Rare case of mantle cell lymphoma of the lacrimal sac

ABSTRACT Mantle cell lymphoma of the ocular and periorbital regions is extremely rare but should be considered in the differential diagnosis of lesions affecting the periorbital tissues. In this study, we present a rare case of mantle cell lymphoma of the lacrimal sac in a 65-year-old male presenting with a mass in the lacrimal sac region and epiphora. After clinical examinations and imaging studies, the mucocele was misdiagnosed. Considering the unexpected findings during external dacryocystorhinostomy, a frozen biopsy was performed, which confirmed the diagnosis of lymphoma.

Parameters to assess the necessity of adjuvant therapy for early-stage oral squamous cell carcinoma.

OBJECTIVE: One-third of head and neck squamous cell carcinomas are early-stage oral cavity squamous cell carcinomas (OCSCC). Despite a high curative rate, 20% of early-stage OCSCC patients do not achieve long-term survival. This study evaluates the role of adjuvant therapy (ADJ) in delaying disease progression and prolonging survival. METHODS: This single-institute retrospective cohort study enrolled 481 early-stage OCSCC patients, 16% (78/481) of whom received ADJ. It was reported according to the STROBE guidelines. Cox proportional hazards regression and Kaplan-Meier survival curves were employed to identify suitable candidates for ADJ. RESULTS: The 5-year locoregional recurrence-free survival (LR-RFS) and overall survival rates were 73.2% and 84.9%, respectively. Positive margins and advanced depth of invasion (DOI) were independent predictors of LR-RFS. For patients with positive margins, adjuvant chemoradiotherapy (CRT) was superior to adjuvant radiotherapy alone in improving LR-RFS (hazard ratios for adjuvant CRT vs. none, 0.042; adjuvant radiotherapy alone vs. none, 0.702). Excluding positive margins, advanced DOI was the most critical factor in assessing the need for ADJ. Positive margins and advanced DOI were more appropriate criteria than EORTC 22931/RTOG 9501 for evaluating adjuvant CRT. CONCLUSIONS: Adjuvant CRT was indicated for patients with positive margins and advanced DOI to improve survival outcomes.

The American Cancer Society National Lung Cancer Roundtable strategic plan: Promoting guideline-concordant lung cancer staging.

Accurate staging improves lung cancer survival by increasing the chances of delivering stage-appropriate therapy. However, there is underutilization of, and variability in, the use of guideline-recommended diagnostic tests used to stage lung cancer. Consequently, the American Cancer Society National Lung Cancer Roundtable (ACS NLCRT) convened the Triage for Appropriate Treatment Task Group-a multidisciplinary expert and stakeholder panel-to identify knowledge and/or resource gaps contributing to guideline-discordant staging and make recommendations to overcome these gaps. The task group determined the following: Gap 1: facilitators of and barriers to guideline-concordant staging are incompletely understood; Recommendation 1: identify facilitators of and barriers to guideline-concordant lung cancer staging; Gap 2: the level of evidence supporting staging algorithms is low-to-moderate; Recommendation 2: prioritize comparative-effectiveness studies evaluating lung cancer staging; Gap 3: guideline recommendations vary across professional societies; Recommendation 3: harmonize guideline recommendations across professional societies; Gap 4: existing databases do not contain sufficient information to measure guideline-concordant staging; Recommendation 4: augment existing databases with the information required to measure guideline-concordant staging; Gap 5: health systems do not have a performance feedback mechanism for lung cancer staging; Recommendation 5: develop and implement a performance feedback mechanism for lung cancer staging; Gap 6: patients rarely self-advocate for guideline-concordant staging; Recommendation 6: increase opportunities for patient self-advocacy for guideline-concordant staging; and Gap 7: current health policies do not motivate guideline-concordant lung cancer staging; Recommendation 7: organize a representative working group under the ACS NLCRT that promotes policies that motivate guideline-concordant lung cancer staging. PLAIN LANGUAGE SUMMARY: Staging-determining the degree of cancer spread-is important because it helps clinicians choose the best cancer treatment. Receiving the best cancer treatment leads to the best possible patient outcomes. Practice guidelines are intended to help clinicians stage patients with lung cancer. However, lung cancer staging in the United States often varies from practice guideline recommendations. This report identifies seven opportunities to improve lung cancer staging.

