgical specimens. Statistical analyses included ROC curves, chi-square tests, and multivariate analysis to determine correlations between imaging findings and pathological results. Results: Significant associations were found between T2Min-ipsilateral (p = 0.018), 1HAv-ipsilateral (p = 0.003), and axillary metastases. ROC analysis demonstrated that T2Min-ipsilateral and 1HAv-ipsilateral have modest to acceptable discriminatory abilities (AUC = 0.681 and AUC = 0.740, respectively). Combined clinical and imaging models enhanced diagnostic accuracy (AUC = 0.749). Conclusions: MRI relaxometry improves the detection of axillary metastases in breast cancer, particularly when integrated with clinical and pathological evaluations.

PET/CT-based target volume definition in involved-site radiotherapy for treatment of early-stage nodal follicular lymphoma.

Recent advancements in imaging, particularly 18F-fluorodeoxyglucose positron-emission tomography-computed tomography (FDG-PET/CT), have improved the detection of involved lymph nodes, thus influencing staging accuracy and potentially treatment outcomes. This study is apost hoc analysis of the GAZAI trial data to evaluate the impact of FDG-PET/CT versus computed tomography (CT) alone on radiation target volumes for involved-site radiotherapy (IS-RT) in early-stage follicular lymphoma (FL). All patients in the GAZAI trial underwent pretherapeutic FDG-PET/CT examinations, which were subject to central quality control. Lymph nodes with pathological metabolism were assessed for CT morphology. Differential regional involvement and the impact on radiation target volume for IS-RT were compared between PET/CT-based to solely CT-based staging. In 54patients with PET-positive lymph nodes after initial surgery, 170 involved lymph nodes were identified in total. FDG-PET/CT identified additionally involved lymph nodes not detected by CT in 61% of the patients, leading to asignificant change in radiation treatment fields for 30% of the cohort. Only 58% of all involved lymph nodes exhibited pathological CT morphology. The findings were robust across different Deauville score thresholds and CT morphological metrics. The findings confirm the essential role of FDG-PET/CT in accurately defining the radiation volume for treatment of early-stage follicular lymphomas with radiotherapy. These results support the integration of FDG-PET/CT into the standard diagnostic pathway and its inclusion in the service catalogue of statutory health insurance, emphasizing its importance for optimal treatment planning and the potential impact on patient outcomes.

Review Article: Anatomical and Physiological Development of Reproductive System in Female Murine

The aim of this article is to address the challenges associated with the accurate and consistent staging of the estrous cycle in female laboratory animals, which is critical for reproductive research and preclinical safety evaluations of drugs and chemicals. Laboratory animals, particularly female murine models, are widely used in research as models for mammalian health and disease. However, many substances tested during preclinical investigations interfere with reproductive function, causing morphological changes in the reproductive tract or disruptions in the phases of the estrous cycle. Recognising these alterations requires a thorough understanding of the histological changes in the reproductive tract throughout the cycle. Existing literature, while comprehensive, often lacks precise criteria for defining the transitions between stages of the cycle, creating inconsistencies in staging. This review adopts a pragmatic and practical approach, synthesising personal experience and a century of literature to present a detailed examination of the anatomical and physiological development of the female murine reproductive system. The review emphasises the histological characteristics of the reproductive tract during different estrous phases, providing a framework for consistent and accurate staging. The findings highlight the reproductive traits that make female murine models ideal for reproductive research, including their well-documented physiology and reliable cycle patterns. This article serves as a valuable resource for toxicological pathologists and researchers, offering clarity on staging methods and reaffirming the relevance of murine models in reproductive studies.

A multimodal similarity-aware and knowledge-driven pre-training approach for reliable pneumoconiosis diagnosis

