Quantitative evaluation of CT scan images to determinate the prognosis of COVID-19 patient using deep learning.

The purpose of this research is to evaluate the accuracy of AI-assisted quantification in comparison to conventional CT parameters reviewed by a radiologist in predicting the severity, progression, and clinical outcome of disease. The current study is a cross-sectional study that was conducted on patients with the diagnosis of COVID-19 and underwent a pulmonary CT scan between August 23th, 2021 to December 21th, 2022. The initial CT scan on admission was used for imaging analysis. The presence of ground glass opacity (GGO), and consolidation were visually evaluated. CT severity score was calculated according to a semi-quantitative method. In addition, AI based quantification of GGO and consolidation volume were also performed. 291 patients (mean age: 64.7 ± 7; 129 males) were included. GGO + consolidation was more frequently revealed in progress-to-severe group whereas pure GGO was more likely to be found in non-severe group. Compared to non-severe group, patients in progress-to-severe group had larger GGO volume percentage (40.6%± 11.9%versus 21.7%± 8.8%, p ˂0.001) as well as consolidation volume percentage (4.8% ± 2% versus 1.9% ± 1%, p < 0.001). Among imaging parameters, consolidation volume percentage and the largest area under curve (AUC) in discriminating non-severe from progress-to-severe group (AUC = 0.91, p < 0.001). According to multivariate regression, consolidation volume was the strongest predictor for disease progression. In conclusion, the consolidation volume measured on the initial chest CT was the most accurate predictor of disease progression, and a larger consolidation volume was associated with a poor clinical outcome. In patients with COVID-19, AI-assisted lesion quantification was useful for risk stratification and prognosis evaluation.

Effect of ultrasound parameters of benign thyroid nodules on radiofrequency ablation efficacy.

BACKGROUND AND AIM: Ultrasound-guided radiofrequency ablation (RFA) is a minimally invasive therapy for thyroid nodules (TNs). Understanding the determinants of RFA efficacy can improve treatment and prognosis. This study aims to investigate the relationship between ultrasound parameters of benign TNs and the efficacy of RFA. METHODS: A pretest-posttest interventional study was conducted in 2021 on 250 randomly sampled patients with benign TNs, receiving RFA. For this purpose, the volume reduction (VR) and the VR ratio (VRR) of the nodules were measured at the 1-, 3-, 6-, and 12-month follow-up periods after the RFA completion. The technical success rate (TSR) of this procedure was then categorized into four states, including low (VRR < 25%), moderate (VRR = 25-49%), high (VRR = 50-74%), and very high (VRR ≥ 75). Ordered logistic regression (OLR) was further utilized to investigate the effect of the ultrasound parameters of TNs on the TSR. The analyses were notably performed using Stata 14.2. RESULTS: The VRR at the 1-, 3-, 6-, and 12-month follow-up periods were 38.7%, 53.6%, 59.3%, and 59.9%, respectively. The mean VR was also statistically significant at all follow-ups (p < 0.001). At the 1-, 3-, and 6-month follow-up periods, the VR of over 50% was observed in 28.2%, 52.1%, and 65.2% of the nodules, respectively. The odds ratios (ORs) of the RFA success were found to be 4.3 times higher for the nodules in the left lobe compared to the right lobe (OR: 4.31, p = 0.002), 6.3 times greater for isoechoic nodules compared to hyperechoic nodules (OR: 6.39, p < 0.001), 6.2 times higher for hyper-vascular nodules compared to hypo-vascular nodules (OR: 6.25, p = 0.005), and 2.3 times greater for mixed nodules compared to solid ones (OR: 2.37, p = 0.049). CONCLUSION: The ultrasound parameters of TNs had a statistically significant effect on the efficacy of RFA. Small-sized, isoechoic, and hyper-vascular nodules, as well as those with mixed tissue, were observed to respond better to RFA, leading to a better prognosis in terms of VR after treatment.

Antenatal ultrasonographic diagnosis of rhizomelic chondrodysplasia punctata.