The accuracy and quality of image-based artificial intelligence for muscle-invasive bladder cancer prediction.

PURPOSE: To evaluate the diagnostic performance of image-based artificial intelligence (AI) studies in predicting muscle-invasive bladder cancer (MIBC). (2) To assess the reporting quality and methodological quality of these studies by Checklist for Artificial Intelligence in Medical Imaging (CLAIM), Radiomics Quality Score (RQS), and Prediction model Risk of Bias Assessment Tool (PROBAST). MATERIALS AND METHODS: We searched Medline, Embase, Web of Science, and The Cochrane Library databases up to October 30, 2023. The eligible studies were evaluated using CLAIM, RQS, and PROBAST. Pooled sensitivity, specificity, and the diagnostic performances of these models for MIBC were also calculated. RESULTS: Twenty-one studies containing 4256 patients were included, of which 17 studies were employed for the quantitative statistical analysis. The CLAIM study adherence rate ranged from 52.5% to 75%, with a median of 64.1%. The RQS points of each study ranged from 2.78% to 50% points, with a median of 30.56% points. All models were rated as high overall ROB. The pooled area under the curve was 0.85 (95% confidence interval (CI) 0.81-0.88) for computed tomography, 0.92 (95% CI 0.89-0.94) for MRI, 0.89 (95% CI 0.86-0.92) for radiomics and 0.91 (95% CI 0.88-0.93) for deep learning, respectively. CONCLUSION: Although AI-powered muscle-invasive bladder cancer-predictive models showed promising performance in the meta-analysis, the reporting quality and the methodological quality were generally low, with a high risk of bias. CRITICAL RELEVANCE STATEMENT: Artificial intelligence might improve the management of patients with bladder cancer. Multiple models for muscle-invasive bladder cancer prediction were developed. Quality assessment is needed to promote clinical application. KEY POINTS: Image-based artificial intelligence models could aid in the identification of muscle-invasive bladder cancer. Current studies had low reporting quality, low methodological quality, and a high risk of bias. Future studies could focus on larger sample sizes and more transparent reporting of pathological evaluation, model explanation, and failure and sensitivity analyses.

Predicting tumor invasion depth in gastric cancer: developing and validating multivariate models incorporating preoperative IVIM-DWI parameters and MRI morphological characteristics.

INTRODUCTION: Accurate assessment of the depth of tumor invasion in gastric cancer (GC) is vital for the selection of suitable patients for neoadjuvant chemotherapy (NAC). Current problem is that preoperative differentiation between T1-2 and T3-4 stage cases in GC is always highly challenging for radiologists. METHODS: A total of 129 GC patients were divided into training (91 cases) and validation (38 cases) cohorts. Pathology from surgical specimens categorized patients into T1-2 and T3-4 stages. IVIM-DWI and MRI morphological characteristics were evaluated, and a multimodal nomogram was developed. The MRI morphological model, IVIM-DWI model, and combined model were constructed using logistic regression. Their effectiveness was assessed using receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). RESULTS: The combined nomogram, integrating preoperative IVIM-DWI parameters (D value) and MRI morphological characteristics (maximum tumor thickness, extra-serosal invasion), achieved the highest area under the curve (AUC) values of 0.901 and 0.883 in the training and validation cohorts, respectively. No significant difference was observed between the AUCs of the IVIM-DWI and MRI morphological models in either cohort (training: 0.796 vs. 0.835, p = 0.593; validation: 0.794 vs. 0.766, p = 0.79). CONCLUSION: The multimodal nomogram, combining IVIM-DWI parameters and MRI morphological characteristics, emerges as a promising tool for assessing tumor invasion depth in GC, potentially guiding the selection of suitable candidates for neoadjuvant chemotherapy (NAC) treatment.

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.

Immunohistochemical ERG positivity is associated with decreased PSMA expression and lower visibility in corresponding [68Ga]Ga-PSMA-11 PET scans of primary prostate cancer.