Background Pneumoconiosis staging is challenging due to the low clarity of X-ray images and the small, diffuse nature of the lesions. Additionally, the scarcity of annotated data makes it difficult to develop accurate staging models. Although clinical text reports provide valuable contextual information, existing works primarily focus on designing multimodal image-text contrastive learning tasks, neglecting the high similarity of pneumoconiosis imaging representations. This results in inadequate extraction of fine-grained multimodal information and underutilization of domain knowledge, limiting their application in medical tasks. Objective The study aims to address the limitations of current multimodal methods by proposing a new approach that improves the precision of pneumoconiosis diagnosis and staging through enhanced fine-grained learning and better utilization of domain knowledge. Methods The proposed Multimodal Similarity-aware and Knowledge-driven Pre-Training (MSK-PT) approach involves two stages. In the first stage, we deeply analyze the similar features of pneumoconiosis images and use a similarity-aware modality alignment strategy to explore the fine-grained representations and associated disturbances of pneumoconiosis lesions between images and texts, guiding the model to match more appropriate feature representations. In the second stage, we utilize data-associated features and pre-stored domain knowledge features as priors and constraints to guide the downstream model in the visual domain without annotations. To address potential erroneous labels generated by model predictions, we further introduce an uncertainty threshold strategy to mitigate the negative impact of imperfect prediction labels and enhance model interpretability. Results We collected and created the pneumoconiosis chest X-ray (PneumoCXR) dataset to evaluate our proposed MSK-PT method. The experimental results show that our method achieved a classification accuracy of 81.73%, outperforming the state-of-the-art algorithms by 2.53%. Conclusions MSK-PT showed diagnostic performance that matches or exceeds the average radiologist's level, even with limited labeled data, highlighting the method's effectiveness and robustness.

Staging of prostate Cancer with ultra-fast PSMA-PET scans enhanced by AI.

PSMA-PET is a reference standard examination for patients with prostate cancer, but even using recently introduced digital PET detectors image acquisition with standard field-of-view scanners is still in the range of 20min. This may cause limited access to examination slots because of the growing demand for PSMA-PET. Ultra-fast PSMA-PET may enhance throughput but comes at the cost of poor image quality. The aim of this manuscript is to evaluate the accuracy of AI-enhanced ultra-fast PSMA-PET for staging of patients with prostate cancer. A total number of 357 whole-body [68Ga]Ga-PSMA-11 PET datasets were included. Patients underwent two digital PET scans, one at standard and one at ultra-fast speed (table speed: 0.6-1.2mm/s vs. 50mm/s). A modified pix2pixHD generative adversarial network to enhance the ultra-fast images was trained with 286 datasets and evaluated with the remaining 71 datasets. The staging accuracy of ultra-fast PSMA-PET and AI-enhanced ultra-fast PET was compared with the reference standard PET separately for miTNM regions proposed by PROMISE V2.0. The AI-network significantly improved the visual image quality and detection rate in most miTNM regions compared with the non-enhanced image data (T: 69.6% vs. 43.5%, p < 0.05; N: 46.3% vs. 27.8%, p < 0.01; M1a 64.4% vs. 47.5%, p < 0.01; M1b: 85.7% vs. 72.1%, p < 0.01). However, improvement was not significant for the M1c category (42.9 vs. 28.6%, p > 0.05). Missed lesions had a smaller SUVmax and lesion size compared with detected lesions (exemplary for N: 9.5 vs. 26.5 SUVmax; 4 vs. 10mm). SUVmax values of lesions were significantly different in all miTNM regions between the ultra-fast and reference standard PET, but only in the T-region between the AI-enhanced and reference standard PET. The AI-based image enhancement improved image quality and region detection rates by a mean of 17.9%. As the sensitivity of synthetic PET for small and low-uptake lesions was limited, a potential clinical use case could be disease monitoring in patients with high tumor volume and PSMA uptake undergoing PSMA radioligand therapy. The improvement in detection rate of distant metastases was not significant. This indicates that more training data is needed to ensure robust results also for lesions that have lower appearance frequency. Future studies on accelerated PSMA-PET seem warranted.

Role of MRI in Assessing the Feasibility of Fertility-Sparing Treatments for Early-Stage Endometrial and Cervical Cancers.

Fertility-sparing treatment (FST) has become a key aspect of managing gynecologic cancers in reproductive-age patients who wish to preserve fertility. Several leading clinical societies, including the European Society of Gynecological Oncology, the European Society for Radiotherapy and Oncology, the European Society of Pathology, and the European Society of Human Reproduction and Embryology, have recently published evidence-based guidelines on fertility-sparing strategies and posttreatment surveillance of patients with early-stage gynecologic cancers, in particular endometrial and cervical cancers. These guidelines highlight MRI as essential to initial patient selection and follow-up. Properly tailored pelvic MRI protocols and clear MRI reports are key to performing accurate staging, assessing eligibility, and confirming the initial and ongoing feasibility of FST. Accordingly, radiologists, particularly those specializing in gynecologic imaging, play a critical role in the multidisciplinary approach to FST. They should be well-versed in FST eligibility criteria and key MRI finding before and after FST, ensuring these details are comprehensively communicated in structured MRI reports.

