Inter-reader agreement of the prostate imaging quality (PI-QUAL) score for basic readers in prostate MRI: A multi-center study.

BACKGROUND: The Prostate Imaging Quality (PI-QUAL) score is the first step toward image quality assessment in multi-parametric prostate MRI (mpMRI). Previous studies have demonstrated moderate to excellent inter-rater agreement among expert readers; however, there is a need for studies to assess the inter-reader agreement of PI-QUAL scoring in basic prostate readers. OBJECTIVES: To assess the inter-reader agreement of the PI-QUAL score amongst basic prostate readers on multi-center prostate mpMRI. METHODS: Five basic prostate readers from different centers assessed the PI-QUAL scores independently using T2-weighted images, diffusion-weighted imaging (DWI) including apparent diffusion coefficient (ADC) maps, and dynamic-contrast-enhanced (DCE) images on mpMRI data obtained from five different centers following Prostate Imaging-Reporting and Data System Version 2.1. The inter-reader agreements amongst radiologists for PI-QUAL were evaluated using weighted Cohen's kappa. Further, the absolute agreements in assessing the diagnostic adequacy of each mpMRI sequence were calculated. RESULTS: A total of 355 men with a median age of 71 years (IQR, 60-78) were enrolled in the study. The pair-wise kappa scores ranged from 0.656 to 0.786 for the PI-QUAL scores, indicating good inter-reader agreements between the readers. The pair-wise absolute agreements ranged from 0.75 to 0.88 for T2W imaging, from 0.74 to 0.83 for the ADC maps, and from 0.77 to 0.86 for DCE images. CONCLUSIONS: Basic prostate radiologists from different institutions provided good inter-reader agreements on multi-center data for the PI-QUAL scores.

Deep learning for assessing image quality in bi-parametric prostate MRI: A feasibility study.

BACKGROUND: Although systems such as Prostate Imaging Quality (PI-QUAL) have been proposed for quality assessment, visual evaluations by human readers remain somewhat inconsistent, particularly among less-experienced readers. OBJECTIVES: To assess the feasibility of deep learning (DL) for the automated assessment of image quality in bi-parametric MRI scans and compare its performance to that of less-experienced readers. METHODS: We used bi-parametric prostate MRI scans from the PI-CAI dataset in this study. A 3-point Likert scale, consisting of poor, moderate, and excellent, was utilized for assessing image quality. Three expert readers established the ground-truth labels for the development (500) and testing sets (100). We trained a 3D DL model on the development set using probabilistic prostate masks and an ordinal loss function. Four less-experienced readers scored the testing set for performance comparison. RESULTS: The kappa scores between the DL model and the expert consensus for T2W images and ADC maps were 0.42 and 0.61, representing moderate and good levels of agreement. The kappa scores between the less-experienced readers and the expert consensus for T2W images and ADC maps ranged from 0.39 to 0.56 (fair to moderate) and from 0.39 to 0.62 (fair to good). CONCLUSIONS: Deep learning (DL) can offer performance comparable to that of less-experienced readers when assessing image quality in bi-parametric prostate MRI, making it a viable option for an automated quality assessment tool. We suggest that DL models trained on more representative datasets, annotated by a larger group of experts, could yield reliable image quality assessment and potentially substitute or assist visual evaluations by human readers.

Does deep learning software improve the consistency and performance of radiologists with various levels of experience in assessing bi-parametric prostate MRI?

OBJECTIVE: To investigate whether commercially available deep learning (DL) software improves the Prostate Imaging-Reporting and Data System (PI-RADS) scoring consistency on bi-parametric MRI among radiologists with various levels of experience; to assess whether the DL software improves the performance of the radiologists in identifying clinically significant prostate cancer (csPCa). METHODS: We retrospectively enrolled consecutive men who underwent bi-parametric prostate MRI at a 3 T scanner due to suspicion of PCa. Four radiologists with 2, 3, 5, and > 20 years of experience evaluated the bi-parametric prostate MRI scans with and without the DL software. Whole-mount pathology or MRI/ultrasound fusion-guided biopsy was the reference. The area under the receiver operating curve (AUROC) was calculated for each radiologist with and without the DL software and compared using De Long's test. In addition, the inter-rater agreement was investigated using kappa statistics. RESULTS: In all, 153 men with a mean age of 63.59 ± 7.56 years (range 53-80) were enrolled in the study. In the study sample, 45 men (29.80%) had clinically significant PCa. During the reading with the DL software, the radiologists changed their initial scores in 1/153 (0.65%), 2/153 (1.3%), 0/153 (0%), and 3/153 (1.9%) of the patients, yielding no significant increase in the AUROC (p > 0.05). Fleiss' kappa scores among the radiologists were 0.39 and 0.40 with and without the DL software (p = 0.56). CONCLUSIONS: The commercially available DL software does not increase the consistency of the bi-parametric PI-RADS scoring or csPCa detection performance of radiologists with varying levels of experience.