PURPOSE: TMPRSS2:ERG gene fusion negatively regulates PSMA expression in prostate adenocarcinoma (PCa) cell lines. Therefore, immunohistochemical (IHC) ERG expression, a surrogate for an underlying ERG rearrangement, and PSMA expression patterns in radical prostatectomy (RPE) specimens of primary PCa, including corresponding PSMA-PET scans were investigated. METHODS: Two cohorts of RPE samples (total n=148): In cohort #1 (n=62 patients) with available RPE and preoperative [68Ga]Ga-PSMA-11 PET, WHO/ISUP grade groups, IHC-ERG (positive vs. negative) and IHC-PSMA expression (% PSMA-negative tumour area, PSMA%neg) were correlated with the corresponding SUVmax. In the second cohort #2 (n=86 patients) including RPE only, same histopathological parameters were evaluated. RESULTS: Cohort #1: PCa with IHC-ERG expression (35.5%) showed significantly lower IHC-PSMA expression and lower SUVmax values on the corresponding PET scans. Eight of 9 PCa with negative PSMA-PET scans had IHC-ERG positivity, and confirmed TMPRSS2::ERG rearrangement. In IHC-PSMA positive PCa, IHC-ERG positivity was significantly associated with lower SUVmax values. In cohort #2, findings of higher IHC-PSMA%neg and IHC-ERG expression was confirmed with only 0-10% PSMA%neg tumour areas in IHC-ERG-negative PCa. CONCLUSION: IHC-ERG expression is significantly associated with more heterogeneous and lower IHC-PSMA tissue expression in two independent RPE cohorts. There is a strong association of ERG positivity in RPE tissue with lower [68Ga]Ga-PSMA-11 uptake on corresponding PET scans. Results may serve as a base for future biomarker development to enable tumour-tailored, individualized imaging approaches.

Japanese classification of pancreatic carcinoma by the Japan Pancreas Society: Eighth edition.

In 2023, the Japan Pancreas Society (JPS) published the new eighth edition of the Japanese classification of pancreatic carcinoma. We present here an excerpted version in English, based on the latest edition. The major changes in this revision are as follows: In the eighth edition of the Union for International Cancer Control (UICC), the T category was changed to be based on tumor size; however, the eighth edition of the Japanese classification retains the previous T category based on local invasion factors. Lymph nodes have been renamed, and regional lymph nodes have been defined by location. Peritoneal cytology, which was not previously included in distant metastasis (M), has now been included in the M category. Moreover, significant additions have been made regarding the pathological diagnosis of endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNAB) and criteria for histological assessment of the effects after chemotherapy and radiation therapy. Although this classification is aimed at carcinoma originating in the pancreas, not in the bile duct or duodenum, if the differentiation of the primary organ is difficult, this classification should be applied. It is also desirable to describe tumors other than carcinoma and metastatic tumors to the pancreas in accordance with this classification.

Medical costs of lung cancer by stage, histology and first-line treatment modality in the Netherlands (2012-2021).

INTRODUCTION: Lung cancer is a leading cause of mortality worldwide, with lung cancer treatment presenting a significant financial burden. The treatment landscape has recently shifted, seeing an increase in targeted- and immunotherapies. Such treatments are expensive, but estimates of the medical costs of the lung cancer treatment pathway largely predate their introduction. METHODS: We link medical expenditures of individuals resident in the Netherlands (n = 19.2 m) for 2013-2021 to tumour-level (n = 137,129, incident 2012-2021) Netherlands Cancer Registry data. We estimate lung cancer-attributable costs by phase of care (initial, continuing and terminal), stratified by cancer stage and histology, and observe trends in medical costs over time. RESULTS: We estimate mean costs over the lung cancer treatment pathway to be €48,443 per patient. Total medical costs are highest in the initial phase, followed by the terminal and continuing phase. Monthly treatment for stage IV lung cancer is significantly more expensive than for early-stage disease (€8293 per month of initial care relative to €3228 for stage IA). Stage IV lung cancer has become significantly more expensive to treat 2018-2021 relative to 2013-2017, with monthly expenditures rising 55 % in initial care and 148 % in continuing care. Population-wide, we find €900.6 million spent on lung cancer care in 2021, €433 million more than in 2016, of which €307.3 million is attributed to per-patient expenditure trends. CONCLUSIONS: Treatment advances are quickly inflating medical costs for late-stage lung cancer. Policy makers should carefully evaluate the cost-effectiveness of novel treatments, and incorporate stage-specific treatment costs in evaluating interventions for early detection.

