Search

Artificial intelligence (AI) is transforming the medical imaging of adult patients. However, its utilization in pediatric oncology imaging remains constrained, in part due to the inherent scarcity of data associated with childhood cancers. Pediatric cancers are rare, and imaging technologies are evolving rapidly, leading to insufficient data of a particular type to effectively train these algorithms. The small market size of pediatric patients compared with adult patients could also contribute to this challenge, as market size is a driver of commercialization. This review provides an overview of the current state of AI applications for pediatric cancer imaging, including applications for medical image acquisition, processing, reconstruction, segmentation, diagnosis, staging, and treatment response monitoring. Although current developments are promising, impediments due to the diverse anatomies of growing children and nonstandardized imaging protocols have led to limited clinical translation thus far. Opportunities include leveraging reconstruction algorithms to achieve accelerated low-dose imaging and automating the generation of metric-based staging and treatment monitoring scores. Transfer learning of adult-based AI models to pediatric cancers, multiinstitutional data sharing, and ethical data privacy practices for pediatric patients with rare cancers will be keys to unlocking the full potential of AI for clinical translation and improving outcomes for these young patients.

Objective: To compare tumor therapy response assessments with whole-body diffusion-weighted imaging (WB-DWI) and 18F-fluorodeoxyglucose ([ 18 F]FDG) PET/MRI in pediatric patients with Hodgkin lymphoma and non-Hodgkin lymphoma., Materials and Methods: In a retrospective, non-randomized single-center study, we reviewed serial simultaneous WB-DWI and [ 18 F]FDG PET/MRI scans of 45 children and young adults (27 males; mean age, 13 years ± 5 [standard deviation]; age range, 1-21 years) with Hodgkin lymphoma (n = 20) and non-Hodgkin lymphoma (n = 25) between February 2018 and October 2022. We measured minimum tumor apparent diffusion coefficient (ADCmin) and maximum standardized uptake value (SUVmax) of up to six target lesions and assessed therapy response according to Lugano criteria and modified criteria for WB-DWI. We evaluated the agreement between WB-DWI- and [ 18 F]FDG PET/MRI-based response classifications with Gwet's agreement coefficient (AC)., Results: After induction chemotherapy, 95% (19 of 20) of patients with Hodgkin lymphoma and 72% (18 of 25) of patients with non-Hodgkin lymphoma showed concordant response in tumor metabolism and proton diffusion. We found a high agreement between treatment response assessments on WB-DWI and [ 18 F]FDG PET/MRI (Gwet's AC = 0.94; 95% confidence interval [CI]: 0.82, 1.00) in patients with Hodgkin lymphoma, and a lower agreement for patients with non-Hodgkin lymphoma (Gwet's AC = 0.66; 95% CI: 0.43, 0.90). After completion of therapy, there was an excellent agreement between WB-DWI and [ 18 F]FDG PET/MRI response assessments (Gwet's AC = 0.97; 95% CI: 0.91, 1)., Conclusion: Therapy response of Hodgkin lymphoma can be evaluated with either [ 18 F]FDG PET or WB-DWI, whereas patients with non-Hodgkin lymphoma may benefit from a combined approach., Clinical Relevance Statement: Hodgkin lymphoma and non-Hodgkin lymphoma exhibit different patterns of tumor response to induction chemotherapy on diffusion-weighted MRI and PET/MRI., Key Points: • Diffusion-weighted imaging has been proposed as an alternative imaging to assess tumor response without ionizing radiation. • After induction therapy, whole-body diffusion-weighted imaging and PET/MRI revealed a higher agreement in patients with Hodgkin lymphoma than in those with non-Hodgkin lymphoma. • At the end of therapy, whole-body diffusion-weighted imaging and PET/MRI revealed an excellent agreement for overall tumor therapy responses for all lymphoma types., (© 2023. The Author(s), under exclusive licence to European Society of Radiology.)

