LV-predominant arrhythmogenic cardiomyopathy related to pathogenic DSP-variant.

Key Clinical Message: In contrast to previously thought, arrhythmogenic cardiomyopathy can occur exclusively in the left ventricle in association with autosomal dominant mutation, even without any skin manifestations. Abstract: We present a case of a 43-year-old male with left ventricle (LV)-predominant arrhythmogenic cardiomyopathy (ACM) caused by a novel p.Q1830 mutation in the desmoplakin (DSP) gene. The patient had a significant family history of sudden cardiac death (SCD) and presented with presyncope and exertional dyspnea. The patient's electrocardiography (ECG) showed frequent premature ventricular complexes (PVCs) with bigeminy and couplet patterns. Cardiac magnetic resonance imaging (CMR) revealed late gadolinium enhancement of the left ventricle (LV) and ventricular systolic dysfunction, suggesting LV-predominant arrhythmogenic cardiomyopathy. The patient was started on guideline-directed medical therapy (GDMT), and an implantable cardioverter-defibrillator (ICD) was implanted for primary prevention. The patient reported significant improvement in his heart failure symptoms at the 2-year follow-up. The article highlights the importance of timely diagnosis with multimodality imaging and genetic testing and management of the rare DSP-related LV-predominant ACM associated with a high risk of SCD.

Superior ophthalmic vein thrombosis in unique double origin: a case report.

Superior ophthalmic vein thrombosis (SOVT) is a rare orbital pathology. It can cause serious complications if it isn´t diagnosed appropriately. It can be secondary to many etiologies, septic or aseptic ones. Diabetic ketoacidosis (DKA) may disturb the vascular endothelium and promote a prothrombotic state. The presence of which is related to a significantly increased risk of morbidity and mortality. We report the case of a 45-year-old woman who presented a SOVT revealing DKA. Orbit magnetic resonance imaging (MRI) showed thrombosis of the right superior ophthalmic vein. A treatment based on thrombolytic treatment, associated with antibiotic coverage and a glycemic balance was initiated. This case highlights the importance of considering both infection and diabetes as an important part of the diagnosis and management of SOVT.

Prediction of hemorrhage in placenta previa: Radiomics analysis of pelvic MRI images.

INTRODUCTION: Prediction of intraoperative massive hemorrhage is still challenging in placenta previa. Radiomics analysis has been investigated as a new evaluation method for analyzing medical images. We used radiomics analysis on placental magnetic resonance imaging (MRI) images to predict intraoperative hemorrhage in placenta previa. METHODS: We used the sagittal MRI T2-weighted sequence in placenta previa. Using the rectangular region from the uterine os to the anterior wall, we extracted 97 radiomics features. We also collected patient demographics and blood test data as clinical variables. Combining these radiomics features and clinical variables, logistic regression models with a stepwise method were built to predict the risk of hemorrhage, defined as blood loss of > 2000 ml. We evaluated the prediction performance of the models using accuracy and area under the curve (AUC), also analyzing the important variables for the prediction by stepwise methods. RESULTS: We enrolled a total of 63 placenta previa cases including 30 hemorrhage cases from two institutes. The model combining clinical variables and radiomics features showed the best prediction performance with an accuracy of 0.70 and an AUC of 0.69 in the internal validation data, and accuracy of 0.41 and an AUC of 0.70 in the external validation data, compared with human experts (accuracy of 0.62). Regarding variable selection, two radiomics features. 'original_glrlm_LowGrayLevelRunEmphasis,' and 'diagnostics_Image-original_Minimum,' were important predictors for hemorrhage by the stepwise method. DISCUSSION: Radiomics features based on MRI could be used as effective predictive variables for hemorrhage in placenta previa. Radiomics analysis of placental imaging could lead to further analysis of quantitative variables related to obstetric diseases.

Recommendations for defining giant cell arteritis fast-track clinics. English version.

