Diagnostic Accuracy of Integrating Ultrasound and Shear Wave Elastography in Assessing Carpal Tunnel Syndrome Severity: a Prospective Observational Study.

Purpose: Carpal tunnel syndrome (CTS) is a common condition characterized by compression of the median nerve (MN) within the carpal tunnel. Accurate diagnosis and assessment of CTS severity are crucial for appropriate management decisions. This study aimed to investigate the combined diagnostic utility of B-mode ultrasound (US) and shear wave elastography (SWE) for assessing the severity of CTS in comparison to electrodiagnostic tests (EDT). Materials and Methods: This prospective observational study was conducted over 9-month periods at a tertiary care hospital. A total of 48 patients (36 females, 12 males; mean age 44 ± 10.9 years; age range 28-57 years) with clinically suspected CTS were enrolled. All patients underwent EDT, US, and SWE. Based on the EDT results, CTS cases were categorized into four groups: mild, moderate, severe, and negative. The cross-sectional area (CSA) and elasticity (E) of the MN were measured at the tunnel inlet (CSAu and Eu) and pronator quadratus region (CSAo and Eo). The differences (CSAu-CSAo and Eu-Eo) were calculated. The primary outcomes were the diagnostic performance of CSAu, CSAu-CSAo, Eu, and Eu-Eo in differentiating moderate/severe from mild/negative CTS compared to EDT findings. Secondary outcomes included a correlation of US/SWE parameters with EDT grades and between each other. ANOVA, correlation, regression, and receiver operating characteristic (ROC) curve analyses were performed. Results: CSAu and CSAu-CSAo increased progressively with worsening CTS severity. E measurements were significantly higher in moderate-to-severe CTS compared to mild or negative cases. The combined metric of CSAu-CSAo at a 5 mm threshold exhibited enhanced performance, with a higher sensitivity (83.3%), specificity (100%), and area under the curve (AUC) (0.98), surpassing the results of CSAu when used independently. Similarly, the SWE measurements indicated that Eu-Eo at a 56.1kPa cutoff achieved an AUC of 0.95, with a sensitivity of 93.3% and specificity of 94.4%, outperforming the metrics for Eu when used alone, which had an AUC of 0.93, with identical sensitivity and specificity values (93.3% and 94.4%, respectively). Conclusion: The integration of ultrasound, shear wave elastography, and electrodiagnostic tests provides a comprehensive approach to evaluate anatomical and neurological changes and guide management decisions for CTS.

Predicting the Consistency of Pituitary Macroadenomas: The Utility of Diffusion-Weighted Imaging and Apparent Diffusion Coefficient Measurements for Surgical Planning.

Understanding the consistency of pituitary macroadenomas is crucial for neurosurgeons planning surgery. This retrospective study aimed to evaluate the utility of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) as non-invasive imaging modalities for predicting the consistency of pituitary macroadenomas. This could contribute to appropriate surgical planning and therefore reduce the likelihood of incomplete resections. The study included 45 patients with pathologically confirmed pituitary macroadenomas. Conventional MRI sequences, DWIs, ADC maps, and pre- and post-contrast MRIs were performed. Two neuroradiologists assessed all of the images. Neurosurgeons assessed the consistency of the tumor macroscopically, and histopathologists examined it microscopically. The MRI findings were compared with postoperative data. According to the operative data, macroadenomas were divided into the two following categories based on their consistency: aspirable (n = 27) and non-aspirable tumors (n = 18). A statistically significant difference in DWI findings was found when comparing macroadenomas of different consistencies (p < 0.001). Most aspirable macroadenomas (66.7%) were hyperintense according to DWI and hypointense on ADC maps, whereas most non-aspirable macroadenomas (83.3%) were hypointense for DWI and hyperintense on ADC maps. At a cut-off value of 0.63 × 10-3 mm2/s, the ADC showed a sensitivity of 85.7% and a specificity of 75% for the detection of non-aspirable macroadenomas (AUC, 0.946). The study concluded that DWI should be routinely performed in conjunction with ADC measurements in the preoperative evaluation of pituitary macroadenomas. This approach may aid in surgical planning, ensure that appropriate techniques are utilized, and reduce the risk of incomplete resection.

Advanced strain elastography is a reliable approach for prostate cancer detection in patients with elevated PSA levels.

