Spontaneous intracranial hypotension: Exploring the viability of non-contrast FLAIR as a substitute for contrast-enhanced T1WI in assessing pachymeningeal thickening.

PURPOSE: To avoid contrast administration in spontaneous intracranial hypotension (SIH), some studies suggest accepting diffuse pachymeningeal hyperintensity (DPMH) on non-contrast fluid-attenuated inversion recovery (FLAIR) as an equivalent sign to diffuse pachymeningeal enhancement (DPME) on contrast-enhanced T1WI (T1ce), despite lacking thorough performance metrics. This study aimed to comprehensively explore its feasibility. METHODS: In this single-center retrospective study, between April 2021 and November 2023, brain MRI examinations of 43 patients clinically diagnosed with SIH were assessed using 1.5 and 3.0 Tesla MRI scanners. Two radiologists independently assessed the presence or absence of DPMH on FLAIR and DPME on T1ce, with T1ce serving as a gold-standard for pachymeningeal thickening. The contribution of the subdural fluid collections to DPMH was investigated with quantitative measurements. Using Cohen's kappa statistics, interobserver agreement was assessed. RESULTS: In 39 out of 43 patients (90.7%), pachymeningeal thickening was observed on T1ce. FLAIR sequence produced an accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 72.1%, 71.8%, 75.0%, 96.6%, and 21.4% respectively, for determining pachymeningeal thickening. FLAIR identified pachymeningeal thickening in 28 cases; however, among these, 21 cases (75%) revealed that the pachymeningeal hyperintense signal was influenced by subdural fluid collections. False-negative rate for FLAIR was 28.2% (11/39). CONCLUSION: The lack of complete correlation between FLAIR and T1ce in identifying pachymeningeal thickening highlights the need for caution in removing contrast agent administration from the MRI protocol of SIH patients, as it reveals a major criterion (i.e., pachymeningeal enhancement) of Bern score.

Risk Factors of Open Surgery Conversion in Laparoscopic Partial Nephrectomy to Achieve Nephron Sparing.

OBJECTIVES: We aimed to evaluate the risk factors for the conversion from laparoscopic partial nephrectomy (LPN) to open surgery to achieve partial nephrectomy (PN). METHODS: Data from patients who underwent LPN between June 2020 and September 2023 were analyzed retrospectively. Patients in whom the PN procedure could be completed laparoscopically were recorded as the 'Fully Laparoscopic' (FL) group (n = 97), and those converted to open surgery from laparoscopy were recorded as the 'Conversion to Open' (CTO) group (n = 10). The demographic and pathologic variables were compared between groups. Regression analyses were used to define predictor factors, and receiver operating characteristic analysis was used to define the cut-off value of the surgical bleeding volume. RESULTS: Conversion to open surgery was found in 10/107 patients (9.3%). There was no statistical difference between groups in demographic and pathologic variables. Intraoperative blood loss volume, upper pole localized tumor, and posterior localized tumor were found to be statistically higher in the CTO group (p = 0.001, p = 0.001, and p = 0.043, respectively). Furthermore, these factors were only found to be statistically significant predictors of conversion to open surgery in both univariate and multivariate regression analyses. 235 cc was found to be the cut-off value of intraoperative blood loss volume for predicting conversion to open surgery (p = 0.001). CONCLUSION: Using these predictive factors in clinical practice, treatment planning will lead to the possibility of starting the treatment directly with open surgery instead of minimally invasive options, and it may also provide a chance of being prepared for the possibility of conversion to open surgery peroperatively.

A New Nephrometry Score for Predicting Positive Surgical Margin After Laparoscopic Partial Nephrectomy.

PURPOSE: To introduce the KESKIN ratio as a novel predictor of positive surgical margin (PSM) after laparoscopic partial nephrectomy (PN) and to evaluate other clinical characteristics and nephrometry scores (including RENAL, PADUA, and C-index) for predicting PSM. METHODS: We retrospectively analyzed 95 patients who underwent laparoscopic PN between June 2020 and April 2023. The KESKIN ratio was defined for all patients. The KESKIN ratio, tumor and patient-related paramaters, and nephrometry scores were analyzed to predict PSM. RESULTS: Positive surgical margin was found in 12 of 95 patients (12.6%). There was no statistical difference between the PSM and negative surgical margin (NSM) groups in RENAL, PADUA, and C-index scores. Only the KESKIN ratio was found to be a statistically significant predictor of PSM in both univariate and multivariate regression analysis (p = 0.007 and p = 0.043, respectively). Mean endophytic diameter and endophytic percentage were found to be statistically significant predictors of PSM in only univariate analysis (p = 0.005 and p = 0.01, respectively). The value of 0.5 was determined as the cut-off value for the KESKIN ratio. Values higher than 0.5 indicate an increase in PSM. CONCLUSIONS: The KESKIN ratio is a novel, easily measurable, and calculable image-based parameter that can be used to predict PSM after laparascopic PN. If externally validated in a larger patient population, the KESKIN ratio may be used in future versions of the current nephrometry scoring systems for predicting the PSM.

Reproducibility of rCBV in glioblastomas using T2*-weighted perfusion MRI: an evaluation of sampling, normalization, and experience.