MULTI-PARAMETER DIFFUSION-WEIGHTED MAGNETIC RESONANCE IMAGING FOR PROSTATE CANCER STAGING TAKING HISTOPATHOLOGY AS THE GOLD STANDARD AT ISLAMABAD DIAGNOSTIC CENTER FAISALABAD

Background: Prostate cancer is one of the most prevalent malignancies in males and a leading cause of cancer-related mortality worldwide. Early detection and accurate staging are critical for improving outcomes and guiding treatment. Multiparametric MRI (mpMRI), particularly diffusion-weighted imaging (DWI), has emerged as a promising non-invasive diagnostic modality for detecting prostate cancer and assessing tumor aggressiveness. Compared to traditional diagnostic tools like transrectal ultrasound (TRUS), mpMRI offers superior sensitivity and diagnostic accuracy for identifying prostate malignancies. Objective: To evaluate the diagnostic performance of DWI MRI in detecting and characterizing prostate cancer in comparison with TRUS-guided histopathology. The study also assessed the effectiveness of different b-values and mpMRI sequences in staging and identifying prostate malignancies. Methods: A prospective cross-sectional study was conducted at Islamabad Diagnostic Center, Faisalabad, from July 2024 to December 2024. A total of 112 male patients, aged 30 years or older, presenting with elevated PSA levels, hematuria, urinary retention, weight loss, prostatitis, or pelvic pain, underwent mpMRI. Imaging sequences, including DWI, ADC mapping, T2-weighted (T2WI), and T1-weighted (T1WI) MRI, were analyzed by independent radiologists. TRUS-guided histopathology was used as the gold standard for correlation. Statistical analysis, including sensitivity, specificity, diagnostic accuracy, and correlation analysis, was performed using SPSS version 22.0. Results: The mean age of participants was 59.8 years (±1.116 SD), with the 70–80 age group comprising 42 (37.5%) patients. Clinical symptoms included elevated PSA levels in 65 (58%), urinary retention in 83 (74.1%), prostatitis in 70 (62.5%), pelvic pain in 35 (31.3%), hematuria in 30 (26.8%), and weight loss in 9 (8%). DWI and ADC mapping demonstrated the highest sensitivity (92%) compared to T2WI (88.5%) and T1WI (66.7%), while T1WI exhibited the highest specificity (72%). Diagnostic accuracy was highest for DWI (77.6%), followed by T2WI (75.8%), ADC (73.2%), and T1WI (67.8%). DWI demonstrated a significant correlation with TRUS findings (p=0.001) and PSA levels (p=0.038). Conclusion: DWI MRI proved to be a non-invasive, highly sensitive imaging modality for the early detection and characterization of prostate cancer, surpassing TRUS in diagnostic accuracy. Its ability to assess tumor aggressiveness and guide treatment decisions underscores its indispensable role in prostate cancer diagnosis. The incorporation of mpMRI, alongside PSA testing and TRUS, offers a more comprehensive diagnostic approach for improved outcomes in prostate cancer management.

Laryngeal Carcinoma Radiologic Staging and What the Surgeon Wants to Know

Laryngeal cancer accounts for approximately 25% of head and neck cancers and is an extremely morbid malignancy, severely affecting quality of life by impeding the ability to communicate, swallow, and breathe. Patients can present with a myriad of symptoms including hoarseness, pain, dysphagia, and even otalgia. Initial clinical evaluation often includes laryngoscopy, assessing for mucosal lesions and vocal fold mobility. Imaging has a secondary role in laryngeal cancer confined to the mucosal surface, as clinical evaluation is more sensitive for the detection and evaluation of small mucosal lesions. However, T1 and T2 lesions may still be encountered as part of an initial evaluation or incidental presentation. While laryngoscopy can determine the superficial extent and size of a lesion, CT and MRI are central in determining deep tissue extent, invasion into adjacent tissues, and evidence of nodal metastases. Treatment options include surgical resection, chemotherapy, and/or chemoradiation therapy. Surgical options can be as limited as transoral laser microsurgery or as extensive as total laryngopharyngectomy. In this setting, the radiologist plays a vital role, as imaging interpretation will help determine the treatment regimen. Imaging findings largely dictate the T stage based on compartment/subsite location, additional subsite or adjacent tissue invasion, visible involvement of the vocal cord(s), and invasion beyond the larynx. Imaging is also key to the assessment for nodal or metastatic disease. Accurate staging is key, as overstaging could lead to unnecessary total laryngectomy, whereas understaging could contribute to treatment failure.

