A Comparative Analysis of Erector Spinae Plane Block Versus Conscious Sedation in Managing Percutaneous Cholecystostomy Pain.

PURPOSE: This study investigates the efficacy of erector spinae plane block (ESPB) for managing perioperative and postoperative pain in patients undergoing percutaneous cholecystostomy (PC) for acute cholecystitis, particularly in high-risk elderly patients with extensive comorbidities and limited functional status. METHODS: In a retrospective single-center study, 58 high-risk patients scheduled for PC were assessed. ESPB was administered to 23 patients, while 22 received conscious sedation. Pain intensity was measured using the numeric rating scale before any analgesic or ESPB administration, during the procedure and at 1 and 12 h post-procedure and secondary outcomes included adverse effects and additional analgesic requirements. RESULTS: The ESPB group experienced significant pain reduction during and post-procedure compared to the conscious sedation group (p = 0.002). Procedure times were shorter (p = 0.015), and postoperative tramadol was less frequently needed in the ESPB group (p = 0.007). The incidence of nausea was also lower in the ESPB group (p = 0.001). No ESPB-related complications were reported. CONCLUSION: ESPB significantly alleviates perioperative and postoperative pain in PC patients, reducing additional analgesic use and side effects. It holds promise as a key component of pain management for high-risk surgical patients. LEVEL OF EVIDENCE: Level 3, Non-randomized controlled cohort/follow-up study.

Changes in retinal vascular density measured by optical coherence tomography angiography in patients with carotid artery stenosis after carotid artery stenting and angioplasty.

PURPOSE: The aim of this study was to compare the effect of carotid artery stenting and angioplasty (CASA) on retinal vascular density (VD) in patients with severe carotid stenosis with a healthy control group and to evaluate using optical coherence tomography angiography (OCTA). METHODS: For this prospective study, eyes on the operated side constituted the ipsilateral eye group, and the other eye constituted the contralateral eye group. 40 eyes of 40 patients with ipsilateral eye of carotisid artery stenosis (CAS), 34 eyes on contralateral side, and 30 healthy eyes (control group) were included in this study. We performed quantitative OCTA analyses of retinal VD changes, before and after CASA. The main outcome measures were the quantitative changes of VD of superficial capillary plexus (SCP) and deep capillary plexus (DCP). RESULTS: We evaluated the VD of ipsilateral eyes and contralateral eyes separately before and after the procedure. All patients did not have visual symptoms. There was no significant difference in the VD of SCP in all groups before the procedure. No significant change was observed in all groups when the VD of the SCP was compared before and after the procedure. The VD of the DCP in the ipsilateral and contralateral group improved significantly after CASA. CONCLUSION: OCTA could noninvasively detect retinal VD improvements after CASA in CAS patients. Quantitative changes in VD evaluated using OCTA are thought to be early indicators in the diagnosis of CAS and in the follow-up of treatment success.

Successful treatment of a rheumatoid arthritis patient with severe synovial hypertrophy and impaired shoulder function with microwave ablation technique.

Rheumatoid arthritis (RA) is a chronic, inflammatory systemic disorder of synovial joints and results in polyarthritis, chronical degeneration, and finally deformities and ankylosis in severe cases. Synovitis and pannus formation are results of inflammatory changes and lead into restriction in joint movement. Shoulders are among the later affected and larger joints and formation of synovitis in early active stages and pannus in later stages might be concluded with frozen shoulder and severe impairment in functionality. These late-term changes cannot be controlled with systemic or local anti-inflammatory agents and synovectomy is chosen in some cases. However, the results are not satisfactory and recurrence is common. In this case report, we presented a case of RA with severe shoulder pain, restricted movement due to synovial hypertrophy, and pannus formation which are resistant to local and systemic interventions and not suitable for surgical or chemical synovectomy. Microwave ablation (MWA) was performed successfully without any complication and she well responded in terms of DAS-28, functional, and pain scores. Range of motion and funcitonal restriction were recovered. This case report describes the use and promising results of MWA in RA with severe synovial hypertrophy and pannus formation even in the absence of active arthritis and effusion. MWA is a safe and minimally invasive technique that can be easily performed in coordinance of rheumatologists and interventional radiologists in proper cases.

Effectiveness of polidocanol sclerotherapy in alleviating symptoms in patients with venous malformations.