A German expert committee recommends defining fast-track clinics (FTC) for the acute diagnosis of giant cell arteritis (GCA) as follows: easy and prompt reachability at least on weekdays, scheduling appointments ideally within 24 h, examination by a specialist with GCA expertise, ≥ 2 experts per FTC, ≥ 50 patients with suspected GCA per year, sonologists with ≥ 300 (≥ 50) temporal and axillary artery examinations, adherence to standard operating procedures, availability of an ≥ 18 (≥ 15) MHz and a lower frequency linear ultrasound probe, and collaboration with partners for neurology and ophthalmology consultations, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT, possibly CT), and for temporal artery biopsy.

Topological differences of striato-thalamo-cortical circuit in functional brain network between premature ejaculation patients with and without depression.

INTRODUCTION: Premature ejaculation (PE), a common male sexual dysfunction, often accompanies by abnormal psychological factors, such as depression. Recent neuroimaging studies have revealed structural and functional brain abnormalities in PE patients. However, there is limited neurological evidence supporting the comorbidity of PE and depression. This study aimed to explore the topological changes of the functional brain networks of PE patients with depression. METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 60 PE patients (30 with depression and 30 without depression) and 29 healthy controls (HCs). Functional brain networks were constructed for all participants based on rs-fMRI data. The nodal parameters including nodal centrality and efficiency were calculated by the method of graph theory analysis and then compared between groups. In addition, the results were corrected for multiple comparisons by family-wise error (FWE) (p < .05). RESULTS: PE patients with depression had increased degree centrality and global efficiency in the right pallidum, as well as increased degree centrality in the right thalamus when compared with HCs. PE patients without depression showed increased degree centrality in the right pallidum and thalamus, as well as increased global efficiency in the right precuneus, pallidum, and thalamus when compared with HCs. PE patients with depression demonstrated decreased degree centrality in the right pallidum and thalamus, as well as decreased global efficiency in the right precuneus, pallidum, and thalamus when compared to those without depression. All the brain regions above survived the FWE correction. CONCLUSION: The results suggested that increased and decreased functional connectivity, as well as the capability of global integration of information in the brain, might be related to the occurrence of PE and the comorbidity depression in PE patients, respectively. These findings provided new insights into the understanding of the pathological mechanisms underlying PE and those with depression.

Predicting disease recurrence in breast cancer patients using machine learning models with clinical and radiomic characteristics: a retrospective study.

BACKGROUND: The goal is to use three different machine learning models to predict the recurrence of breast cancer across a very heterogeneous sample of patients with varying disease kinds and stages. METHODS: A heterogeneous group of patients with varying cancer kinds and stages, including both triple-negative breast cancer (TNBC) and non-triple-negative breast cancer (non-TNBC), was examined. Three distinct models were created using the following five machine learning techniques: Adaptive Boosting (AdaBoost), Random Under-sampling Boosting (RUSBoost), Extreme Gradient Boosting (XGBoost), support vector machines (SVM), and Logistic Regression. The clinical model used both clinical and pathology data in conjunction with the machine learning algorithms. The machine learning algorithms were combined with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) imaging characteristics in the radiomic model, and the merged model combined the two types of data. Each technique was evaluated using several criteria, including the receiver operating characteristic (ROC) curve, precision, recall, and F1 score. RESULTS: The results suggest that the integration of clinical and radiomic data improves the predictive accuracy in identifying instances of breast cancer recurrence. The XGBoost algorithm is widely recognized as the most effective algorithm in terms of performance. CONCLUSION: The findings presented in this study offer significant contributions to the field of breast cancer research, particularly in relation to the prediction of cancer recurrence. These insights hold great potential for informing future investigations and clinical interventions that seek to enhance the accuracy and effectiveness of recurrence prediction in breast cancer patients.

Metastatic Gastric Adenocarcinoma in the Inguinal Hernia Sac Diagnosed Radiologically: A Case Report.