Psychiatric disorders remain one of the most debilitating conditions; however, most patients are never diagnosed and do not seek treatment. Despite its massive burden on modern society and the health system, many hurdles prevent proper diagnosis and management of these disorders. The diagnosis is primarily based on clinical symptoms, and efforts to find appropriate biomarkers have not been practical. Through the past years, researchers have put a tremendous effort into finding biomarkers in "omics" fields: genomics, transcriptomics, proteomics, metabolomics, and epigenomics. This article reviews the evolving field of radiomics and its role in diagnosing psychiatric disorders as the sixth potential "omics." The first section of this paper elaborates on the definition of radiomics and its potential to provide a detailed structural study of the brain. Following that, we have provided the latest promising results of this novel approach in a broad range of psychiatric disorders. Radiomics fits well within the concept of psychoradiology. Besides volumetric analysis, radiomics takes advantage of many other features. This technique may open a new field in psychiatry for diagnosing and classifying psychiatric disorders and treatment response prediction in the era of precision and personalized medicine. The initial results are encouraging, but radiomics in psychiatry is still in its infancy. Despite the extensive burden of psychiatric disorders, there are very few published studies in this field, with small patient populations. The lack of prospective multi-centric studies and heterogeneity of studies in design are the significant barriers against the clinical adaptation of radiomics in psychoradiology.

Purpose: To assess and compare the diagnostic accuracy of whole-body (WB) DW-MRI with 2-[ 18 F]FDG PET for staging and treatment monitoring of children with Langerhans cell histiocytosis (LCH)., Methods: Twenty-three children with LCH underwent 2-[ 18 F]FDG PET and WB DW-MRI at baseline. Two nuclear medicine physicians and two radiologists independently assessed presence/absence of tumors in 8 anatomical areas. Sixteen children also performed 2-[ 18 F]FDG PET and WB DW-MRI at follow-up. One radiologist and one nuclear medicine physician revised follow-up scans and collected changes in tumor apparent diffusion (ADC) and standardized uptake values (SUV) before and after therapy in all detectable lesions. 2-[ 18 F]FDG PET results were considered the standard of reference for tumor detection and evaluation of treatment response according to Lugano criteria. Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy of WB DW-MRI at baseline were calculated, and the 95% confidence intervals were estimated by using the Clopper-Pearson (exact) method; changes in tumor SUVs and ADC were compared using a Mann-Whitney U test. Agreement between reviewers was assessed with a Cohen's weighted kappa coefficient. Analyses were conducted using SAS software version 9.4., Results: Agreement between reviewers was perfect (kappa coefficient = 1) for all analyzed regions but spine and neck (kappa coefficient = 0.89 and 0.83, respectively) for 2-[ 18 F]FDG PET images, and abdomen and pelvis (kappa coefficient = 0.65 and 0.88, respectively) for WB DW-MRI. Sensitivity and specificity were 95.5% and 100% for WB DW-MRI compared to 2-[ 18 F]FDG PET. Pre to post-treatment changes in SUV ratio and ADC mean were inversely correlated for all lesions (r: -0.27, p = 0·06) and significantly different between responders and non-responders to chemotherapy (p = 0.0006 and p = 0·003 for SUV ratio and ADC mean , respectively)., Conclusion: Our study showed that WB DW-MRI has similar accuracy to 2-[ 18 F]FDG PET for staging and treatment monitoring of LCH in children. While 2-[ 18 F]FDG PET remains an approved radiological examination for assessing metabolically active disease, WB DW-MRI could be considered as an alternative approach without radiation exposure. The combination of both modalities might have advantages over either approach alone., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: To provide a holistic and complete comparison of the five most advanced AI models in the augmentation of low-dose 18 F-FDG PET data over the entire dose reduction spectrum., Methods: In this multicenter study, five AI models were investigated for restoring low-count whole-body PET/MRI, covering convolutional benchmarks - U-Net, enhanced deep super-resolution network (EDSR), generative adversarial network (GAN) - and the most cutting-edge image reconstruction transformer models in computer vision to date - Swin transformer image restoration network (SwinIR) and EDSR-ViT (vision transformer). The models were evaluated against six groups of count levels representing the simulated 75%, 50%, 25%, 12.5%, 6.25%, and 1% (extremely ultra-low-count) of the clinical standard 3 MBq/kg 18 F-FDG dose. The comparisons were performed upon two independent cohorts - (1) a primary cohort from Stanford University and (2) a cross-continental external validation cohort from Tübingen University - in order to ensure the findings are generalizable. A total of 476 original count and simulated low-count whole-body PET/MRI scans were incorporated into this analysis., Results: For low-count PET restoration on the primary cohort, the mean structural similarity index (SSIM) scores for dose 6.25% were 0.898 (95% CI, 0.887-0.910) for EDSR, 0.893 (0.881-0.905) for EDSR-ViT, 0.873 (0.859-0.887) for GAN, 0.885 (0.873-0.898) for U-Net, and 0.910 (0.900-0.920) for SwinIR. In continuation, SwinIR and U-Net's performances were also discreetly evaluated at each simulated radiotracer dose levels. Using the primary Stanford cohort, the mean diagnostic image quality (DIQ; 5-point Likert scale) scores of SwinIR restoration were 5 (SD, 0) for dose 75%, 4.50 (0.535) for dose 50%, 3.75 (0.463) for dose 25%, 3.25 (0.463) for dose 12.5%, 4 (0.926) for dose 6.25%, and 2.5 (0.534) for dose 1%., Conclusion: Compared to low-count PET images, with near-to or nondiagnostic images at higher dose reduction levels (up to 6.25%), both SwinIR and U-Net significantly improve the diagnostic quality of PET images. A radiotracer dose reduction to 1% of the current clinical standard radiotracer dose is out of scope for current AI techniques., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Idiopathic intracranial hypertension (IIH) represents a clinical disease entity without a clear etiology, that if left untreated, can result in severe outcomes, including permanent vision loss. For this reason, early diagnosis and treatment is necessary. Historically, the role of cross-sectional imaging has been to rule out secondary or emergent causes of increased intracranial pressure, including tumor, infection, hydrocephalus, or venous thrombosis. MRI and MRV, however, can serve as valuable imaging tools to not only rule out causes for secondary intracranial hypertension but can also detect indirect signs of IIH resultant from increased intracranial pressure, and demonstrate potentially treatable sinus venous stenosis. Digital subtraction venographic imaging also plays a central role in both diagnosis and treatment, providing enhanced anatomic delineation and temporal flow evaluation, quantitative assessment of the pressure gradient across a venous stenosis, treatment guidance, and immediate opportunity for endovascular therapy. In this review, we discuss the multiple modalities for imaging IIH, their limitations, and their contributions to the management of IIH.