This study aimed to examine the validity and reproducibility of strain elastography (SE) for detecting prostate cancer (PCa) in patients with elevated prostate-specific antigen (PSA) levels. The study included 107 patients with elevated PSA levels. All eligible patients underwent transrectal ultrasound (TRUS) with real-time elastography (RTE) to detect suspicious lesions. Two readers independently evaluated the lesions and assigned a strain ratio and elastography score to each lesion. Histopathology was used as a reference standard to estimate the validity of RTE in predicting malignant lesions. An intraclass correlation (ICC) was performed to detect reliability of the strain ratios and elastography scores. TRUS-guided biopsy detected malignancies in 64 (59.8%) patients. TRUS with RTE revealed 122 lesions. The strain ratio index (SRI) cut-off values to diagnose malignancy were 4.05 and 4.35, with sensitivity, specificity, and accuracy of 94.7%, 91.3%, and 93.4%, respectively. An elastography score > 3 was the best cut-off value for detecting malignancy. According to readers, the sensitivity, specificity, and accuracy were 91.3-94.7%, 89.5-93.4%, and 91.3-90.9%, respectively. Excellent inter-reader agreement was recorded for SRI and elastography scores, with ICC of 0.937 and 0.800, respectively. SE proves to be an efficient tool for detecting PCa with high accuracy in patients with elevated PSA levels.

Complication Rates and Risk of Recurrence After Percutaneous Radiofrequency Ablation and Microwave Ablation for the Treatment of Liver Tumors: a Meta-analysis.

RATIONALE AND OBJECTIVES: The rate of complications and risk of local recurrence following percutaneous radiofrequency ablation (RFA) and microwave ablation (MWA) for liver tumors varies significantly between investigations. This meta-analysis aimed to assess complication rates and risk of local recurrence after percutaneous RFA and MWA. MATERIALS AND METHODS: PubMed, Medline, Web of Science, the Cochrane Library, Embase, Google Scholar, and CINAHL were systematically searched from database inception until August 2022 to retrieve articles reporting the complication rates and risk of recurrence after percutaneous RFA and MWA for the treatment of liver tumors. Pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated and displayed by forest plots. To measure heterogeneity, Cochran Q and I2 statistics were also applied. Egger's test and funnel plots were also performed to assess any potential publication bias. Additionally, subgroup analysis was done to investigate the source of heterogeneity. RESULTS: 26 studies including 2026 and 1974 patients for RFA and MWA, respectively, were included. The rate of minor complications was significantly higher after MWA compared to RFA, yielding an overall OR of 0.688 (95% CI: 0.549-0.862, P = 0.001). Similarly, the rate of major complications was significantly higher after MWA than RFA (P = 0.012), yielding an overall OR of 0.639 (95% CI: 0.450-0.907). No significant difference was found between RFA and MWA in terms of local recurrence after ablation (P > 0.05). In addition, there was no statistical evidence of publication bias. CONCLUSION: When most factors are considered equally, percutaneous RFA and MWA can be considered safe modalities for the treatment of liver tumors, with RFA superior in terms of the incidence of minor and major complications.

The Impact of Adding Digital Breast Tomosynthesis to BI-RADS Categorization of Mammographically Equivocal Breast Lesions.

Digital mammography (DM) is the cornerstone of breast cancer detection. Digital breast tomosynthesis (DBT) is an advanced imaging technique used for diagnosing and screening breast lesions, particularly in dense breasts. This study aimed to evaluate the impact of combining DBT with DM on the BI-RADS categorization of equivocal breast lesions. We prospectively evaluated 148 females with equivocal BI-RADS breast lesions (BI-RADS 0, 3, and 4) with DM. All patients underwent DBT. Two experienced radiologists analyzed the lesions. They then assigned a BI-RADS category for each lesion according to the BI-RADS 2013 lexicon, using DM, DBT, and integrated DM and DBT. We compared the results based on major radiological characteristics, BI-RADS classification, and diagnostic accuracy, using the histopathological examination of the lesions as a reference standard. The total number of lesions was 178 on DBT and 159 on DM. Nineteen lesions were discovered using DBT and were missed by DM. The final diagnoses of 178 lesions were malignant (41.6%) and benign (58.4%). Compared to DM, DBT produced 34.8% downgrading and 32% upgrading of breast lesions. Compared with DM, DBT decreased the number of BI-RADS 4 and 3. All the upgraded BI-RADS 4 lesions were confirmed to be malignant. The combination of DM and DBT improves the diagnostic accuracy of BI-RADS for evaluating and characterizing mammographic equivocal breast lesions and allows for proper BI-RADS categorization.