Macroscopic tumor implants in the hernia sac are a very rare condition. They occur as a result of the implantation of malignant cells in the malignant ascites from the inguinal canal to the hernia sac. In this case report, we share the clinical and radiological findings of the macroscopic tumoral implants in the hernia sac at the level of the inguinal canal and scrotum in a male patient aged 65 years with a history of total gastrectomy for gastric adenocarcinoma and developing malignant ascites six months after the surgery.

Impact of Functional Mitral Regurgitation on Left Ventricular Strain in Nonischemic Dilated Cardiomyopathy Patients with Type 2 Mellitus Diabetes: A Magnetic Resonance Feature Tracking Study.

BACKGROUND: The impact of functional mitral regurgitation and type 2 mellitus diabetes (T2DM) on left ventricular (LV) strain in nonischemic dilated cardiomyopathy (NIDCM) patients remains unclear. PURPOSE: To evaluate the impact of mitral regurgitation severity on LV strain, and explore additive effect of T2DM on LV function across varying mitral regurgitation severity levels in NIDCM patients. STUDY TYPE: Retrospective. POPULATION: 352 NIDCM (T2DM-) patients (49.1 ± 14.6 years, 67% male) (207, 85, and 60 no/mild, moderate, and severe mitral regurgitation) and 96 NIDCM (T2DM+) patients (55.2 ± 12.4 years, 77% male) (47, 30, and 19 no/mild, moderate, and severe mitral regurgitation). FIELD STRENGTH/SEQUENCE: 3.0 T/balanced steady-state free precession sequence. ASSESSMENT: LV geometric parameters and strain were measured and compared among groups. Determinants of LV strain were investigated. STATISTICAL TEST: Student's t-test, Mann-Whitney U test, one-way ANOVA, Kruskal-Wallis test, univariable and multivariable linear regression. P < 0.05 was considered statistically significant. RESULTS: LV GLPS and longitudinal PDSR decreased gradually with increasing mitral regurgitation severity in NIDCM patients with T2DM(GLPS: -5.7% ± 2.1% vs. -4.3% ± 1.6% vs. -2.6% ± 1.3%; longitudinal PDSR:0.5 ± 0.2 sec-1 vs. 0.4 ± 0.2 sec-1 vs. 0.3 ± 0.1 sec-1). NIDCM (T2DM+) demonstrated decreased GCPS and GLPS in the no/mild subgroup, reduced LV GCPS, GLPS, and longitudinal PDSR in the moderate subgroup, and reduced GRPS, GCPS, GLPS, and longitudinal PDSR in the severe subgroup compared with NIDCM (T2DM-) patients. Multivariable regression analysis identified that mitral regurgitation severity (ß = -0.13, 0.15, and 0.25 for GRPS, GCPS, and GLPS) and the presence of T2DM (ß = 0.14 and 0.13 for GCPS and GLPS) were independent determinants of LV strains in NIDCM patients. DATA CONCLUSION: Increased mitral regurgitation severity is associated with reduced LV strains in NIDCM patients with T2DM. The presence of T2DM exacerbated the decline of LV function across various mitral regurgitation levels in NIDCM patients, resulting in reduced LV strains. TECHNICAL EFFICACY: Stage 3.

Pivotal role of the synovioentheseal complex in the imaging of arthritis and rheumatic diseases.

Imaging plays a key role in the diagnosis and management of rheumatic diseases. Although joints and periarticular tissue are commonly involved in rheumatic diseases, entheses further away from joints, such as in the Achilles tendon or plantar fascia insertion onto the calcaneus, as well as skin and subcutaneous tissue, are among other -sometimes overlooked- targets. The link of enthesitis, which describes inflammation at the insertions of ligaments, tendons, or joint capsules, with spondyloarthritis (SpA) was established just before the turn of the century as a characteristic feature based on imaging studies with histopathological correspondence. To highlight the association between enthesitis and synovitis in SpA, the anatomical unit of the "synovioentheseal complex" (SEC) and the concepts of "functional enthesis" and "articular enthesis," apart from the better known "insertional enthesis," were introduced to encompass other inflammatory lesions associated with SpA. Studies from the last two decades revealed the involvement of the SEC in rheumatic and non-rheumatic disorders with different pathogeneses. Although such involvement is sometimes distinctive, it does not necessarily point to a specific diagnosis at other times. Nevertheless, the potential of SEC inflammation in the differentiation of SpA from other forms of arthritis remains important. The purpose of this review was to provide essential information concerning the involvement of the SEC in the diagnosis of rheumatic diseases and arthritis, focusing on imaging characteristics.