Enhancing Preoperative Assessment of Endometrial Cancer: The Role of Diffusion-Weighted Magnetic Resonance Imaging in Evaluating Myometrial Invasion.

BACKGROUND: Endometrial cancer (EC) is the most common gynecological malignancy. Accurate preoperative staging is essential for guiding treatment. The depth of myometrial invasion is a key prognostic factor. This prospective study aimed to evaluate the added benefit of diffusion-weighted imaging (DWI) compared to T2-weighted imaging (T2WI) and dynamic contrast-enhanced MRI (DCE-MRI) for the preoperative assessment of myometrial invasion in EC. AIM AND OBJECTIVES: The aim of this prospective study was to evaluate the added benefit of DWI in the preoperative assessment of myometrial invasion in EC, in comparison with T2WI and DCE-MRI. The objectives were to assess the imaging characteristics of endometrial carcinoma on T2WI, DCE, and DW MR, to assess the depth of myometrial invasion and overall stage in EC patients, to compare the diagnostic performance of DCE-MRI with that of DW-MRI combined with T2WI, to describe how MR imaging findings can be combined with tumor histologic features and grading to guide treatment planning, and to evaluate the pitfalls and limitations of DCE and DW MR in the assessment of EC. MATERIALS AND METHODS: Thirty-one patients with histologically confirmed EC underwent preoperative pelvic MRI on a 1.5T scanner. T2WI, DWI (b-values 0, 1000 s/mm2), and DCE-MRI were performed. Two radiologists independently assessed myometrial invasion on T2WI, T2WI + DWI, and T2WI + DCE-MRI. Histopathology after hysterectomy was the reference standard. Diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each MRI protocol, with separate analyses for superficial (<50%) and deep (≥50%) myometrial invasions. RESULTS: The accuracy for assessing superficial invasion was 61.3% for T2WI, 87.1% for T2WI + DWI, and 87.1% for T2WI + DCE-MRI. For deep invasion, accuracy was 64.5% for T2WI, 90.3% for T2WI + DWI, and 90.3% for T2WI + DCE-MRI. Sensitivity, specificity, PPV, and NPV for T2WI + DWI and T2WI + DCE-MRI were high and comparable (88.9-91.7%) for both superficial and deep invasions. T2WI had markedly lower sensitivity and specificity. The differences between T2WI and the functional MRI protocols were statistically significant (p < 0.01). CONCLUSION: DWI and DCE-MRI significantly improve the diagnostic performance of MRI for the preoperative assessment of myometrial invasion depth in EC compared to T2WI alone. DWI + T2WI and DCE-MRI + T2WI demonstrate comparable high accuracy. DWI may be preferable since it is faster and avoids contrast administration.

Survival of patients with mucosal melanoma in Cali, Colombia: a retrospective cohort study.