Magnetic Resonance Imaging Features of Rhino-Orbito-Cerebral Mucormycosis in Post-COVID-19 Patients: Radio-Pathological Correlation.

There has been a notable increase in rhino-orbito-cerebral mucormycosis (ROCM) post-coronavirus disease 2019 (COVID-19), which is an invasive fungal infection with a fatal outcome. Magnetic resonance imaging (MRI) is a valuable tool for early diagnosis of ROCM and assists in the proper management of these cases. This study aimed to describe the characteristic MRI findings of ROCM in post-COVID-19 patients to help in the early diagnosis and management of these patients. This retrospective descriptive study was conducted at a single hospital and included 52 patients with COVID-19 and a histopathologically proven ROCM infection who were referred for an MRI of the paranasal sinuses (PNS) due to sino-orbital manifestations. Two radiologists reviewed all the MR images in consensus. The diagnosis was confirmed by histopathological examination. The maxillary sinus was the most commonly affected PNS (96.2%). In most patients (57.7%), multiple sinuses were involved with the black turbinate sign on postcontrast images. Extrasinus was evident in 43 patients with orbital involvement. The pterygopalatine fossa was involved in four patients. Three patients had cavernous sinus extension, two had pachymeningeal enhancement, and one had epidural collection. The alveolar margin was affected in two patients, and five patients had an extension to the cheek. The awareness of radiologists by the characteristic MRI features of ROCM in post-COVID-19 patients helps in early detection, early proper management, and prevention of morbid complications.

Precision Mapping of Intrahepatic Biliary Anatomy and Its Anatomical Variants Having a Normal Liver Using 2D and 3D MRCP.

Despite significant advances in hepatobiliary surgery, biliary injury and leakage remain typical postoperative complications. Thus, a precise depiction of the intrahepatic biliary anatomy and anatomical variant is crucial in preoperative evaluation. This study aimed to evaluate the precision of 2D and 3D magnetic resonance cholangiopancreatography (MRCP) in exact mapping of intrahepatic biliary anatomy and its variants anatomically in subjects with normal liver using intraoperative cholangiography (IOC) as a reference standard. Thirty-five subjects with normal liver activity were imaged via IOC and 3D MRCP. The findings were compared and statistically analyzed. Type I was observed in 23 subjects using IOC and 22 using MRCP. Type II was evident in 4 subjects via IOC and 6 via MRCP. Type III was observed equally by both modalities (4 subjects). Both modalities observed type IV in 3 subjects. The unclassified type was observed in a single subject via IOC and was missed in 3D MRCP. Accurate detection by MRCP of intrahepatic biliary anatomy and its anatomical variants was made in 33 subjects out of 35, with an accuracy of 94.3% and a sensitivity of 100%. In the remaining two subjects, MRCP results provided a false-positive pattern of trifurcation. MRCP competently maps the standard biliary anatomy.

Isolated Convolutional-Neural-Network-Based Deep-Feature Extraction for Brain Tumor Classification Using Shallow Classifier.

In today's world, a brain tumor is one of the most serious diseases. If it is detected at an advanced stage, it might lead to a very limited survival rate. Therefore, brain tumor classification is crucial for appropriate therapeutic planning to improve patient life quality. This research investigates a deep-feature-trained brain tumor detection and differentiation model using classical/linear machine learning classifiers (MLCs). In this study, transfer learning is used to obtain deep brain magnetic resonance imaging (MRI) scan features from a constructed convolutional neural network (CNN). First, multiple layers (19, 22, and 25) of isolated CNNs are constructed and trained to evaluate the performance. The developed CNN models are then utilized for training the multiple MLCs by extracting deep features via transfer learning. The available brain MRI datasets are employed to validate the proposed approach. The deep features of pre-trained models are also extracted to evaluate and compare their performance with the proposed approach. The proposed CNN deep-feature-trained support vector machine model yielded higher accuracy than other commonly used pre-trained deep-feature MLC training models. The presented approach detects and distinguishes brain tumors with 98% accuracy. It also has a good classification rate (97.2%) for an unknown dataset not used to train the model. Following extensive testing and analysis, the suggested technique might be helpful in assisting doctors in diagnosing brain tumors.