Contrast-enhanced 3D black-blood magnetic resonance imaging for diagnosis of cerebral venous thrombosis.

PURPOSE: Cerebral venous thrombosis (CVT) is often under-recognized on routine magnetic resonance imaging (MRI) examinations without concomitant magnetic resonance venography (MRV). Contrast-enhanced black-blood MRI (BBMRI) based on a three-dimensional T1-weighted variable-flip-angle turbo spin echo sequence, one of the sequences used routinely in our practice, has the potential for detection of thrombi in patients with CVT. The aim of this study is to evaluate the diagnostic performance and enhancement patterns of contrast-enhanced three-dimensional BBMRI for the diagnosis of CVT. MATERIALS AND METHODS: Contrast-enhanced BBMRI and contrast-enhanced MRV sequences of 64 patients, acquired from June 2018 to January 2021, were retrospectively reviewed by neuroradiologists for detection of CVT in each venous sinus segment. Diagnostic performance values were calculated for contrast-enhanced BBMRI based on enhancement patterns. RESULTS: Of 749 venous segments from 64 patients analyzed, CVT was demonstrated in 41 venous segments from 12 patients on contrast-enhanced MRV (CE MRV). Thick wall enhancement and total enhancement patterns were dominantly demonstrated in thrombosed segments. Compared with contrast-enhanced MRV, contrast-enhanced BBMRI had a patient-based sensitivity and specificity of 100% and 98.1%, respectively, and a segment-based sensitivity and specificity of 87.8% and 96.2%, respectively. The positive predictive value of contrast-enhanced BBMRI in detecting CVT was 92.3% (patient-based) and 57.1% (segment-based), and the negative predictive value was 100% (patient-based) and 99.3% (segment-based). CONCLUSION: Contrast-enhanced BBMRI has high diagnostic performance in detection and diagnosis of CVT. This sequence may be useful to recognize CVT when dedicated CE MRV was not performed in patients with nonspecific neurological symptoms.

MRI features of ovarian teratomas with somatic-type malignancy and mature cystic teratomas.

PURPOSE: We evaluated the magnetic resonance imaging (MRI) features of ovarian teratomas with somatic-type malignancy (TSMs) and benign ovarian mature cystic teratomas (MCTs) to determine the diagnostic contribution of the MRI findings for differentiating these two teratomas. METHODS: We compared the MRI findings between ovarian TSMs (n = 10) and MCTs (n = 193), and we conducted a receiver operating characteristic (ROC) analysis to determine the MRI findings' contribution to the differentiation of TSMs from MCTs. RESULTS: The maximum diameters of whole lesion and the largest solid component in the TSMs were larger than those of the MCTs (p = 0.0001 and p < 0.0001, respectively). Fat tissue in solid components was seen in 73/116 (62.9%) MCTs but in none of the TSMs (p = 0.0001). Ring-like enhancement in solid components was seen in 60/116 (51.7%) MCTs and none of the TSMs (p = 0.0031). On dynamic contrast-enhanced MRI (DCE MRI), all of the solid components in the TSMs showed a high- or intermediate-risk time intensity curve (TIC), and those in 113 of the 116 (97.4%) MCTs showed a low-risk TIC (p < 0.0001). The area under the curve of the ROC analysis using the high-/intermediate-risk TIC on DCE MRI was the highest (0.99) for differentiating TSMs from MCTs: sensitivity 100%, specificity 97.4%, positive predictive value 75.0%, negative predictive value 100%, and accuracy, 97.6%. CONCLUSION: Compared to ovarian MCTs, ovarian TSMs are larger and have larger solid components with high- or intermediate-risk TICs on DCE MRI. Ovarian MCTs frequently show small solid components with fat tissue, ring-like enhancement, and a low-risk TIC on DCE MRI.