BACKGROUND: Mucosa melanoma is a rare condition with aggressive behavior and a less favorable prognosis compared to cutaneous melanoma. The objective of this study was to estimate the overall survival and clinical outcomes of patients diagnosed with mucosal melanoma in a Colombian hospital. METHODS: A retrospective cohort study was conducted at Fundación Valle del Lili, a single center located in Cali, Colombia. Patients aged ≥ 18 years, both sexes, diagnosed with mucosal melanoma by histopathology study were included between 2010-2019. Patients who received extra-institutional treatment or whose vital status was unknown during follow-up were excluded. Demographic, clinical and laboratory data were obtained from medical records and laboratory and pathology databases. A descriptive analysis was performed. Survival analysis was conducted using the Kaplan-Meier method. RESULTS: A total of 23 patients were included. Median age was 63 years old (IQR: 57-68) and 52.2% were woman. Clinical stage was 34.8% early, 26.1% locally advanced and 39.1% metastatic. The main primary locations were nasopharynx (30.4%), genitals (26.1%), rectum (21.7%), oral cavity (13%) and paranasal sinuses (8.7%). The majority received surgery (30.4%) and immunotherapy (26.1%) as first line treatment. Overall survival at one year was 80.8%, at three years 44.3%, and at five years 36.9%. CONCLUSION: Mucosal melanoma is a rare, aggressive disease with adverse oncological outcomes due to late diagnosis and limited treatment options. This study provides real-world data in a single-center of Colombia.

Subdivision of pT1N0 (American Joint Committee on Cancer 8th edition) distal cholangiocarcinoma for adjuvant chemotherapy consideration.

BACKGROUND: The adjuvant S-1 trial affirmed adjuvant chemotherapy for biliary tract cancer but excluded pT1N0 distal cholangiocarcinoma (DCC) according to the seventh edition of the American Joint Committee on Cancer (AJCC) classification. The introduction of tumor depth of invasion (DOI) for T-classification in the eighth edition complicates identifying DCC patients less likely to benefit from adjuvant chemotherapy. METHODS: Our cohort consisted of 185 patients with DCC who underwent pancreaticoduodenectomy between 2002 and 2019. We compared clinicopathological factors and survival outcomes between pT1N0 patients in the seventh edition and those in the eighth edition. New DOI cutoffs for subdividing pT1N0 (8th edition) patients were evaluated to identify patients less likely to benefit from adjuvant chemotherapy. RESULTS: Transitioning to the eighth edition increased in pT1N0 cases from eight to 46. The 5-year cumulative recurrence rates of them were 14.3% for the seventh edition and 28.3% for the eighth edition. We proposed a DOI cutoff of <2 mm, at which the 5-year cumulative recurrence rate was 11.5%. CONCLUSION: The eighth AJCC classification revealed that a significant proportion of pT1N0 DCC patients were at risk for recurrence. A DOI cutoff of <2 mm may be considered to potentially improve patient selection for adjuvant chemotherapy.

Pictorial review of multiparametric MRI in bladder urothelial carcinoma with variant histology: pearls and pitfalls.

Bladder cancer (BC), predominantly comprising urothelial carcinomas (UCs), ranks as the tenth most common cancer worldwide. UCs with variant histology (variant UC), including squamous differentiation, glandular differentiation, plasmacytoid variant, micropapillary variant, sarcomatoid variant, and nested variant, accounting for 5-10% of cases, exhibit more aggressive and advanced tumor characteristics compared to pure UC. The Vesical Imaging-Reporting and Data System (VI-RADS), established in 2018, provides guidelines for the preoperative evaluation of muscle-invasive bladder cancer (MIBC) using multiparametric magnetic resonance imaging (mpMRI). This technique integrates T2-weighted imaging (T2WI), dynamic contrast-enhanced (DCE)-MRI, and diffusion-weighted imaging (DWI) to distinguish MIBC from non-muscle-invasive bladder cancer (NMIBC). VI-RADS has demonstrated high diagnostic performance in differentiating these two categories for pure UC. However, its accuracy in detecting muscle invasion in variant UCs is currently under investigation. These variant UCs are associated with a higher likelihood of disease recurrence and require precise preoperative assessment and immediate surgical intervention. This review highlights the potential value of mpMRI for different variant UCs and explores the clinical implications and prospects of VI-RADS in managing these patients, emphasizing the need for careful interpretation of mpMRI examinations including DCE-MRI, particularly given the heterogeneity and aggressive nature of variant UCs. Additionally, the review addresses the fundamental MRI reading procedures, discusses potential causes of diagnostic errors, and considers future directions in the use of artificial intelligence and radiomics to further optimize the bladder MRI protocol.

Evaluating the Efficacy and Accuracy of AI-Assisted Diagnostic Techniques in Endometrial Carcinoma: A Systematic Review.