Investigating the correlation between severe acute pancreatitis and pancreatic necrosis with some serum parameters.

BACKGROUND: Acute pancreatitis (AP) is a disease related to significant morbidity and even mortality. Various factors are involved in the etiology, especially gallstones and excessive alcohol consumption. Although, the course of the disease in most of the cases is generally mild, in some cases, the disease can be severe and lead to pancreatic or peripancreatic necrosis. Radiologically, 'Balthazar computed tomography severity index' (CTSI) is used to assess the severity and presence of necrosis in pancreatitis. In this study, we classified the severity of AP in patients with Balthazar CTSI and investigated whether there is a correlation between some serum parameters and AP severity and which serum parameters can be used as a safe marker to predict the AP severity and the development of pancreatic necrosis (PN). METHODS: A total of 341 patients diagnosed with AP and hospitalized in our general surgery clinic between the years 2012 and 2018 were included in this study. Hematological and biochemical parameters of the patients were recorded. Abdominal CT's of the patients were evaluated according to the Balthazar CTSI. The correlation between these parameters and AP severity evaluated by Balthazar CTSI was investigated. RESULTS: PN was detected in 19.4% of 341 patients who participated in the study. Patients whose PN detected in their abdominal CT's by Balthazar CTSI; neutrophil counts, neutrophil/lymphocyte ratio (NLR), thrombocyte/lymphocyte ratio, plateletlymphocyte ratio, and neutrophil/monocyte ratio (NMR) were significantly higher and the serum albumin was significantly lower than patients with PN. CONCLUSION: Neutrophil count, serum albumin levels, NLR, LR, and NMR can be used as predictive markers to determine AP severity.

Is there any additional benefit of 68Ga-PSMA PET on radiotherapy target volume definition in patients with glioblastoma?

OBJECTIVE: To investigate the contribution of 68Gallium (68Ga)-PSMA (prostate-specific membrane antigen) positron emission tomography (PET) in defining radiotherapy (RT) target volume for glioblastoma and to compare the target volumes defined by Magnetic Resonance Imaging (MRI). METHODS: RT planning Computed Tomography (CT) images were fused separately with pre-operative MRI and PET/MRI images of 10 glioblastoma patients, retrospectively. The contrast-enhanced area in T1 weighted MRI was contoured as gross tumor volume (GTV) and clinical target volume (CTV1) was obtained by including the cavity and T2/FLAIR hyperintense areas after giving a margin of 2 cm to the GTV. 68Ga-PSMA uptake area was contoured as biological tumor volume (BTV) and CTV2 was obtained with a margin of 2 cm to BTV. Planning target volumes (PTVs) were created with the 3 mm added to the CTVs. Conformity index (CI), dice similarity coefficient (DSC) and overlap volume (OV) were calculated by obtaining the intersection and union volumes. Volumetric comparison, similarity and overlap analyzes were performed statistically by Wilcoxon signed rank and One sample t-test. RESULTS: The median GTV was 21,96 cc (1,04 - 82,04) and BTV was 25,58 cc (2,43 - 99,47). BTV was on average 47% larger than GTV which was statistically significant (p = 0.03). For GTV-BTV, CTV1-CTV2 and PTV1-PTV2; mean values of CI were 0,56, 0,76 and 0,76; DSC were 0,70, 0,86 and 0,86; OV were 0,88, 0,94 and 0,94, respectively. There was no significant difference on size and spatial similarity between CTV1 and CTV2, PTV1 and PTV2. CONCLUSION: Altough BTV was larger than GTV, this significance was lost while we gave the same CTV margin including the peripheral edema. It seems that it may help to improve defining non-enhancing tumor part and also recurrent tumor volume. ADVANCES IN KNOWLEDGE: Recent studies have focused on the role of 68Ga-PSMA PET in imaging of glial tumors. It has been observed that 68Ga-PSMA PET can clearly define the tumor borders and it can be beneficial in target volume delineation, especially in reirradiation of recurrent tumors.