Dorsal wrist ganglion: clinical and imaging correlation in symptomatic population based on high-field MRI.

OBJECTIVES: To determine prevalence in the symptomatic population of dorsal mucoid cysts centered on dorsal capsuloscapholunate septum (DCSS) using high-field magnetic resonance imaging (MRI) for anatomoclinical and epidemiological correlations. MATERIALS AND METHODS: This single-center retrospective study analyzed all 3-Tesla MRIs consecutively performed for painful wrists in 295 patients. Two blinded readers performed measurements. The protocol included T1 spin echo and 3D proton density sequences with fat saturation. Inter-observer reliability was assessed using kappa and intra-class correlation coefficients for cyst detection and volumetry, respectively. Disagreements concerning cyst detection were resolved by a consensus reading. Cyst size, relationship to extrinsic and scapholunate ligaments (SL), continuity of SL, minimum distance to the posterior interosseous nerve (PIN), cyst communication with joint, and anatomical classifications of cysts were analyzed. Correlation tests were performed to assess associations. RESULTS: Two-hundred ninety-five patients (mean age 39.6 +/- 15.6 (standard deviation), 161 males) were evaluated for detection of dorsal wrist cysts identified in 150/295. In this subgroup, the mean age was 38.7 years (15-75), the sex ratio of 0.6 (59% women), and the median volume cyst of 8.7 mm3 (0.52-2555). Cyst detection, volume, and major axis measurements showed very high agreement between observers, respectively, 0.89, 0.96, and 0.91. 42 patients had dorsal SL pain. A weak negative correlation was found between distance to PIN and dorsal SL pain (r = -0.2415; p < 0.05) and a weak positive correlation between Guérini's classification and dorsal SL pain (r = 0.2466; p < 0.05). CONCLUSION: High-field MRI is the modality of choice for the detection, anatomical, and volumetric assessment of dorsal cysts. Preoperative assessment will be aided by the proposed revised anatomical classification. CLINICAL RELEVANCE STATEMENT: High-field MRI is the modality of choice for the anatomical study of dorsal ganglion cysts. It allows the radiologist to accurately describe the anatomical relationships, size, and visibility of the pedicle, essential information for the surgeon's preoperative assessment. KEY POINTS: Dorsal mucoid wrist ganglion is a condition for which prevalence remains to be determined. High-field MRI is a reproducible imaging modality for the detection and assessment of dorsal wrist cysts. High-field MRI has a key role in the preoperative management of dorsal mucoid cysts.

Can a nomogram predict apical prostate cancer pathology upgrade from fusion biopsy to final pathology? A multicenter study.

BACKGROUND: This study evaluates the efficacy of a nomogram for predicting the pathology upgrade of apical prostate cancer (PCa). METHODS: A total of 754 eligible patients were diagnosed with apical PCa through combined systematic and magnetic resonance imaging (MRI)-targeted prostate biopsy followed by radical prostatectomy (RP) were retrospectively identified from two hospitals (training: 754, internal validation: 182, internal-external validation: 148). A nomogram for the identification of apical tumors in high-risk pathology upgrades through comparing the results of biopsy and RP was established incorporating statistically significant risk factors based on univariable and multivariable logistic regression. The nomogram's performance was assessed via the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA). RESULTS: Univariable and multivariable analysis identified age, targeted biopsy, number of targeted cores, TNM stage, and the prostate imaging-reporting and data system score as significant predictors of apical tumor pathological progression. Our nomogram, based on these variables, demonstrated ROC curves for pathology upgrade with values of 0.883 (95% CI, 0.847-0.929), 0.865 (95% CI, 0.790-0.945), and 0.840 (95% CI, 0.742-0.904) for the training, internal validation and internal-external validation cohorts respectively. Calibration curves showed good consistency between the predicted and actual outcomes. The validation groups also showed great generalizability with the calibration curves. DCA results also demonstrated excellent performance for our nomogram with positive benefit across a threshold probability range of 0-0.9 for the training and internal validation group, and 0-0.6 for the internal-external validation group. CONCLUSION: The nomogram, integrating clinical, radiological, and pathological data, effectively predicts the risk of pathology upgrade in apical PCa tumors. It holds significant potential to guide clinicians in optimizing the surgical management of these patients.