Diagnosing endometrial carcinoma correctly is essential for appropriate treatment, as it is a major health risk. As machine learning (ML) and artificial intelligence (AI) have grown in popularity, so has interest in their potential to improve cancer diagnosis accuracy. In the context of endometrial cancer, this study attempts to examine the efficacy as well as the accuracy of AI-assisted diagnostic approaches. Additionally, it aims to methodically evaluate the contribution of AI and ML techniques to the improvement of endometrial cancer diagnosis. Following PRISMA guidelines, we performed a thorough search of numerous databases, including Medline via Ovid, PubMed, Scopus, Web of Science, and Google Scholar. Ten years were searched, encompassing both basic and advanced research. Peer-reviewed papers and original research studies that explicitly looked at the application of AI/ML in endometrial cancer diagnosis were the main targets of the well-defined selection criteria. Using the Critical Appraisal Skills Programme (CASP) methodology, two independent researchers conducted a thorough screening process and quality assessment of included studies. The review found a notable inclination towards the effective use of AI in endometrial carcinoma diagnostics, namely in the identification and categorization of endometrial cancer. Artificial intelligence models, particularly Convolutional Neural Networks (CNNs) and deep learning algorithms have shown remarkable precision in detecting endometrial cancer. They frequently achieve or even exceed the diagnostic proficiency of human specialists. The use of artificial intelligence in medical diagnostics signifies revolutionary progress in the field of oncology. AI-assisted diagnostic tools have demonstrated the potential to improve the precision and effectiveness of cancer diagnosis, namely in cases of endometrial carcinoma. This innovation not only enhances the quality of patient care but also indicates a transition towards more individualized and efficient treatment approaches in the field of oncology. The advancement of AI technology is expected to play a crucial role in medical diagnostics, particularly in the field of cancer detection and treatment, perhaps leading to a significant transformation in the approach to these areas.

Pictorial review of the diagnosis of muscle-invasive bladder cancer using vesical imaging-reporting and data system (VI-RADS).

The Vesical Imaging-Reporting and Data System (VI-RADS) is a standard magnetic resonance imaging (MRI) and diagnostic method for muscle-invasive bladder cancer that was published in 2018. Several studies have demonstrated that VI-RADS has high diagnostic power and reproducibility. However, reading VI-RADS requires a certain amount of expertise, and radiologists need to be aware of the various pitfalls. MRI of the bladder includes T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCEI). T2WI is excellent for understanding anatomy. DWI and DCEI show high contrast between the tumor and normal anatomical structures and are suitable for staging local tumors. Bladder tumors are classified into five categories according to their size and morphology and their positional relationship to the bladder wall based on the VI-RADS diagnostic criteria. If the T2WI, DWI, and DCEI categories are the same, the category is the VI-RADS category. If the categories do not match, the DWI category is the VI-RADS category. If image quality of DWI is not evaluable, the DCEI category is the final category. In many cases, DWI is dominant, but this does not mean that T2WI and DCEI can be omitted from the reading of the bladder. In this educational review, typical and atypical teaching cases are demonstrated, and how to resolve misdiagnosis and the limitations of VI-RADS are discussed. The most important aspect of VI-RADS reading is to practice multiparametric reading with a solid understanding of the characteristics and role of each sequence and an awareness of the various pitfalls.

Utility of FDG PET-CT in CT Stage IA non-small cell lung cancer: The New Zealand Te Whatu Ora Northern region experience.