Usefulness of multiparametric MRI for local staging of bladder cancer

Introduction: Under staging and over staging are not uncommon with traditional MRI while staging bladder cancer. Current improvements in MRI technology due to addition of functional MR sequences that is, dynamic contrast-enhanced (DCE) imaging and diffusion-weighted imaging (DWI) have enhanced its clinical utility. The current study was designed to look for staging accuracy of multiparametric MRI (mp-MRI) that is, T2W + DCE + DWI, over conventional MRI. Material and methods: Forty patients with bladder cancer were included were subjected to mp-MRI on a 3T scanner with a phased array body coil. Four MR image sets that is, T2W, T2W + DCE, T2W + DWI, and T2W + DCE + DWI were interpreted. Accuracy of each image set was determined separately and was compared with the gold standard histopathological staging. Result: Staging accuracy of different image set increased from T2W (55%) to DCE (72.5%) to DWI (80%). Maximum accuracy was seen in mp-MRI (T2W + DWI + DCE) (87.5%). While differentiating non muscle invasive from muscle invasive disease (⩽T1 vs ⩾T2 stage) staging accuracy increased from T2W (65%) to DCE (80%) to DWI (85%) with maximum in mp-MRI (90%). Conclusion: mp-MRI offers high staging accuracy for bladder cancer.

Two-Dimensional Shear-Wave Elastography: Accuracy in Liver Fibrosis Staging Using Magnetic Resonance Elastography as the Reference Standard.

Background: The accurate staging of liver fibrosis is crucial for managing chronic liver disease (CLD). Although magnetic resonance elastography (MRE) is the reference standard for noninvasive fibrosis assessment, its cost, specialized hardware, and operational demands restrict accessibility. In contrast, two-dimensional shear-wave elastography (2D-SWE) is more affordable, accessible, and widely integrated into routine ultrasound systems. Objective: Our aim was to determine the optimal 2D-SWE cut-offs for detecting significant fibrosis (≥F2) and evaluate its diagnostic performance across fibrosis stages. Methods: In this prospective study, 71 patients with suspected CLD underwent same-day MRE and 2D-SWE. MRE-defined cut-offs categorized fibrosis stages (≥3.5 kPa for significant fibrosis). Sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), and likelihood ratios were calculated for various 2D-SWE thresholds. Results: At a 2D-SWE cut-off of 7.0 kPa, sensitivity for detecting ≥F2 fibrosis was 100% with a specificity of 85.7% and a positive likelihood ratio (LR+) of 7.0. Increasing the threshold to 8.0 kPa improved specificity to 91.8% while maintaining a sensitivity of 86.4% and achieving an AUROC of 0.89. For cirrhosis, a cut-off of 11.0 kPa achieved 100% sensitivity and 96.9% specificity. A 5.0 kPa cut-off reliably excluded abnormal stiffness with 89.1% sensitivity. Conclusions: Two-dimensional SWE is a reliable method for staging liver fibrosis. Thresholds of 7.0 kPa for screening significant fibrosis, 8.0 kPa for confirmation, and 11.0 kPa for diagnosing cirrhosis demonstrate high diagnostic accuracy. A 5.0 kPa cut-off effectively excludes abnormal liver stiffness.

The role of neuropsychological assessment in the evaluation of patients with cognitive-behavioral change due to suspected Alzheimer's disease and other causes of cognitive impairment and dementia.