Verification of image quality improvement by deep learning reconstruction to 1.5 T MRI in T2-weighted images of the prostate gland.

This study aimed to evaluate whether the image quality of 1.5 T magnetic resonance imaging (MRI) of the prostate is equal to or higher than that of 3 T MRI by applying deep learning reconstruction (DLR). To objectively analyze the images from the 13 healthy volunteers, we measured the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the images obtained by the 1.5 T scanner with and without DLR, as well as for images obtained by the 3 T scanner. In the subjective, T2W images of the prostate were visually evaluated by two board-certified radiologists. The SNRs and CNRs in 1.5 T images with DLR were higher than that in 3 T images. Subjective image scores were better for 1.5 T images with DLR than 3 T images. The use of the DLR technique in 1.5 T MRI substantially improved the SNR and image quality of T2W images of the prostate gland, as compared to 3 T MRI.

Correlations among MRI-based cervical and thoracic vertebral bone quality score, CT-based Hounsfield Unit score, and DEXA t-score in assessment of bone mineral density.

BACKGROUND: Further optimization of the validated vertebral bone quality (VBQ) score using magnetic resonance imaging (MRI) may expand its clinical utility for bone mineral density (BMD) assessment. This study evaluated the correlations among cervical and thoracic VBQ scores, the validated Hounsfield Unit (HU) measured on computed tomography (CT), and dual-energy x-ray absorptiometry (DEXA) values. METHODS: We retrieved the medical and radiographic records of 165 patients who underwent synchronous MRI of the cervical and thoracic spine, as well as DEXA and CT imaging of the spine obtained within 1 year of each other between 2015 and 2022. Radiographic data consisted of the MRI-based cervical and thoracic VBQ scores, CT-based HU, and DEXA T-scores of the spine and hip. Patient age, sex, body mass index (BMI), and ethnicity were also obtained. RESULTS: Mean cervical and thoracic VBQ scores were 3.99 ± 1.68 and 3.82 ± 2.11, respectively. Mean HU and DEXA T-scores of the spine and hip were 135.75 ± 60.36, -1.01 ± 1.15, and -0.47 ± 2.27. All correlations among VBQ, HU, and DEXA were insignificant except for weak correlations between cervical and thoracic VBQ, and cervical VBQ and HU. No correlations were observed between radiographic scores and patient age or BMI. No differences based on ethnicity or sex were observed with respect to cervical or thoracic VBQ, HU, or DEXA. CONCLUSION: Cervical and thoracic VBQ scores are distinct from Hounsfield Unit and DEXA values. VBQ scoring in the cervical and thoracic spine is not influenced by patient age, ethnicity, sex, or BMI.

Prediction of Clinically Significant Prostate Cancer by a Specific Collagen-related Transcriptome, Proteome, and Urinome Signature.