PURPOSE: The reproducibility of relative cerebral blood volume (rCBV) measurements among readers with different levels of experience is a concern. This study aimed to investigate the inter-reader reproducibility of rCBV measurement of glioblastomas using the hotspot method in dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-MRI) with various strategies. METHODS: In this institutional review board-approved single-center study, 30 patients with glioblastoma were retrospectively evaluated with DSC-MRI at a 3.0 Tesla scanner. Three groups of reviewers, including neuroradiologists, general radiologists, and radiology residents, calculated the rCBV based on the number of regions of interest (ROIs) and reference areas. For statistical analysis of feature reproducibility, the intraclass correlation coefficient (ICC) and Bland-Altman plots were used. Analyses were made among individuals, reader groups, reader-group pooling, and a population that contained all of them. RESULTS: For individuals, the highest inter-reader reproducibility was observed between neuroradiologists [ICC: 0.527; 95% confidence interval (CI): 0.21-0.74] and between residents (ICC: 0.513; 95% CI: 0.20-0.73). There was poor reproducibility in the analyses of individuals with different levels of experience (ICC range: 0.296-0.335) and in reader-wise and group-wise pooling (ICC range: 0.296-0.335 and 0.397-0.427, respectively). However, an increase in ICC values was observed when five ROIs were used. In an analysis of all strategies, the ICC for the centrum semiovale was significantly higher than that for contralateral white matter (P < 0.001). CONCLUSION: The inter-reader reproducibility of rCBV measurement was poor to moderate regardless of whether it was calculated by neuroradiologists, general radiologists, or residents, which may indicate the need for automated methods. Choosing five ROIs and using the centrum semiovale as a reference area may increase reliability for all users.

Can Only the Shape Feature in Radiomics Help Machine Learning Show That Bladder Cancer Has Invaded Muscles?

OBJECTIVES: The presence of muscle invasion is an important factor in establishing a treatment strategy for bladder cancer (BCa). The aim of this study is to reveal the diagnostic performance of radiomic shape features in predicting muscle-invasive BCa. METHODS: In this study, 60 patients with histologically proven BCa who underwent a preoperative MRI were retrospectively recruited. The whole tumor volume was segmented on apparent diffusion coefficient (ADC) maps and T2W images. Afterward, the shape features of the volume of interest were extracted using PyRadiomics. Machine learning classification was performed using statistically different shape features in MATLAB® (The MathWorks, Inc., Natick, Massachusetts, United States). RESULTS: The findings revealed that 27 bladder cancer patients had muscle invasion, while 33 had superficial bladder cancer (53 men and seven women; mean age: 62±14). Surface area, volume, and relevant features were significantly greater in the invasive group than in the non-invasive group based on the ADC maps (P<0.05). Superficial bladder cancer had a more spherical form compared to invasive bladder cancer (P=0.05) with both imaging modalities. Flatness and elongation did not differ significantly between groups with either modality (P>0.05). Logistic regression had the highest accuracy of 83.3% (sensitivity 82.8%, specificity 84%) in assessing invasion based on the shape features of ADC maps, while K-nearest neighbors had the highest accuracy of 78.2% (sensitivity 79.1%, specificity 69.4%) in assessing invasion based on T2W images. CONCLUSIONS: Shape features can be helpful in predicting muscle invasion in bladder cancer using machine learning methods.

REliability of consensus-based segMentatIoN in raDiomic feature reproducibility (REMIND): A word of caution.

OBJECTIVE: To evaluate the reliability of consensus-based segmentation in terms of reproducibility of radiomic features. METHODS: In this retrospective study, three tumor data sets were investigated: breast cancer (n = 30), renal cell carcinoma (n = 30), and pituitary macroadenoma (n = 30). MRI was utilized for breast and pituitary data sets, while CT was used for renal data set. 12 readers participated in the segmentation process. Consensus segmentation was created by making corrections on a previous region or volume of interest. Four experiments were designed to evaluate the reproducibility of radiomic features. Reliability was assessed with intraclass correlation coefficient (ICC) with two cut-off values: 0.75 and 0.9. RESULTS: Considering the lower bound of the 95% confidence interval and the ICC threshold of 0.90, at least 61% of the radiomic features were not reproducible in the inter-consensus analysis. In the susceptibility experiment, at least half (54%) became non-reproducible when the first reader is replaced with a different reader. In the intra-consensus analysis, at least about one-third (32%) were non-reproducible when the same second reader segmented the image over the same first reader two weeks later. Compared to inter-reader analysis based on independent single readers, the inter-consensus analysis did not statistically significantly improve the rates of reproducible features in all data sets and analyses. CONCLUSIONS: Despite the positive connotation of the word "consensus", it is essential to REMIND that consensus-based segmentation has significant reproducibility issues. Therefore, the usage of consensus-based segmentation alone should be avoided unless a reliability analysis is performed, even if it is not practical in clinical settings.

Do Patients Really Have Pain with Quadriceps Fat Pad Edema?

OBJECTIVE: To determine the appropriate MRI criteria for the radiological diagnosis of significant quadriceps fat pad edema, to investigate the relationship between these criteria and anterior knee pain, and to evaluate possible structural and positional factors in the etiology. MATERIAL AND METHODS: In this retrospective case-control study, individuals with and without quadriceps fat pad edema in the knee MRIs taken between May 2016 and December 2018 were determined as the case and control groups, respectively, in a ratio of 1:1. The MRI criteria for significant quadriceps fat pad edema were set as 10 mm and above the anterior-posterior diameter of the quadriceps fat pad, posterior convexity, and an increased signal in the fat-suppressed proton density sequence. The groups were compared for anterior knee pain, pain characteristics, working positions (sitting and standing), and MRI findings of structural factors. P < 0.05 was considered statistically significant. RESULTS: A total of 108 individuals were evaluated. Anterior knee pain was more common in the case group (49/54, p < 0.001) and was highly correlated with signs of quadriceps fat pad edema (R = -0,657). Frequent pain at night (18/54, p = 0.013), increased pain when walking upstairs (40/54, p = 0.003), knees are flexed (43/54, p < 0.001), and decreased pain when knees are extended (42/54, p < 0.001) were significantly high in the case group. No significant differences were observed in working position and structural factors. CONCLUSION: Quadriceps fat pad edema is significantly associated with anterior knee pain and certain specific pain characteristics.