The Alzheimer's Association convened a Diagnostic Evaluation, Testing, Counseling and Disclosure Clinical Practice Guideline workgroup to help combat the major global health challengessurrounding the timely detection, accurate diagnosis, and appropriate disclosure of mild cognitive impairment (MCI) or dementia due to Alzheimer's disease (AD) or other diseases that cause these types of cognitive-behavioral disorders. The newly published clinical practice guidelines are proposed as a structured approach to evaluation. The purpose of the present article is to provide a clinical perspective on the use of neuropsychology within the new framework and practice guidelines outlined under the Diagnostic Evaluation, Testing, Counseling and Disclosure of Suspected Alzheimer's Disease and Related Disorders (DETeCD-ADRD) recommendations for primary care and specialty care. Neuropsychological evaluation is a critical component in supporting early and accurate diagnosis and staging, characterizing the clinical profile, assessing trajectory over time, and providing recommendations specifically tailored to the individual and their care team. HIGHLIGHTS: Reviews theneuropsychological evaluation component of the new framework and clinical practice guidelines outlined under the Alzheimer's Association clinical practice guidelines for the Diagnostic Evaluation, Testing, Counseling and Disclosure of Suspected Alzheimer's Disease and Related Disorders (DETeCD-ADRD). Examines the utility of neuropsychological evaluation in theassessment of Alzheimer's Disease and Related Disorders (ADRD). Supports a basis for neuropsychology in early and accurate diagnosis and staging, characterizing the clinical profile, assessing trajectory over time, and providing recommendations specifically tailored to the individual and their care team.

Does lymph node dissection improve the prognosis of patients with colorectal cancer?

The number of lymph nodes (LNs) dissected during surgery has become an interesting topic. Simple intuition always leads us to believe that dissecting more LNs will result in more accurate pathological staging and assurance of surgical quality. However, when the number of LNs dissected reaches a certain threshold, the patient's prognosis does not continue to improve as the number of dissected nodes increases. Instead, an increase in the number of dissected LNs may be accompanied by a higher incidence of complications. Currently, there are only less than 40% of colorectal cancer patients undergoing adequate LN evaluation. Therefore, obtaining a sufficient number of LNs in clinical practice is extremely challenging. How to further address the insufficiency of LN dissection due to various reasons, which results in concerns of surgeons about patient prognosis, is currently a critical focus.

Laparoscopic Paraaortic Lymph Node Sampling in Gastric Cancer Patients with Suspected Paraaortic Lymph Node Metastasis

D2 lymphadenectomy is the standard approach for lymph node dissection in curable gastric cancer. However, paraaortic lymph node (PALN) dissection in addition to D2 lymphadenectomy has not been shown to improve survival rates and is therefore not routinely performed. Nevertheless, PALN sampling may be indicated for diagnostic purposes because it can provide critical information for accurate staging and treatment planning. Laparoscopic PALN sampling, however, poses significant challenges due to limited accessibility and visibility in the paraaortic region. Moreover, the proximity of major blood vessels, such as the abdominal aorta and renal vein, is another difficult aspect of the procedure. In this context, we present two cases to demonstrate practical strategies for facilitating laparoscopic PALN sampling. The procedure can be effectively performed by first identifying the ligament of Treitz and then, when necessary, fixing the small bowel mesentery to the abdominal wall using a tagging suture so that there is adequate vision and enough working space. This enables careful and precise dissection of the target tissue without compromising the feasibility and safety of the operation.

A Comprehensive Literature Review of Histopathology of Squamous Cell Carcinoma

Background: The literature on the histopathology of squamous cell carcinoma (SCC), particularly cutaneous squamous cell carcinoma (cSCC), has evolved significantly over the past decade, revealing a complex interplay of histopathologic features, molecular markers, and clinical outcomes. Literature Review: The work by (K. El-Mofty, 2014) explores histopathologic risk factors associated with oral and oropharyngeal SCC variants, particularly those related to HPV. The identification of distinct morphological characteristics shared among keratinizing neoplasms is essential for accurate diagnosis and treatment planning. The article highlights the unique behaviors of HPV-related variants, which may exhibit either favorable prognoses or aggressive metastatic potential, thus necessitating careful evaluation. The role of immunohistochemical markers in the diagnosis and staging of cSCC is further elaborated by (Bălășescu et al., 2022), who identify key characteristics that predict disease progression. Their findings suggest that immunohistochemical markers can enhance diagnostic accuracy, particularly in poorly differentiated cases, thereby informing treatment strategies. Finally, (Gabriel Cocuz et al., 2022) provide a scientometric analysis of current research directions, highlighting the sustained interest in histopathology and immunohistochemistry of cSCC. Their work suggests an ongoing recognition of the importance of personalized diagnostics and targeted therapies to improve patient outcomes. Conclusion: In conclusion, the reviewed literature underscores the complexity of cSCC histopathology and the critical need for accurate diagnosis and staging. The integration of histopathological features with molecular markers and the continual evolution of diagnostic techniques are essential for refining our understanding of SCC behavior and enhancing treatment efficacy. Ongoing research is necessary to address existing challenges and optimize patient management strategies.