BACKGROUND AND OBJECTIVE: While collagen density has been associated with poor outcomes in various cancers, its role in prostate cancer (PCa) remains elusive. Our aim was to analyze collagen-related transcriptomic, proteomic, and urinome alterations in the context of detection of clinically significant PCa (csPCa, International Society of Urological Pathology [ISUP] grade group ≥2). METHODS: Comprehensive analyses for PCa transcriptome (n = 1393), proteome (n = 104), and urinome (n = 923) data sets focused on 55 collagen-related genes. Investigation of the cellular source of collagen-related transcripts via single-cell RNA sequencing was conducted. Statistical evaluations, clustering, and machine learning models were used for data analysis to identify csPCa signatures. KEY FINDINGS AND LIMITATIONS: Differential expression of 30 of 55 collagen-related genes and 34 proteins was confirmed in csPCa in comparison to benign prostate tissue or ISUP 1 cancer. A collagen-high cancer cluster exhibited distinct cellular and molecular characteristics, including fibroblast and endothelial cell infiltration, intense extracellular matrix turnover, and enhanced growth factor and inflammatory signaling. Robust collagen-based machine learning models were established to identify csPCa. The models outcompeted prostate-specific antigen (PSA) and age, showing comparable performance to multiparametric magnetic resonance imaging (mpMRI) in predicting csPCa. Of note, the urinome-based collagen model identified four of five csPCa cases among patients with Prostate Imaging-Reporting and Data System (PI-IRADS) 3 lesions, for which the presence of csPCa is considered equivocal. The retrospective character of the study is a limitation. CONCLUSIONS AND CLINICAL IMPLICATIONS: Collagen-related transcriptome, proteome, and urinome signatures exhibited superior accuracy in detecting csPCa in comparison to PSA and age. The collagen signatures, especially in cases of ambiguous lesions on mpMRI, successfully identified csPCa and could potentially reduce unnecessary biopsies. The urinome-based collagen signature represents a promising liquid biopsy tool that requires prospective evaluation to improve the potential of this collagen-based approach to enhance diagnostic precision in PCa for risk stratification and guiding personalized interventions. PATIENT SUMMARY: In our study, collagen-related alterations in tissue, and urine were able to predict the presence of clinically significant prostate cancer at primary diagnosis.

Magnetic Resonance Imaging (MRI) Not Inferior to the Gold Standard of Diagnostic Arthroscopy for Identification of Wrist Ligamentous Pathology.

Accurate diagnoses of wrist ligamentous injuries are critical to guiding the proper treatment pathway for patients with these pathologies. While advancements in imaging continue and magnetic resonance imaging (MRI) is valuable, diagnostic arthroscopy remains superior, particularly if involvement of the non-central triangular fibrocartilage complex (TFCC), scapholunate interosseous ligament (SLIL), or lunotriquetral interosseous ligament (LTIL) is suspected based on history and physical exam, and even in the face of negative MRI findings.

Multiparametric MRI-based radiomics analysis for prediction of lymph node metastasis and survival outcome in gastric cancer: A dual-center study.

RATIONALE AND OBJECTIVES: Gastric cancer (GC) is highly heterogeneous, and accurate preoperative assessment of lymph node status remains challenging. We aimed to develop a multiparametric MRI-based model for predicting lymph node metastasis (LNM) in GC and to explore its prognostic implications. MATERIALS AND METHODS: In this dual-center retrospective study, 479 GC patients undergoing preoperative multiparametric MRI before radical gastrectomy were enrolled. 1595 imaging features were extracted from T2-weighted imaging, apparent diffusion coefficient maps, and contrast-enhanced T1-weighted imaging (cT1WI), respectively. Feature selection steps, including the Boruta and Simulated Annealing algorithms, were conducted to identify key features. Different radiomics models (RMs) based on the single- and multiple-sequence were constructed. The performance of various RMs in predicting LNM was assessed in terms of discrimination, calibration, and clinical usefulness. Additionally, Kaplan-Meier survival curves were employed to estimate differences in disease-free survival (DFS) and overall survival (OS). RESULTS: The multi-sequence radiomics model (MRM) achieved area under the curves (AUCs) of 0.774 [95 % confidence interval (CI), 0.703-0.845], 0.721 (95 % CI, 0.593-0.850), and 0.720 (95 % CI, 0.639-0.801) in the training and two validation cohorts, respectively, outperforming the single-sequence RMs. Notably, the RM derived from cT1WI demonstrated superior performance compared to the other two single-sequence models. Furthermore, the proposed MRM exhibited a significant association with DFS and OS in GC patients (both P < 0.05). CONCLUSION: The multiparametric MRI-based radiomics model, derived from primary lesions, demonstrated moderate performance in predicting LNM and survival outcomes in patients with GC, which could provide valuable insights for personalized treatment strategies.