Diffusion-weighted imaging (DWI) is a well-established MRI sequence for diagnosing early stroke and provides therapeutic implications. However, DWI yields pertinent information in various other brain pathologies and helps establish a specific diagnosis and management of other central nervous system disorders. Some of these conditions can present with acute changes in neurological status and mimic stroke. This review will focus briefly on diffusion imaging techniques, followed by a more comprehensive description of the utility of DWI in common neurological entities beyond stroke., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Radiomics has achieved significant momentum in radiology research and can reveal image information invisible to radiologists' eyes. Radiomics first evolved for oncologic imaging. Oncologic applications (histopathology, tumor grading, gene mutation analysis, patient survival, and treatment response prediction) of radiomics are widespread. However, it is not limited to oncologic analysis, and any digital medical images can benefit from radiomics analysis. This article reviews the current literature on radiomics in non-oncologic, neurological disorders including ischemic strokes, hemorrhagic stroke, cerebral aneurysms, and demyelinating disorders., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2021, Sotoudeh et al.)

The development of cognitive dysfunction and dementia is a complex, multifactorial process. One of the contributors to various types of cognitive dysfunction is carotid atherosclerosis which can frequently be seen in asymptomatic individuals. There are a number of different manifestations of asymptomatic carotid atherosclerosis including arterial stiffness, carotid intima-media thickening, flow-limiting stenosis, and complex, atherosclerotic plaque. Each of these forms of atherosclerosis may contribute to cerebral parenchymal damage, contributing to cognitive dysfunction. In this review article, we will discuss each of these forms of carotid atherosclerosis, present the potential mechanistic underpinnings behind an association, and then review the scientific evidence supporting potential associations to cognitive dysfunction and dementia., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Baradaran, Sarrami and Gupta.)

Aim This study aimed to develop a predictive model to predict patients' mortality with coronavirus disease 2019 (COVID-19) from the basic medical data on the first day of admission. Methods The medical data including the demographic, clinical, and laboratory features on the first day of admission of clinically diagnosed COVID-19 patients were documented. The outcome of patients was also recorded as discharge or death. Feature selection models were then implemented and different machine learning models were developed on top of the selected features to predict discharge or death. The trained models were then tested on the test dataset. Results A total of 520 patients were included in the training dataset. The feature selection demonstrated 22 features as the most powerful predictive features. Among different machine learning models, the naive Bayes demonstrated the best performance with an area under the curve of 0.85. The ensemble model of the naive Bayes and neural network combination had slightly better performance with an area under the curve of 0.86. The models had relatively the same performance on the test dataset. Conclusion Developing a predictive machine learning model based on the basic medical features on the first day of admission in COVID-19 infection is feasible with acceptable performance., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2021, Tabatabaie et al.)