OBJECTIVE: The objective of this study was to retrospectively evaluate the effectiveness of polidocanol in managing pain, swelling, functional limiting and cosmetic disorders in patients with venous malformations (VMs). METHODS: This retrospective study included patients who underwent sclerotherapy with polidocanol for VMs between 2020 and 2022. Patient records, imaging findings, and evaluation questionnaires used in the preprocedure and follow-up phases were reviewed. After sclerotherapy, patients were followed up at 1, 2, 3, and 6 months. During these visits, the previously used 11-point verbal numerical rating scale (from 0 [no pain] to 10 [worst pain thinkable]) was used to evaluate the severity of symptoms such as pain, swelling, cosmetic discomfort, and functional limitation, and patients were asked to report the number of days per week they experienced these symptoms owing to the VM. RESULTS: A total of 194 sclerotherapy procedures (mean, 1.6 ± 0.3 procedures) in 84 patients (55 female and 29 male patients; mean age, 22.45 ± 11.83 years) were conducted. The majority of these malformations (81%, or 68 patients) were located in the extremities. We found a significant decrease in pain, swelling, functional limitation, cosmetic appearance, and number of painful days between all time points, except for the comparison between months 3 and 6 (P < .001) CONCLUSIONS: Polidocanol sclerotherapy is a safe and effective treatment for VMs that significantly decreases patient complaints and has a very low complication rate. Particularly, following patients at short intervals and administering additional sclerotherapy sessions when necessary will significantly increase patient satisfaction.

Artificial Intelligence in Renal Mass Characterization: A Systematic Review of Methodologic Items Related to Modeling, Performance Evaluation, Clinical Utility, and Transparency.

OBJECTIVE. The objective of our study was to systematically review the literature about the application of artificial intelligence (AI) to renal mass characterization with a focus on the methodologic quality items. MATERIALS AND METHODS. A systematic literature search was conducted using PubMed to identify original research studies about the application of AI to renal mass characterization. Besides baseline study characteristics, a total of 15 methodologic quality items were extracted and evaluated on the basis of the following four main categories: modeling, performance evaluation, clinical utility, and transparency items. The qualitative synthesis was presented using descriptive statistics with an accompanying narrative. RESULTS. Thirty studies were included in this systematic review. Overall, the methodologic quality items were mostly favorable for modeling (63%) and performance evaluation (63%). Even so, the studies (57%) more frequently constructed their work on nonrobust features. Furthermore, only a few studies (10%) had a generalizability assessment with independent or external validation. The studies were mostly unsuccessful in terms of clinical utility evaluation (89%) and transparency (97%) items. For clinical utility, the interesting findings were lack of comparisons with both radiologists' evaluation (87%) and traditional models (70%) in most of the studies. For transparency, most studies (97%) did not share their data with the public. CONCLUSION. To bring AI-based renal mass characterization from research to practice, future studies need to improve modeling and performance evaluation strategies and pay attention to clinical utility and transparency issues.

Prediction of Benign and Malignant Solid Renal Masses: Machine Learning-Based CT Texture Analysis.

RATIONALE AND OBJECTIVES: This study aimed to investigate whether benign and malignant renal solid masses could be distinguished through machine learning (ML)-based computed tomography (CT) texture analysis. MATERIALS AND METHODS: Seventy-nine patients with 84 solid renal masses (21 benign; 63 malignant) from a single center were included in this retrospective study. Malignant masses included common renal cell carcinoma (RCC) subtypes: clear cell RCC, papillary cell RCC, and chromophobe RCC. Benign masses are represented by oncocytomas and fat-poor angiomyolipomas. Following preprocessing steps, a total of 271 texture features were extracted from unenhanced and contrast-enhanced CT images. Dimension reduction was done with a reliability analysis and then with a feature selection algorithm. A nested-approach was used for feature selection, model optimization, and validation. Eight ML algorithms were used for the classifications: decision tree, locally weighted learning, k-nearest neighbors, naive Bayes, logistic regression, support vector machine, neural network, and random forest. RESULTS: The number of features with good reproducibility was 198 for unenhanced CT and 244 for contrast-enhanced CT. Random forest algorithm demonstrated the best predictive performance using five selected contrast-enhanced CT texture features. The accuracy and area under the curve metrics were 90.5% and 0.915, respectively. Having eliminated the highly collinear features from the analysis, the accuracy and area under the curve values slightly increased to 91.7% and 0.916, respectively. CONCLUSION: ML-based contrast-enhanced CT texture analysis might be a potential method for distinguishing benign and malignant solid renal masses with satisfactory performance.

Radiomics of Renal Masses: Systematic Review of Reproducibility and Validation Strategies.