Comparison and ensemble of 2D and 3D approaches for COVID-19 detection in CT images.

Detecting COVID-19 in computed tomography (CT) or radiography images has been proposed as a supplement to the RT-PCR test. We compare slice-based (2D) and volume-based (3D) approaches to this problem and propose a deep learning ensemble, called IST-CovNet, combining the best 2D and 3D systems with novel preprocessing and attention modules and the use of a bidirectional Long Short-Term Memory model for combining slice-level decisions. The proposed ensemble obtains 90.80% accuracy and 0.95 AUC score overall on the newly collected IST-C dataset in detecting COVID-19 among normal controls and other types of lung pathologies; and 93.69% accuracy and 0.99 AUC score on the publicly available MosMedData dataset that consists of COVID-19 scans and normal controls only. The system also obtains state-of-art results (90.16% accuracy and 0.94 AUC) on the COVID-CT-MD dataset which is only used for testing. The system is deployed at Istanbul University Cerrahpasa School of Medicine where it is used to automatically screen CT scans of patients, while waiting for RT-PCR tests or radiologist evaluation.

Fibroblast Growth Factor Receptor-4 Expression in Pituitary Adenomas is Associated with Aggressive Tumor Features.

PURPOSE: To investigate the relationship of Fibroblast Growth Factor Receptor-4 (FGFR-4) expression with radiologic, pathologic, and clinical parameters in pituitary adenomas. METHODS: Among 307 patients who underwent pituitary surgery for a pituitary adenoma between 2000 and 2015, we included 161 patients (53 gonadotroph, 26 corticotroph, 25 null cell, 22 lactotroph, 13 somatotroph, 8 adenomas with unusual combination, 7 Pit-1 positive adenomas, and 7 lactosomatotroph) based on availability of pathology specimens. Patients' radiologic, pathologic, and clinical parameters were determined. FGFR-4 immunostaining was evaluated using a semi-quantitative histologic score (H-score). RESULTS: The mean follow-up period was 61 (IQR=32-84) months. The median H-scores for FGFR-4 were higher in patients without remission, those with residual lesion, and T2-hyperintense adenoma (p<0.05). Ki-67 level was higher in patients without remission compared to those in remission (p<0.05). The mean Ki-67 levels did not differ between patients with and without residual lesion or T2-hyperintense tumor (p>0.05). There was no significant difference (p>0.05) when the H-score and Ki-67 levels were assessed in terms of sex, sellar-dural invasion, Knosp and a grading system for superior, inferior, parasellar, anterior and posterior tumor extension Classification, tumor function or presence of poor subtype. Adenomas with Ki-67 expression ≥3% had higher FGFR4 expression levels than those with <3% expression (p=0.002). There was a weak positive correlation between H-score and Ki-67 (p=0.011; r=0.201). CONCLUSIONS: Higher levels of FGFR-4 in pituitary adenomas could be use a marker for more aggressive tumor behavior.

Focusing on Asthma and Chronic Obstructive Pulmonary Disease with COVID-19.