Importance: A carotid web (CW) is a shelf-like lesion along the posterior wall of the internal carotid artery bulb and an underrecognized cause of young stroke. Several studies suggest that patients with symptomatic CW have a high risk of recurrent stroke, but high-quality data are lacking., Objective: To assess the 2-year risk of recurrent stroke in patients with a symptomatic CW., Design, Setting, and Participants: A comparative cohort study used data from the MR CLEAN trial (from 2010-2014) and MR CLEAN Registry (from 2014-2017). Data were analyzed in September 2020. The MR CLEAN trial and MR CLEAN Registry were nationwide prospective multicenter studies on endovascular treatment (EVT) of large vessel occlusion (LVO) stroke in the Netherlands. Baseline data were from 3439 consecutive adult patients with anterior circulation LVO stroke and available computed tomography (CT)-angiography of the carotid bulb. Two neuroradiologists reevaluated CT-angiography images for presence or absence of CW and identified 30 patients with CW ipsilateral to the index stroke. For these 30 eligible CW participants, detailed follow-up data regarding stroke recurrence within 2 years were acquired. These 30 patients with CW ipsilateral to the index stroke were compared with 168 patients without CW who participated in the MR CLEAN extended follow-up trial and who were randomized to the EVT arm., Main Outcomes and Measures: The primary outcome was recurrent stroke occurring within 2 years after the index stroke. Cox proportional hazards regression models were used to compare recurrent stroke rates within 2 years for patients with and without CW, adjusted for age and sex. The research question was formulated prior to data collection., Results: Of 3439 patients with baseline CT-angiography assessed, the median age was 72 years (interquartile range, 61-80 years) and 1813 (53%) were men. Patients with CW were younger (median age, 57 [interquartile range, 46-66] years vs 66 [interquartile range, 56-77] years; P = .02 and more often women (22 of 30 [73%] vs 67 of 168 [40%]; P = .001) than patients without CW. Twenty-eight of 30 patients (93%) received medical management after the index stroke (23 with antiplatelet therapy and 5 with anticoagulant therapy). During 2 years of follow-up, 5 of 30 patients (17%) with CW had a recurrent stroke compared with 5 of 168 patients (3%) without CW (adjusted hazard ratio, 4.9; 95% CI, 1.4-18.1)., Conclusions and Relevance: In this study, 1 of 6 patients with a symptomatic CW had a recurrent stroke within 2 years, suggesting that medical management alone may not provide sufficient protection for patients with CW.

As human life expectancy increases, there is an increased prevalence of neurodegenerative disorders and dementia. There are many ongoing research trials for early diagnosis and management of dementia, and neuroimaging is a critical part of such studies. However, conventional neuroimaging often fails to provide enough diagnostic findings in patients with neurodegenerative disorders. In this context, different MRI sequences are currently under investigation to facilitate the accurate diagnosis of such disorders. Susceptibility-weighted imaging (SWI) is an innovative MRI technique that utilizes "magnitude" and "phase" images to produce an image contrast that is sensitive for the detection of susceptibility differences of the tissues. As many neurodegenerative disorders are associated with accelerated iron deposition and/or microhemorrhages in different parts of the brain, SWI can be applied to detect these diagnostic clues. For instance, in cerebral amyloid angiopathy, SWI can demonstrate cortical microhemorrhages, which are predominantly in the frontal and parietal regions. Or in Parkinson disease, abnormal swallow-tail sign on high-resolution SWI is highly diagnostic. Also, SWI is a useful sequence to detect the low signal intensity of precentral cortices in patients with amyotrophic lateral sclerosis. Being familiar with SWI findings in neurodegenerative disorders is critical for an accurate diagnosis. In this paper, the authors review the technical parameters of SWI, physiologic, and pathologic iron deposition in the brain, and the role of SWI in the evaluation of neurodegenerative disorders in daily practice., (© 2021 American Society of Neuroimaging.)