The clinical applications of dual-layer spectral detector CT in digestive system diseases.

Dual-layer spectral detector CT (DLCT) has several advantages in clinical practice, this study aims to reveal the clinical applications of DLCT in digestive system diseases. We searched PubMed and Cochrane Reviews for articles published from January 1, 2010 to May 31, 2024, using the terms "dual-layer spectral detector CT" or "dual-layer CT" combined with "hepatic fat" or "hepatic fibrosis" "hepatocellular carcinoma" or "pancreatic ductal adenocarcinoma" or "pancreatic neuroendocrine tumors" or "gastric cancer" or "colorectal cancer" or "Crohn's disease" or "bowel ischemia" or "acute abdominal conditions". DLCT consists of a top layer sensitive to lower-energy photons and a bottom layer sensitive to higher-energy photons. This configuration enables simultaneous acquisition of two energy spectra from a single X-ray beam ensuring consistent spatial alignment and temporal resolution. Spectral raw images allow image post-processing to improve image quality, reduce radiation doses and contrast media doses, and generate multiple quantitative parameters. It has broad potential for early detection, accurate staging, efficacy assessment, and prognosis prediction of liver, pancreatic, and gastrointestinal diseases, as well as for the assessment of digestive system vasculature. DLCT not only provides valuable information for the clinical diagnosis and therapeutic effect evaluation of digestive system diseases but also may play a more important role in the overall management of digestive diseases and in the decision-making of individualized medicine. Question What are the advantages of DLCT compared to traditional single-energy CT in the early detection, staging, and therapeutic evaluation of digestive system diseases? Findings DLCT enhances image quality, improves tissue characterization, and allows for multi-parametric analysis, making it superior in detecting and evaluating liver, pancreatic, and gastrointestinal diseases. Clinical relevance DLCT provides high-quality, multi-parametric imaging that improves the accuracy of diagnosing digestive diseases, facilitates more precise treatment planning, and enhances monitoring of treatment response, ultimately contributing to better patient management and prognosis.

Diagnostic Efficacy of Staging Laparoscopy Compared to CT and PET-CT in Gastric Cancer: A Retrospective Cohort Analysis.

Background and Objectives: This study aimed to assess the diagnostic accuracy and prognostic significance of staging laparoscopy (SL) compared to computed tomography (CT) and positron emission tomography-computed tomography (PET-CT) in gastric cancer staging. We evaluated the ability of SL to detect occult peritoneal metastases and influence of SL on survival outcomes across cancer stages and treatment approaches. Materials and Methods: In this retrospective cohort study, 95 patients with gastric cancer underwent preoperative assessment using CT, PET-CT, and SL between 2018 and 2024. Diagnostic performance metrics were calculated for SL, CT, and PET/CT across the local, locally advanced, and metastatic stages. Survival outcomes were analyzed using Kaplan-Meier curves, and comparisons were made using log-rank tests. A multivariable Cox proportional hazards model incorporating interaction terms was used to determine the independent prognostic factors affecting survival, focusing on SL findings and cytology results. Results: The cohort comprised 75 males (78.9%) and 20 females (21.1%), with a mean age of 57.4 ± 10.1 years. The tumor location distribution was predominant in the corpus (31.1%) and cardia. Tumor staging revealed that 48.1% were classified as T3 and 28.8% as T4, respectively. Diagnostic accuracy analysis showed that SL outperformed CT and PET-CT in detecting peritoneal metastasis across all stages. Specifically, SL demonstrated a sensitivity and specificity of 85% and 95% for local disease, 92% and 80% for locally advanced disease, and 95% and 99% for metastatic disease, significantly exceeding those of CT and PET-CT. Patients with SL findings had a median overall survival (OS) of 30 months compared with 20 months for those assessed only with CT and PET-CT (p < 0.05). The stage-specific median OS for SL patients was 40 months in the local, 25 months in the locally advanced (p < 0.05), and 15 months in the metastatic disease (p < 0.01) groups, indicating significant survival benefits. Multivariable Cox regression identified SL findings as an independent factor associated with reduced mortality risk (HR: 0.70, 95% CI: 0.50-0.90, p < 0.01), while positive cytology findings predicted poorer survival (HR: 1.80, 95% CI: 1.25-2.60, p < 0.01). Interaction terms revealed that SL yielded greater survival benefits in patients with metastatic disease (hazard ratio [HR]: 0.60, p < 0.01) and those undergoing systemic therapy (HR: 0.75, p = 0.04). Conclusions: SL provides superior diagnostic accuracy and prognostic information for advanced gastric cancer staging compared with CT and PET-CT. By accurately detecting peritoneal metastasis, SL aids in optimizing treatment plans, particularly in advanced stages, thus potentially improving patient outcomes.