INTRODUCTION: We aimed to evaluate clinical and laboratory findings of hospitalized asthma and chronic obstructive pulmonary disease (COPD) patients with COVID-19 and demonstrate that they have different symptoms and/or laboratory results and outcomes than COVID-19 patients with comorbidity (CoV-com) and without comorbidity (CoV-alone). METHODOLOGY: The data of the demographic, clinical, laboratory findings of hospitalized CoV-alone, asthma, COPD patients with COVID-19 (CoV-asthma, CoV-COPD, respectively), and CoV-com were analyzed. RESULTS: Out of 1082 patients hospitalized for COVID-19, 585 (54.1%) had CoV-alone, 40 (3.7%) had CoV-asthma, 46 (4.3%) had CoV-COPD and 411 (38%) had CoV-com. Cough, shortness of breath, fever and weakness were the most common four symptoms seen in all COVID-19 patients. Shortness of breath, myalgia, headache symptoms were more common in CoV-asthma than the other groups (p < 0.001, p < 0.01, p < 0.05 respectively). Sputum was more common in CoV-COPD than other groups (p < 0.01). COPD group most frequently had increased values, different from the other groups with CRP>5ng/mL in 91.3%, D-dimer > 0.05mg/dL in 89.1%, troponin > 0.014micg/L in %63.9, INR>1.15 in 52.2%, CK-MB>25U/L in 48.5%, PT>14s in 40.9% of patients (p < 0.05, p < 0.001, p < 0.001, p < 0.001, p < 0.05, p < 0.001, respectively). NT-ProBNP was found to have the highest AUC value and the best differentiating parameter for CoV-asthma from CoV-alone. Typical CT findings were present in 44.4% of CoV-alone, 57.5% of CoV-asthma, 28.3% of CoV-COPD and 38.9% of CoV-com groups. CoV-COPD and CoV-com patients died more frequently than other groups (17.8%, 18.5%). CONCLUSIONS: CoV-asthma and CoV-COPD patients might have different symptoms and laboratory parameters than other COVID-19 patients which can guide the physicians.

The Diagnostic Value of Superb Microvascular Imaging in Prediction of Uterine Artery Embolization Treatment Response in Uterine Leiomyomas.

OBJECTIVES: We aimed to determine if superb microvascular imaging (SMI) can predict response to uterine artery embolization (UAE) as compared with power Doppler ultrasound. METHODS: The blood flow and the volume of the dominant leiomyoma was evaluated by power Doppler ultrasonography (PDUS) and SMI 1 day before and 3 months after the UAE procedure. SMI and PDUS blood flow were classified to 4 grades of vascularity. The change in fibroid volume in Grades 0-2 (hypovascular group) was compared to the hypervascular Grade 3 group. RESULTS: Twenty-eight women (mean age, 40.9 years; range, 33-53 years) were examined with PDUS and SMI before and 3 months after UAE. The volume reduction was statistically significantly higher hypervascular group (P < .05). When we accept 30% or more volume reduction as a good response to UAE, the positive predictive value, negative predictive value, sensitivity, specificity, and accuracy of SMI were 100, 64, 73.6, 100, and 82.1%, respectively. There was excellent agreement between the two blinded observers in SMI measurements. CONCLUSIONS: SMI, with its high reproducibility, provides further microvessel information than PDUS in uterine fibroids. It may be a useful tool in prediction of response to UAE treatment and improve counseling and patient selection for UAE versus medical or surgical treatment options.

Extra-Cochlear Insertion in Cochlear Implantation: A Potentially Disastrous Condition.

OBJECTIVES: Cochlear implantation is an increasingly used technique for auditory rehabilitation of pediatric and adult population. Safe implantation is achieved in most cases; however, intraoperative complications and misplacement of the electrode are observed in some. The aim of this presentation was to review the characteristics of patients with extra-cochlear electrode insertion, postoperative diagnostic methods, and considerations in revision surgery. MATERIALS AND METHODS: In total, 423 cases of cochlear implantation performed in our clinic between 2012 and 2018 were retrospectively analyzed and those of extra-cochlear implantation were evaluated. RESULTS: Extra-cochlear insertion was found in 3 patients. The electrode was placed into the internal acoustic canal in the first case, superior semicircular canal in the second case, and internal carotid artery canal in the third case. Cochlear insertion was achieved in all cases with re-implantation, and no complication was observed. CONCLUSION: This case series highlights that rare, but potentially serious, consequences of misplacement of the electrode in cochlear implantation can be successfully avoided and treated via a multidisciplinary approach.

Penile masses: Shear Wave Elastography correlated with Magnetic Resonance Imagining. A two cases report.

Definitive diagnosis of penile masses usually depends on clinical symptoms and patient history but in some challenging cases the help of radiologic diagnostic tools is required. Although ultrasound is an effective tool for detecting penile masses, unlike magnetic resonance imagining, it is not able to differentiate benign and malignant pathologies. Shear wave elastography (SWE) is a novel method, which has the ability to differentiate malignant and benign tissues by giving quantitative information about tissue elasticity. In this paper we present two cases with penile masses to demonstrate the potential use of SWE in the differential diagnosis of penile masses.