OBJECTIVE. The purpose of this study was to systematically review the radiomics literature on renal mass characterization in terms of reproducibility and validation strategies. MATERIALS AND METHODS. With use of PubMed and Google Scholar, a systematic literature search was performed to identify original research papers assessing the value of radiomics in characterization of renal masses. The data items were extracted on the basis of three main categories: baseline study characteristics, radiomic feature reproducibility strategies, and statistical model validation strategies. RESULTS. After screening and application of the eligibility criteria, a total of 41 papers were included in the study. Almost one-half of the papers (19 [46%]) presented at least one reproducibility analysis. Segmentation variability (18 [44%]) was the main theme of the analyses, outnumbering image acquisition or processing (3 [7%]). No single paper considered slice selection bias. The most commonly used statistical tool for analysis was intraclass correlation coefficient (14 of 19 [74%]), with no consensus on the threshold or cutoff values. Approximately one-half of the papers (22 [54%]) used at least one validation method, with a predominance of internal validation techniques (20 [49%]). The most frequently used internal validation technique was k-fold cross-validation (12 [29%]). Independent or external validation was used in only three papers (7%). CONCLUSION. Workflow characteristics described in the radiomics literature about renal mass characterization are heterogeneous. To bring radiomics from a mere research area to clinical use, the field needs many more papers that consider the reproducibility of radiomic features and include independent or external validation in their workflow.

Schwannomas of Uncommon Peripheral Locations: Analysis of Imaging Findings of 21 Cases.

BACKGROUND: Schwannomas are benign slow-growing tumors most often associated with the cranial nerves. Schwannomas often originate from the eighth cranial nerve. They may also originate from the peripheral nervous system of the neck and extremities. However extracranial peripheral schwannomas are considered a rare entity. OBJECTIVES: The knowledge of rare localizations and typical imaging findings will lead to a successfulradiological diagnosis. Therefore, in this study, we present the clinical findings and MRI characteristics of schwannomas with a rare localization involving the peripheral, lower and upper extremity and intramuscular regions. MATERIALS AND METHODS: The hospital database was screened for patients with an extracranial soft tissue mass. Twenty-one cases of schwannomas were found in rare localization. We analyzed the MR images of these patients retrospectively. The MR images were evaluated in terms of tumor location, signal intensity, and enhancement pattern. The histological examination of all the patients confirmed the diagnosis of schwannoma. RESULTS: In 21 patients, the schwannomas were peripheral, localized to upper (n = 6) and lower extremities (n = 11). The remaining four patients had intramuscular schwannomas. The patients diagnosed with intramuscular schwannomas had schwannomas in sternocleidomastoid, gastrocnemius, triceps muscle and lateral wall of the abdomen. The average long-axis diameter of the tumor was 27.7 mm and the average short-axis diameter was 16.4 mm. The contrast pattern was diffused in eight tumors and peripheral in 13. CONCLUSION: In this study, we present clinical findings and MRI characteristics of schwannomas with a rare localization involving the peripheral, lower and upper extremity and intramuscular regions.

Clear Cell Renal Cell Carcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis for Prediction of Fuhrman Nuclear Grade.

OBJECTIVE: To evaluate the performance of quantitative computed tomography (CT) texture analysis using different machine learning (ML) classifiers for discriminating low and high nuclear grade clear cell renal cell carcinomas (cc-RCCs). MATERIALS AND METHODS: This retrospective study included 53 patients with pathologically proven 54 cc-RCCs (31 low-grade [grade 1 or 2]; 23 high-grade [grade 3 or 4]). In one patient, two synchronous cc-RCCs were included in the analysis. Mean age was 57.5 years. Thirty-four (64.1%) patients were male and 19 were female (35.9%). Mean tumour size based on the maximum diameter was 57.4 mm (range, 16-145 mm). Forty patients underwent radical nephrectomy and 13 underwent partial nephrectomy. Following pre-processing steps, two-dimensional CT texture features were extracted using portal-phase contrast-enhanced CT. Reproducibility of texture features was assessed with the intra-class correlation coefficient (ICC). Nested cross-validation with a wrapper-based algorithm was used in feature selection and model optimisation. The ML classifiers were support vector machine (SVM), multilayer perceptron (MLP, a sort of neural network), naïve Bayes, k-nearest neighbours, and random forest. The performance of the classifiers was compared by certain metrics. RESULTS: Among 279 texture features, 241 features with an ICC equal to or higher than 0.80 (excellent reproducibility) were included in the further feature selection process. The best model was created using SVM. The selected subset of features for SVM included five co-occurrence matrix (ICC range, 0.885-0.998), three run-length matrix (ICC range, 0.889-0.992), one gradient (ICC = 0.998), and four Haar wavelet features (ICC range, 0.941-0.997). The overall accuracy, sensitivity (for detecting high-grade cc-RCCs), specificity (for detecting high-grade cc-RCCs), and overall area under the curve of the best model were 85.1%, 91.3%, 80.6%, and 0.860, respectively. CONCLUSIONS: The ML-based CT texture analysis can be a useful and promising non-invasive method for prediction of low and high Fuhrman nuclear grade cc-RCCs. KEY POINTS: • Based on the percutaneous biopsy literature, ML-based CT texture analysis has a comparable predictive performance with percutaneous biopsy. • Highest predictive performance was obtained with use of the SVM. • SVM correctly classified 85.1% of cc-RCCs in terms of nuclear grade, with an AUC of 0.860.