Introduction: Radiomics now has significant momentum in the era of precision medicine. Glioma is one of the pathologies that has been extensively evaluated by radiomics. However, this technique has not been incorporated into clinical practice. In this systematic review, we selected and reviewed the published studies about glioma grading by radiomics to evaluate this technique's feasibility and its challenges., Material and Methods: Using seven different search strings, we considered all published English manuscripts from 2015 to September 2020 in PubMed, Embase, and Scopus databases. After implementing the exclusion and inclusion criteria, the final papers were selected for the methodological quality assessment based on our in-house Modified Radiomics Standard Scoring (RQS) containing 43 items (minimum score of 0, maximum score of 44). Finally, we offered our opinion about the challenges and weaknesses of the selected papers., Results: By our search, 1,177 manuscripts were found (485 in PubMed, 343 in Embase, and 349 in Scopus). After the implementation of inclusion and exclusion criteria, 18 papers remained for the final analysis by RQS. The total RQS score ranged from 26 (59% of maximum possible score) to 43 (97% of maximum possible score) with a mean of 33.5 (76% of maximum possible score)., Conclusion: The current studies are promising but very heterogeneous in design with high variation in the radiomics software, the number of extracted features, the number of selected features, and machine learning models. All of the studies were retrospective in design; many are based on small datasets and/or suffer from class imbalance and lack of external validation data-sets., (© 2021 S. Karger AG, Basel.)

Background: We assess the potency of different Doppler indices in the differentiation of obstructive and nonobstructive hydronephrosis., Materials and Methods: In this study, infants and children who were referred for the evaluation of unilateral hydronephrosis were enrolled. Ultrasonography for the assessment of the degree of hydronephrosis and a voiding cystourethrogram for the exclusion of vesicoureteral reflux was performed. Then, Doppler ultrasonography was done for both kidneys of each patient using four classic Doppler indices as well as the difference (delta) of each index between to kidneys. Diuretic renography with 99 mTc-ethylene dicysteine (99 mTc-EC) was performed for each patient., Results: Thirty-nine patients met the inclusion criteria. After diuretic renography, 29 (74.35%) patients had shown a nonobstructive pattern, and ten (25.65%) patients had a partial (intermediate) or complete obstruction. Using receiver operating characteristic (ROC) curve, none of the classic indices of Doppler duplex (i.e., resistive index [RI], resistance index, end diastolic velocity, and peak systolic velocity) had the ability to make a difference between obstructive and nonobstructive hydronephrosis. However, by calculating the difference (delta) of these indices between two kidneys of each patient, delta RI could differentiate the nonobstructive condition, significantly ( P = 0.006). A cutoff value of 0.055 has 60% sensitivity and 82.8% specificity. The area under the ROC curve for delta RI is 0.795 (standard error: 0.086, 95% confidence interval [CI]: 0.626, 0.964). Furthermore, RI ratio between two kidneys of each patient could differentiate the nonobstructive condition, significantly ( P = 0.012). A cutoff point of 1.075 has 70% sensitivity and 82.8% specificity. The area under the ROC curve for RI ratio was 0.769 (standard error: 0.104, 95% CI: 0.565, 0.973)., Conclusion: This study shows that RI ratio and delta RI with a high specificity could differentiate nonobstructive hydronephrosis and therefore it is a promising way to use especially in the follow-up of children with hydronephrosis., Competing Interests: There are no conflicts of interest.

Background: In primary studies with 3 T Magnets, phase sensitive reconstruction of T1-weighted inversion recovery (PSIR) have showed ability to depict the cervical multiple sclerosis (MS) lesions some of which may not be detected by short tau inversion recovery (STIR). Regarding to more availability of 1.5 T MRI, this study was designed to evaluate the eligibility of PSIR in 1.5 T for detection of spinal cord MS lesions., Method: In a study between September 2016 till March 2017 the patients with proven diagnosis of MS enrolled to the study. The standard protocol (sagittal STIR and T2W FSE and axial T2W FSE) as well as sagittal PSIR sequences were performed using a 1.5 T magnet. The images were studied and the lesions were localized and recorded as sharp or faint on each sequence., Results: Of 25 patients (22 females and 3 males, with mean age of 33.5 ± 9.8 years and mean disease duration of 5.4 ± 3.9 years) 69 lesions in STIR, 53 lesions in T2W FSE, 47 lesions in Magnitude reconstruction of PSIR (Magnitude), and 30 lesions in phase sensitive (real) reconstruction PSIR were detected. A Wilcoxon signed-rank test showed STIR has a statistically significant higher detection rate of the plaques rather than other three sequences. (STIR and T2W FSE, Z = -4.000, p < 0.0001, STIR and Magnitude, Z = -4.690, p < 0.0001, STIR and PSIR, Z = -6.245, p = 0.002) Also, STIR had a statistically significant superiority in the boundary definition of the plaques rather than other three sequences., Conclusion: This study shows that in the setting of a 1.5 T magnet field, STIR significantly has a superiority over both of the PSIR reconstructions (i.e. real and magnitude) for the detection as well as the boundary definition of the cervical cord lesions of MS. These results have a good relevance to clinical practice by using MRI scanners and sequences routinely available, however, it is discrepant with other reports performed by 3 T Magnet fields., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: To evaluate the correlation of magnetic resonance imaging (MRI) features of breast lesions of Breast Imaging Reporting and Database System (BI-RADS) category 4 with histopathologic results., Materials and Methods: In a prospective study between December 2013 and April 2015, patients with suspicious mammographic and/or ultrasound findings referred for Breast MRI were evaluated. Patients with lesions of BI-RADS category 4 were enrolled with a written informed consent. In each patient, mass lesion (ML) or nonmass lesion (NML) was determined, and different characteristics of the lesions were recorded. A follow-up program was taken with mean 3-12 months. Patients who underwent core needle biopsy or open biopsy were summoned., Results: Seventy-eight females aged 24-67 years (mean 43.1 ± 8.8) met the inclusion criteria and had adequate samples for histopathologic study. Twenty-nine (37.2%) patients had ML and 49 (62.8%) patients had NML. Tissue sampling in 63 (80.7%) patients was through core needle biopsy and in 15 (19.2%) patients through surgery. A wide spectrum of benign and malignant pathologic diagnoses was seen. In statistical analysis, none of the MRI features has a significant correlation with any specific histopathologic diagnosis ( P = 0.185). However, the relation between the MRI category (ML or NML) and pathology results was significant at level of 0.1 ( P = 0.06)., Conclusion: This study showed that a wide spectrum of histopathologic results is seen in BI-RADS category 4. However, in this sample volume, none of the MRI features in this BI-RADS category has a significant correlation with any specific histopathologic diagnosis.