Implications of pretreatment extramural venous invasion in rectal cancer patients: A population-based study.

AIM: Extramural venous invasion detected by MRI (mrEMVI) has in several expert centre studies been identified as an important prognostic factor in rectal cancer, and in guiding neoadjuvant therapy. However, population-based evidence for mrEMVI as a predictor for recurrent disease is lacking. METHOD: This was a multicentre retrospective study based on the Swedish Colorectal Cancer Registry. The study period encompassed patients operated with abdominal resection for rectal cancer 2017-2021, with follow-up until January 2023. Patients diagnosed at hospitals with radiological registry data coverage <90% or with metastatic disease were excluded. Pretreatment mrEMVI constituted exposure, while recurrence-free survival was the main outcome. Distant and local recurrence, and overall survival were secondary outcomes, and pretreatment and postoperative scenarios were explored using multivariable Cox regression with multiple imputation. Hazard ratios (HRs) with 95% confidence intervals (CIs) were reported. RESULTS: A total of 2737 patients from 13 hospitals were eligible for analysis. Pretreatment mrEMVI was reported in 14.5% of patients, while 71.9% had negative findings and 13.6% had missing data. In the pretreatment scenario, mrEMVI was an independent predictor for worse recurrence-free survival with an adjusted HR of 1.64 (95% CI: 1.31-2.06). In the postoperative MDT setting, the influence of mrEMVI on recurrence-free survival decreased with an adjusted HR of 1.27 (95% CI: 1.00-1.61). CONCLUSION: mrEMVI at diagnosis is an independent predictor of recurrence-free survival in an unselected population of rectal cancer patients undergoing abdominal resection.

Effects of axial loading and positions on lumbar spinal stenosis: an MRI study using a new axial loading device.

OBJECTIVE: A new axial loading device was used to investigate the effects of axial loading and positions on lumbar structure and lumbar spinal stenosis. METHODS: A total of 40 patients sequentially underwent 4 examinations: (1) the psoas-relaxed position MRI, (2) the extended position MRI, (3) the psoas-relaxed position axial loading MRI, (4) the extended position axial loading MRI. The dural sac cross-sectional area, sagittal vertebral canal diameter, disc height and ligamentum flavum thickness of L3-4, L4-5, L5-S1 and lumbar lordosis angle were measured and compared. A new device with pneumatic shoulder-hip compression mode was used for axial loading. RESULTS: In the absence of axial loading, there was a significant reduction in dural sac cross-sectional area with extension only seen at the L3-4 (p = 0.033) relative to the dural sac area in the psoas-relaxed position. However, with axial loading, there was a significant reduction in dural sac cross-sectional area at all levels in both psoas-relaxed (L3-4, p = 0.041; L5-S1, p = 0.005; L4-5, p = 0.002) and extension (p < 0.001) positions. The sagittal vertebral canal diameter and disc height were significantly reduced at all lumbar levels with axial loading and extension (p < 0.001); however, in psoas-relaxed position, the sagittal vertebral canal diameter was only reduced with axial loading at L3-4 (p = 0.018) and L4-5 (p = 0.011), and the disc height was reduced with axial-loading at all levels (L3-4, p = 0.027; L5-S1, p = 0.001; L4-5, p < 0.001). The ligamentum flavum thickness and lumbar lordosis in extension position had a statistically significant increase compared to psoas-relaxed position with or without axial loading (p < 0.001). CONCLUSION: Both axial loading and extension of lumbar may exacerbate lumbar spinal stenosis. Axial loading in extension position could maximally aggravate lumbar spinal stenosis, but may cause some patients intolerable. For those patients, axial loading MRI in psoas-relaxed position may be a good choice.