INTRODUCTION: Our objective was to investigate the utility of fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET-CT) in assessing CT Stage 1A non-small cell lung cancer (NSCLC) in patients under consideration for curative treatment. Performing FDG PET-CT in these patients may lead to unnecessary delays in treatment if it can be shown to provide no added value. METHODS: We retrospectively reviewed 735 lesions in 653 patients from the New Zealand Te Whatu Ora Northern region lung cancer database with suspected or pathologically proven Stage 1A NSCLC on CT scan who also underwent FDG PET-CT imaging. We determined how often FDG PET-CT findings upstaged patients and then compared to pathological staging where available. RESULTS: FDG PET-CT provided an overall upstaging rate of 9.7%. Category-specific rates were 0% in Tis, 0.9% in T1mi, 7.4% in T1a, 10% in T1b and 12% in T1c groups. The percentage of lesions upstaged on FDG PET-CT that remained Stage 1A was 100% in T1mi, 100% in T1a, 47.1% in T1b and 40.7% in T1c groups. The P value was statistically significant at 0.004, indicating upstaging beyond Stage 1A was dependent on T category. CONCLUSION: Our data suggests that FDG PET-CT is indicated for T1b and T1c lesions but is of limited utility in Tis, T1mi and T1a lesions. Adopting a more targeted approach and omitting FDG PET-CT in patients with Tis, T1mi, and T1a lesions may benefit all patients with lung cancer by improving accessibility and treatment timelines.

Does clinical T1N0 GGN really require checking for distant metastasis during initial staging for lung cancer?

BACKGROUND: Accurate clinical staging is crucial for selection of optimal oncological treatment strategies in non-small cell lung cancer (NSCLC). Although brain MRI, bone scintigraphy and whole-body PET/CT play important roles in detecting distant metastases, there is a lack of evidence regarding the indication for metastatic staging in early NSCLCs, especially ground-grass nodules (GGNs). Our aim was to determine whether checking for distant metastasis is required in cases of clinical T1N0 GGN. METHODS: This was a retrospective study of initial staging using imaging tests in patients who had undergone complete surgical R0 resection for clinical T1N0 Stage IA NSCLC. RESULTS: A total of 273 patients with cT1N0 GGNs (n = 183) or cT1N0 solid tumors (STs, n = 90) were deemed eligible. No cases of distant metastasis were detected on initial routine imaging evaluations. Among all cT1N0M0 cases, there were 191 incidental findings on various modalities (128 in the GGN). Most frequently detected on brain MRI was cerebral leukoaraiosis, which was found in 98/273 (35.9%) patients, while cerebral infarction was detected in 12/273 (4.4%) patients. Treatable neoplasms, including brain meningioma and thyroid, gastric, renal and colon cancers were also detected on PET/CT (and/or MRI). Among those, 19 patients were diagnosed with a treatable disease, including other-site cancers curable with surgery. CONCLUSIONS: Extensive staging (MRI, scintigraphy, PET/CT etc.) for distant metastasis is not required for patients diagnosed with clinical T1N0 GGNs, though various imaging modalities revealed the presence of adventitious diseases with the potential to increase surgical risks, lead to separate management, and worsen patient outcomes, especially in elderly patients. If clinically feasible, it could be considered to complement staging with whole-body procedures including PET/CT.

Development and validation of a nomogram for predicting cancer-specific survival in small-bowel adenocarcinoma patients using the SEER database.

BACKGROUND: Small bowel adenocarcinoma (SBA) is a rare gastrointestinal malignancy forwhich survival is hampered by late diagnosis, complex responses to treatment, and poor prognosis. Accurate prognostic tools are crucial for optimizing treatment strategies and improving patient outcomes. This study aimed to develop and validate a nomogram based on the Surveillance, Epidemiology, and End Results (SEER) database to predict cancer-specific survival (CSS) in patients with SBA and compare it to traditional American Joint Committee on Cancer (AJCC) staging. METHODS: We analyzed data from 2,064 patients diagnosed with SBA between 2010 and 2020 from the SEER database. Patients were randomly assigned to training and validation cohorts (7:3 ratio). Kaplan‒Meier survival analysis, Cox multivariate regression, and nomograms were constructed for analysis of 3-year and 5-year CSS. The performance of the nomograms was evaluated using Harrell's concordance index (C-index), the area under the receiver operating characteristic (ROC) curve, calibration curves, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). RESULTS: Multivariate Cox regression identified sex, age at diagnosis, marital status, tumor site, pathological grade, T stage, N stage, M stage, surgery, retrieval of regional lymph nodes (RORLN), and chemotherapy as independent covariates associated with CSS. In both the training and validation cohorts, the developed nomograms demonstrated superior performance to that of the AJCC staging system, with C-indices of 0.764 and 0.759, respectively. The area under the curve (AUC) values obtained by ROC analysis for 3-year and 5-year CSS prediction significantly surpassed those of the AJCC model. The nomograms were validated using calibration and decision curves, confirming their clinical utility and superior predictive accuracy. The NRI and IDI indicated the enhanced predictive capability of the nomogram model. CONCLUSION: The SEER-based nomogram offers a significantly superior ability to predict CSS in SBA patients, supporting its potential application in clinical decision-making and personalized approaches to managing SBA to improve survival outcomes.