Background: Computed tomography-guided percutaneous core needle biopsy (PCNB) is a diagnostic technique for initial assessment of mediastinal mass lesions. This study was conducted to evaluate its diagnostic yield and its complication rate., Materials and Methods: We reviewed the records of CT-guided PCNB in 110 patients with mediastinal mass lesions performed in Kashani and Alzahra Hospitals, Isfahan, from 2006 to 2012. Gender, age at biopsy, size, and anatomic location of the lesion, number of passes, site of approach, complications, and final diagnosis were extracted., Results: Our series encompasses 52 (47.2%) females and 58 (52/7%) males with mean age of 41 ± 8 years. The most common site of involvement was the anterior mediastinum (91.8% of cases). An average of 3/5 passes per patient has been taken for tissue sampling. Parasternal site was the most frequent approach taken for PCNB (in 78.1% of cases). Diagnostic tissue was obtained in 99 (90%) biopsies while, in 11 (10%) cases, specimen materials were inadequate. Lymphoma (49.5%) and bronchogenic carcinoma (33.3%) were the most frequent lesions in our series. The overall complication rate was 17.2% from which 10.9% was pneumothorax, 5.4% was hemoptysis, and 0.9% was vasovagal reflex., Conclusion: CT-guided PCNB is a safe and reliable procedure that can provide a precise diagnosis for patients with both benign and malignant mediastinal masses, and it is considered the preferred first diagnostic procedure use for this purpose.

Background: Ulnar nerve entrapment (UNE) has been diagnosed with clinical examination and electrodiagnostic studies. This study was designed to determine the value of a combination of grey-scale and color Doppler ultrasound findings in the diagnosis of patients with UNE., Materials and Methods: During May to August 2013 41 patients with UNE (proven by electrodiagnostic studies) and 44 healthy volunteers were evaluated by ultrasound study. Three cross-sectional area (CSA) of ulnar nerve around cubital fossa was determined and measured in both groups. The maximum and minimum diameter of ulnar nerve was measured for calculating flattening ratio index (FRI). Vascularity of ulnar nerve around cubital fossa was also examined in proper color Doppler setting., Results: The mean CSA of nerve at all proximal, middle and distal levels were greater in patients with UNE than in controls (P = 0.02, <0.001 and 0.34 respectively). A cut-off point of 10.5 mm(2) for CSA (in the level of the cubital fossa) yielded a sensitivity and specificity of 92.7% and 93.2%, respectively. Mean FRI was 3.1 ± 0.6 in patients with UNE group and 1.4 ± 0.2 in the control group with a significant difference (P < 0.001). FRI with cutoff point 2.15 has been shown as an important parameter for the detection of UNE. The vascularity in UNE has a sensitivity and specificity of 66% and 93.2%, respectively, and has a higher probability of being positive in severe UNE., Conclusion: Combination of grey-scale and color Doppler ultrasound may provide valuable diagnostic criteria and severity assessment of UNE.