The Role of Dynamic Contrast Enhanced Magnetic Resonance Imaging in Evaluating Prostate Adenocarcinoma: A Partially-Blinded Retrospective Study of a Prostatectomy Patient Cohort With Whole Gland Histopathology Correlation and Application of PI-RADS or TNM Staging.

Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in the current Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS v2.1) is considered optional, with primary scoring based on T2-weighted imaging (T2WI) and diffusion weighted imaging (DWI). Our study is designed to assess the relative contribution of DCE MRI in a patient-cohort with whole mount prostate histopathology and spatially-mapped prostate adenocarcinoma (PCa) for reference. We performed a partially-blinded retrospective review of 47 prostatectomy patients with recent multi-parametric MRI (mpMRI). Scans included T2WI, DWI with apparent diffusion coefficient (ADC) mapping, and DCE imaging. Lesion conspicuity was scored on a 10-point scale with ≥ 6 considered "positive," and image quality was assessed on a 4-point scale for each sequence. The diagnostic contribution of DCE images was evaluated on a 4-point scale. The mpMRI studies were assigned PI-RADS scores and tumor, node, metastasis (TNM) T-stage with blinded comparison to spatially-mapped whole-mount pathology. Results were compared to the prospective clinical reports, which used standardized PI-RADS templates that emphasize T2WI, DWI and ADC. Per lesion sensitivity for PCa was 93.5%, 82.6%, 63.0%, and 58.7% on T2WI, DCE, ADC and DWI, respectively. Mean lesion conspicuity was 8.5, 7.9, 6.2, and 6.1, on T2W, DCE, ADC and DWI, respectively. The higher values on T2WI and DCE imaging were not significantly different from each other but were both significantly different from DWI and ADC (p < 0.001). DCE scans were determined to have a marked diagnostic contribution in 83% of patients, with the most common diagnostic yield being detection of contralateral peripheral zone tumor or delineating presence/absence of extra-prostatic extension (EPE), contributing to more accurate PCa staging by PI-RADS or TNM, as compared to histopathology. We demonstrate that DCE may contribute to lesion detection and local staging as compared to T2WI plus DWI-ADC alone and that lesion conspicuity using DCE is markedly improved as compared to DWI-ADC. These findings support modification of PI-RADS v2.1 to include use of DCE acquisitions and that a TNM staging is feasible on mpMRI as compared to surgical pathology.

The Depth Estimation and Visualization of Dermatological Lesions: Development and Usability Study.

Thus far, considerable research has been focused on classifying a lesion as benign or malignant. However, there is a requirement for quick depth estimation of a lesion for the accurate clinical staging of the lesion. The lesion could be malignant and quickly grow beneath the skin. While biopsy slides provide clear information on lesion depth, it is an emerging domain to find quick and noninvasive methods to estimate depth, particularly based on 2D images. This study proposes a novel methodology for the depth estimation and visualization of skin lesions. Current diagnostic methods are approximate in determining how much a lesion may have proliferated within the skin. Using color gradients and depth maps, this method will give us a definite estimate and visualization procedure for lesions and other skin issues. We aim to generate 3D holograms of the lesion depth such that dermatologists can better diagnose melanoma. We started by performing classification using a convolutional neural network (CNN), followed by using explainable artificial intelligence to localize the image features responsible for the CNN output. We used the gradient class activation map approach to perform localization of the lesion from the rest of the image. We applied computer graphics for depth estimation and developing the 3D structure of the lesion. We used the depth from defocus method for depth estimation from single images and Gabor filters for volumetric representation of the depth map. Our novel method, called red spot analysis, measures the degree of infection based on how a conical hologram is constructed. We collaborated with a dermatologist to analyze the 3D hologram output and received feedback on how this method can be introduced to clinical implementation. The neural model plus the explainable artificial intelligence algorithm achieved an accuracy of 86% in classifying the lesions correctly as benign or malignant. For the entire pipeline, we mapped the benign and malignant cases to their conical representations. We received exceedingly positive feedback while pitching this idea at the King Edward Memorial Institute in India. Dermatologists considered this a potentially useful tool in the depth estimation of lesions. We received a number of ideas for evaluating the technique before it can be introduced to the clinical scene. When we map the CNN outputs (benign or malignant) to the corresponding hologram, we observe that a malignant lesion has a higher concentration of red spots (infection) in the upper and deeper portions of the skin, and that the malignant cases have deeper conical sections when compared with the benign cases. This proves that the qualitative results map with the initial classification performed by the neural model. The positive feedback provided by the dermatologist suggests that the qualitative conclusion of the method is sufficient.