BACKGROUND: Rhizomelic chondrodysplasia punctata (RCDP) is a rare autosomal recessive inherited subtype of a family of congenital anomalies known as chondrodysplasia calcificans punctate (CCP). Given their low rate of occurrence, these cases are highly challenging to diagnose, and because the presence of chondrodysplasia is an indication for legal abortion in Iran, such diagnosis is extremely critical. CASE PRESENTATION: A 27-year-old white multipara was referred for obstetric ultrasonography at 17 weeks and 6 days of gestation because an ultrasonographic study performed at an outside institution revealed a short femur length. Given the patient's positive family history of chondrodysplasia, she underwent targeted sonography to check the anomaly of the bone and cartilage. The key finding in the sonography was short bones for gestational age. CONCLUSION: The important clue in this finding was the patient's family history, which made the gynaecologist request an ultrasound to prevent the birth of a child with a congenital disorder. Genetic tests are usually performed on amniocentesis samples. Because the presence of chondrodysplasia is an indication for legal abortion in Iran, finally, the patient underwent legal abortion after amniocentesis and genetic tests.

Changes in diffusion tensor imaging indices in basal ganglia and thalamus of patients with Relapsing-Remitting Multiple Sclerosis and relation with clinical conditions: A case-control study.

Background: Multiple sclerosis (MS) is recognized as the most prevalent autoimmune abnormality of the CNS. T1WI, T2WI, and FLAIR are limited in the quantification of tissue damage and detection of tissue alterations in white and grey matter in MS. This study aimed to the evaluation of changes in DTI indices in these patients at the thalamus and basal ganglia. Methods: 30 relapsing-remitting MS (RRMS) cases and 30 normal individuals were included. Conventional MRI (T2, FLAIR) was acquired to confirm NAGM in MS patients. A T1 MPRAGE protocol was used to normalize DTI images. FSL, SPM, and Explore DTI software were employed to reach Mean Diffusivities (MD), Axial Diffusivities (AD), Fractional anisotropy (FA), and Radial Diffusivity (RD) at the thalamus and the basal ganglia. Results: The FA and RD of the thalamus were decreased in healthy controls compared to MS cases (0.319 vs. 0.296 and 0.0009 vs. 0.0006, respectively) (P < 0.05). The AD value in the thalamus and the FA value in the caudate nucleus were significantly lower in MS cases than in controls (0.0009 vs. 0.0011 and 0.16 vs. 0.18, respectively) (P < 0.05). MD values in the thalamus or basal ganglia were not significantly different between groups. Conclusions: DTI measures including FA, RD, and AD have a good diagnostic performance in detecting microstructural changes in the normal-appearing thalamus in cases with RRMS while they had no significant relationship with clinical signs in terms of EDSS. Availability of data and material: Not applicable.

A literature review on the imaging methods for breast cancer.

Breast cancer will be easier and more effective to treat if detected early. Breast cancer is assessed and detected using imaging as a primary approach. The capacity to diagnose breast cancers is continually improving thanks to developments in imaging technologies. However, some of these enhancements have been linked to delays in the initiation of treatment procedures of breast cancer. Overall, cancer management relies heavily on imaging procedures such as screening and symptomatic disease management. Mammography, which is considered the gold standard, and breast ultrasonography are employed as routine imaging modalities. Previous research has shown that, despite recent developments, no single imaging modality can detect and characterizing majority of breast lesions. Various imaging methods and their uses in diagnosing and caring the breast cancer are discussed in this study.

Investigating the role of susceptibility weighted imaging for assessment of ischemic penumbra with respect to Venus blood flow in ischemic stroke patients.