Textural differences between renal cell carcinoma subtypes: Machine learning-based quantitative computed tomography texture analysis with independent external validation.

OBJECTIVE: To develop externally validated, reproducible, and generalizable models for distinguishing three major subtypes of renal cell carcinomas (RCCs) using machine learning-based quantitative computed tomography (CT) texture analysis (qCT-TA). MATERIALS AND METHODS: Sixty-eight RCCs were included in this retrospective study for model development and internal validation. Another 26 RCCs were included from public databases (The Cancer Genome Atlas-TCGA) for independent external validation. Following image preparation steps (reconstruction, resampling, normalization, and discretization), 275 texture features were extracted from unenhanced and corticomedullary phase CT images. Feature selection was firstly done with reproducibility analysis by three radiologists, and; then, with a wrapper-based classifier-specific algorithm. A nested cross-validation was performed for feature selection and model optimization. Base classifiers were the artificial neural network (ANN) and support vector machine (SVM). Base classifiers were also combined with three additional algorithms to improve generalizability performance. Classifications were done with the following groups: (i), non-clear cell RCC (non-cc-RCC) versus clear cell RCC (cc-RCC) and (ii), cc-RCC versus papillary cell RCC (pc-RCC) versus chromophobe cell RCC (chc-RCC). Main performance metric for comparisons was the Matthews correlation coefficient (MCC). RESULTS: Number of the reproducible features is smaller for the unenhanced images (93 out of 275) compared to the corticomedullary phase images (232 out of 275). Overall performance metrics of the machine learning-based qCT-TA derived from corticomedullary phase images were better than those of unenhanced images. Using corticomedullary phase images, ANN with adaptive boosting algorithm performed best for discrimination of non-cc-RCCs from cc-RCCs (MCC = 0.728) with an external validation accuracy, sensitivity, and specificity of 84.6%, 69.2%, and 100%, respectively. On the other hand, the performance of the machine learning-based qCT-TA is rather poor for distinguishing three major subtypes. The SVM with bagging algorithm performed best for discrimination of pc-RCC from other RCC subtypes (MCC = 0.804) with an external validation accuracy, sensitivity, and specificity of 69.2%, 71.4%, and 100%, respectively. CONCLUSIONS: Machine learning-based qCT-TA can distinguish non-cc-RCCs from cc-RCCs with a satisfying performance. On the other hand, the performance of the method for distinguishing three major subtypes is rather poor. Corticomedullary phase CT images provide much more valuable texture parameters than unenhanced images.

Relationship between vertebral artery blood flow in different head positions and vertigo.

OBJECTIVE: To identify the vertebral artery blood flow in different head positions in patients with positional vertigo with no specific diagnosis. METHODS: Patients with history of vestibular symptoms associated with changes in head position were enrolled into the study. Healthy volunteers were evaluated as control group. Doppler ultrasonography examination of the cervical segment of the vertebral arteries was performed under three different head positions: (i) supine position, (ii) head hyperextended and rotated to the right side and (iii) head hyperextended and rotated to the left side. RESULTS: In the study group, right and left vertebral artery blood flow was significantly lower in the ipsilateral hyperextended position compared to standard supine position (respectively p = .014; p = .001), but did not differ significantly when compared between the standard supine and contralateral hyperextended positions (respectively = .959; p = .669). In the control group, left and right vertebral artery blood flow did not differ significantly when the head was hyperextended to the right or left sides compared to standard supine position (p > .05). CONCLUSIONS: Our data demonstrated that the etiology of vestibular complaints in patients with undiagnosed positional vertigo might be related to impairment in vertebral artery blood flow according to head positions.