A preoperative scoring system for predicting the extraprostatic extension of prostate cancer following radical prostatectomy using magnetic resonance imaging and clinical factors.

PURPOSE: We aimed to develop a preoperative prediction model for extraprostatic extension (EPE) in prostate cancer (PCa) patients following radical prostatectomy (RP) using MRI and clinical factors. METHODS: This retrospective study enrolled 266 consecutive patients who underwent RP for PCa in 2022. These patients were divided into a training set (n = 187) and a test set (n = 79) through random assignment. The evaluated variables included age, prostate-specific antigen (PSA) level, prostate volume, PSA density (PSAD), index tumor length on MRI, Prostate Imaging-Reporting and Data System (PI-RADS) category, and EPE-related MRI features as defined by PI-RADS v2.1. A predictive model was constructed through multivariable logistic regression and subsequently translated into a scoring system. The performance of this scoring system in terms of prediction and calibration was assessed using C statistics and the Hosmer‒Lemeshow test. RESULTS: Among patients in the training and test cohorts, 74 (39.6%) and 25 (31.6%), respectively, exhibited EPE after RP. The formulated scoring system incorporated the following factors: PSAD, index tumor length, bulging prostatic contour, and tumor-capsule interface > 10 mm as identified on MRI. This scoring system demonstrated strong prediction performance for EPE in both the training (C statistic, 0.87 [95% confidence interval, 0.86-0.87]) and test cohorts (C statistic, 0.85 [0.83-0.89]). Furthermore, the scoring system exhibited good calibration in both cohorts (P = 0.988 and 0.402, respectively). CONCLUSION: Our scoring system, built upon MRI features defined by the PI-RADS, offers valuable assistance in assessing the likelihood of EPE after RP.

Value of orthogonal axial MR images in preoperative T staging of gastric cancer.

PURPOSE: To assess the value of orthogonal axial images (OAI) of MRI in gastric cancer T staging. METHODS: This retrospective study enrolled 133 patients (median age, 63 [range, 24-85] years) with gastric adenocarcinoma who underwent both CT and MRI followed by surgery. MRI lacking or incorporating OAI and CT images were evaluated, respectively. Diagnostic performance (accuracy, sensitivity, and specificity) for each T stage, overall diagnostic accuracy and rates of over- and understaging were quantified employing pathological T stage as a reference standard. The McNemar's test was performed to compare the overall accuracy. RESULTS: Among patients with pT1-pT4 disease, MRI with OAI (accuracy: 88.7-94.7%, sensitivity: 66.7-93.0%, specificity: 91.5-100.0%) exhibited superior diagnostic performance compared to MRI without OAI (accuracy: 81.2-88.7%, sensitivity: 46.2-83.1%, specificity: 85.5-99.1%) and CT (accuracy: 88.0-92.5%, sensitivity: 53.3-90.1%, specificity: 88.7-98.1%). The overall accuracy of MRI with OAI was significantly higher (83.5%) than that of MRI without OAI (67.7%) (p < .001). However, there was no significant difference in the overall accuracy of MRI with OAI and CT (78.9%) (p = .35). The over- and understaging rates of MRI with OAI (12.0, 4.5%) were lower than those of MRI without OAI (21.8, 10.5%) and CT (12.8, 8.3%). CONCLUSION: OAI play a pivotal role in the T staging of gastric cancer. MRI incorporating OAI demonstrated commendable performance for gastric cancer T-staging, with a slight tendency toward its superiority over CT.