Preoperative detection of extraprostatic tumor extension in patients with primary prostate cancer utilizing [68Ga]Ga-PSMA-11 PET/MRI

ObjectivesRadical prostatectomy (RP) is a common intervention in patients with localized prostate cancer (PCa), with nerve-sparing RP recommended to reduce adverse effects on patient quality of life. Accurate pre-operative detection of extraprostatic extension (EPE) remains challenging, often leading to the application of suboptimal treatment. The aim of this study was to enhance pre-operative EPE detection through multimodal data integration using explainable machine learning (ML).MethodsPatients with newly diagnosed PCa who underwent [68Ga]Ga-PSMA-11 PET/MRI and subsequent RP were recruited retrospectively from two time ranges for training, cross-validation, and independent validation. The presence of EPE was measured from post-surgical histopathology and predicted using ML and pre-operative parameters, including PET/MRI-derived features, blood-based markers, histology-derived parameters, and demographic parameters. ML models were subsequently compared with conventional PET/MRI-based image readings.ResultsThe study involved 107 patients, 59 (55%) of whom were affected by EPE according to postoperative findings for the initial training and cross-validation. The ML models demonstrated superior diagnostic performance over conventional PET/MRI image readings, with the explainable boosting machine model achieving an AUC of 0.88 (95% CI 0.87–0.89) during cross-validation and an AUC of 0.88 (95% CI 0.75–0.97) during independent validation. The ML approach integrating invasive features demonstrated better predictive capabilities for EPE compared to visual clinical read-outs (Cross-validation AUC 0.88 versus 0.71, p = 0.02).ConclusionML based on routinely acquired clinical data can significantly improve the pre-operative detection of EPE in PCa patients, potentially enabling more accurate clinical staging and decision-making, thereby improving patient outcomes.Critical relevance statementThis study demonstrates that integrating multimodal data with machine learning significantly improves the pre-operative detection of extraprostatic extension in prostate cancer patients, outperforming conventional imaging methods and potentially leading to more accurate clinical staging and better treatment decisions.Key PointsExtraprostatic extension is an important indicator guiding treatment approaches.Current assessment of extraprostatic extension is difficult and lacks accuracy.Machine learning improves detection of extraprostatic extension using PSMA-PET/MRI and histopathology.Graphical

Turn-On NIR-II Polymer Dots with Large Stokes Shift for In Vivo Visualizing Dynamical Brain Zinc in Alzheimer's Disease Mouse.

It is a critical and broad prospect to evaluate ion levels and monitor their dynamic changes in the brain for early diagnosis, in-depth mechanism investigation, and accurate staging of neurodegenerative diseases including Alzheimer's disease (AD). It is still a great challenge to in vivo track Zn2+ levels in the brain by fluorescence imaging due to the drawbacks including short emission wavelength, poor selectivity and sensitivity, and unfavorable penetration across the blood-brain barrier (BBB) for currently developed fluorescent probes. We herein engineer a fluorescent probe with a large Stokes shift of 256 nm, NNDPTQ Pdots, which display substantial Zn2+-specific turn-on response in the NIR II region with the longest emission of 1064 nm up to now. The probe shows a fast response within seconds, high selectivity, low-nanomolar affinity of 6 nM, low detection limit of 3.4 nM, and efficient BBB-permeability efficacy of 37%. The results of brain imaging demonstrate that brain Zn2+ level in AD mice is substantially higher than normal mice and also is elevated with the prolonging of AD-bearing time. This study may provide a promising fluorescent indicator for in vivo tracing of brain Zn2+ levels to reveal AD pathogenesis.