INTRODUCTION: Susceptibility weighted imaging can be used to study intracranial venous blood arteries based on the paramagnetic sensitivity of blood discharged by oxygen (SWI). Significant hypotensive drainage channels have been discovered in the ischemic tissue of the brain, which have been recognized by SWI. The compliance or non-compliance between the variation in venous drainage of ischemic brain tissue by SWI and diffusion limitation. MATERIAL AND METHODS: This cross-sectional study was conducted in 2019 on 20 patients (15 men and 5 females) who were assigned to the Ghaem Hospital MRI Institute in Rasht, Iran. RESULTS: Infarction has been detected in a total of 20 vascular regions. The caliber of the sulcal and intramedullary veins, on the other hand, was increased in 80 percent and 65 percent of the infarcted regions, respectively. In 45 percent of the vascular regions, a match between SWI and diffusion-weighted magnetic resonance imaging (DWI) was detected, mismatch was detected in two; follow-up revealed infarct progression. CONCLUSIONS: Significant data on critically perfused cerebral cortex with possibility of infarction growth was focused on in elevated SWI investigations, contributing to SWI as a worthy MR implies that could be attached as complementary protocols to neuroimaging techniques for acute ischemia, according to the findings of this study.

Automatic fetal biometry prediction using a novel deep convolutional network architecture.

PURPOSE: Fetal biometric measurements face a number of challenges, including the presence of speckle, limited soft-tissue contrast and difficulties in the presence of low amniotic fluid. This work proposes a convolutional neural network for automatic segmentation and measurement of fetal biometric parameters, including biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) from ultrasound images that relies on the attention gates incorporated into the multi-feature pyramid Unet (MFP-Unet) network. METHODS: The proposed approach, referred to as Attention MFP-Unet, learns to extract/detect salient regions automatically to be treated as the object of interest via the attention gates. After determining the type of anatomical structure in the image using a convolutional neural network, Niblack's thresholding technique was applied as pre-processing algorithm for head and abdomen identification, whereas a novel algorithm was used for femur extraction. A publicly-available dataset (HC18 grand-challenge) and clinical data of 1334 subjects were utilized for training and evaluation of the Attention MFP-Unet algorithm. RESULTS: Dice similarity coefficient (DSC), hausdorff distance (HD), percentage of good contours, the conformity coefficient, and average perpendicular distance (APD) were employed for quantitative evaluation of fetal anatomy segmentation. In addition, correlation analysis, good contours, and conformity were employed to evaluate the accuracy of the biometry predictions. Attention MFP-Unet achieved 0.98, 1.14 mm, 100%, 0.95, and 0.2 mm for DSC, HD, good contours, conformity, and APD, respectively. CONCLUSIONS: Quantitative evaluation demonstrated the superior performance of the Attention MFP-Unet compared to state-of-the-art approaches commonly employed for automatic measurement of fetal biometric parameters.

Sonography: a sensitive and specific method for detecting trochlear cartilage pathologies.

PURPOSE: MRI is now the modality of choice for evaluating articular cartilage. Nevertheless, it has some general drawbacks. Some patients cannot undergo MRI, and in others US scan could be the first examination and cartilage should be evaluated. Ultrasound could be a useful method for detecting trochlear cartilage low-grade lesions. In this study, our goal was to evaluate the efficacy of ultrasonography in detecting these lesions. METHODS: All patients referred to our hospital, from July 2018 to July 2019, who were arthroscopic candidates due to sport-related pathologies, underwent ultrasound scan 1 day prior to surgery. Ultrasound assessment was performed by an expert radiologist, with a 13-MHz probe, located transversely proximal to the patella in different degrees of knee flexion to assess trochlear lesion grade and thickness. Arthroscopic examination of all patients was performed by an experienced orthopedic knee surgeon (second author). Sensitivity and specificity of ultrasound were calculated. RESULTS: A total of 48 patients were involved in the study with a mean age of 33.2 years (SD: 9.7), between 19 and 51 years of age. Patients were 81% male (39 patients). The sensitivity of ultrasound in grading of trochlear cartilage lesion was 100%, meanwhile its specificity was 88.2% (30 cases had normal cartilage while this figure was 34 in arthroscopy). CONCLUSION: Sonography is a low-cost, accessible diagnostic tool with high sensitivity and specificity for early detection of trochlear cartilage pathologies. It can play an important role as an outpatient diagnostic workup in patients with anterior knee pain.