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Kidney stones, known medically as nephrolithiasis, present a significant health concern globally, particularly in regions such as India and the Middle East. Despite extensive research, the complexity of ureteral obstruction due to kidney stones remains a challenge in urology. This study addresses this gap by analysing the effects of obstruction in a three-dimensional model of the ureter with a constant diameter, simulating various percentages of blockage. Through computational analysis, the pressure and velocity effects on the ureter wall are explored, providing insights into the dynamics of obstructed ureters. Building upon previous research, this study contributes to a deeper understanding of the factors influencing flow patterns and pressure variations within the urinary tract. Additionally, findings from this study may lead to advancements in non-invasive assessment methods for diagnosing and treating ureteral obstruction caused by kidney stones. Furthermore, insights gained from this research could potentially inform clinical decision-making, leading to improved management strategies and better outcomes for patients affected by this debilitating condition. The novelty of this work lies in its comprehensive analysis of the effects of obstruction on the ureteral wall, offering valuable implications for urological practice and patient care.

Background Aging is a non-modifiable risk factor for neurodegenerative disease. It is well established that the brain undergoes physiological atrophy with age. So, this study was conducted to analyse the correlation between the age of the person and the size of the various subcortical nuclei of the brain and whether these measurements can serve as a useful indicator for physiological atrophy leading to degenerative disease in clinical practice. Methods A total of 600 MRI scans from healthy individuals were examined and the measurements of subcortical nuclei were taken and subsequently analysed. Results A statistically significant difference between the genders was observed in the sizes of the axial diameters of caudate nucleus, putamen and globus pallidus. Caudate nucleus transverse diameter showed a moderate negative correlation with age in males. Globus pallidus axial diameter with age showed weak positive correlation for males. Globus pallidus transverse diameter showed weak positive correlation with age for both males and females, but it was stronger for males compared to females. Conclusions These results will help neurologists and neurosurgeons in analysing various early degenerative diseases and treat them accordingly.

AbstractThe airflow behaviour and particle deposition before and after the maxillary expansion are evaluated using the computational fluid dynamics method. A pediatric patient was subjected to maxillary expansion and the CT scans of pre and post were recorded. The procured CT scans were developed into 3D models using Materialise MIMICS 21.0 (Materialise, Ann Arbor, MI). The analysis was performed using ANSYS FLUENT 2020 R2 with three different flow rates defined at the nostril inlet as 5, 10, and 15 LPM. The surface area and nasal volume increased by 5.1% and 16.5%, respectively, for the post-maxillary expansion case. The velocity profiles show a maximum value at the nasal valve regions followed by a decreased velocity in the mid-nasal region with an 85% lower velocity observed at the nasal valve for the post-maxillary expansion case. The nasal resistance and pressure drop decrease by 46% to 66% in post-maxillary expansion cases. The maximum WSS at the nasal valve region is observed which is reduced by around 47% for post-maxillary expansion cases. Particle deposition studies show a reduction in particle depositions in post cases indicating a greater number of inhaled particles reaching the lungs. The pressure drop and the nasal resistance values were reduced by more than 50% for post-maxillary expansion. The particle deposition studies show increased depositions at higher flow rates for both cases.

Background and objective: Causes for nasal airway obstruction (NAO) are many but septum deviation is the most prevalent etiology. A deviated septum affects the airflow dynamics in the human nasal cavity, which in turn affects the physiological functions of the nasal cavity like heating, humidification, and filtration capabilities. The present study investigates and compares the airflow patterns in a healthy nasal cavity to a septal deviated nasal cavity.Methods: Two nasal airway models are considered and compared in this study. One with a septal deviation and the second with a healthy patent nasal cavity. Airflow analysis is carried out by developing the CT scans into 3D models using Materialise MIMICS (Materialise, Ann Arbor, MI), and then using the FLUENT solver of ANSYS 2020R2. The simulations are carried out for airflows ranging in laminar and turbulent flows using the SST k-ω turbulence model. Polyhedral meshes are used and the mesh check using Grid Convergence Index studies is adopted.Results: The pressure and velocity profiles are assessed for a wide range of mass flow rates. The results indicate a turbulent flow pattern for mass flow rates over 15 LPM. The velocity profiles show aberrated flow profiles in a septal deviated nasal cavity where the peak velocity is observed at the mid-nasal region rather than the nasal valve region. There was a 38% to 55% higher nasal resistance in the septal deviated nasal cavity as compared to a normal and healthy nasal cavity. The pressure drop in the septal deviated nasal cavity is higher by 60%–120% when compared to a healthy nasal cavity.Conclusion: The septal deviated nasal cavity greatly affects the nasal airflow distribution resulting in higher velocities in the mid-nasal region, increased pressure drop and higher nasal resistance. Hence the NAO with septal deviation has to be rectified with proper surgical procedures.

Introduction: Emphysematous pyelonephritis (EPN), an acute necrotizing infection of the kidney and surrounding tissues, is associated with considerable mortality. We evaluated how existing critical care scoring systems could predict the need for intensive care unit (ICU) management for these patients. We also analyzed if CT-imaging further enhances these predictive systems. Patients and Methods: A retrospective analysis of 90 consecutive patients diagnosed clinico-radiologically with EPN from January 2011 to September 2020. Five scoring systems were evaluated for their predictive ability for the need for ICU management and mortality risk: National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), ‘quick’ Sequential Organ Failure Assessment score (qSOFA), Systemic Inflammatory Response Syndrome score (SIRS), and Sequential Organ Failure Assessment score (SOFA). CT images were classified as per Huang & Tseng and evaluated as stand-alone or added to the different predictive models. Receiver operating characteristic (ROC) curves were plotted for each critical care score and CT-Class using logistic regression, to obtain the area under curve (AUC) value for comparison of ICU admission predictability. Patients were analyzed up till discharge. Results: Ninety patients were diagnosed with EPN. Twenty-six patients required ICU management and nine patients died. The best scoring system to predict the need of early ICU management is NEWS (AUC 0.884). CT Class had no independent predictive power, nor did it add significantly to improvement in most of the early warning scoring systems, but rather guided us to the need for radiological, endourological or surgical intervention. Conclusion: In patients with EPN, the NEWS scoring system predicts best the requirement of ICU care. It aids in triage of patients with EPN to appropriate early management and reduce mortality risk.

Background Aging is a non-modifiable risk factor for neurodegenerative disease. It is well established that the brain undergoes physiological atrophy with age. So, this study was conducted to analyse the correlation between the age of the person and the size of the various subcortical nuclei of the brain and whether these measurements can serve as a useful indicator for physiological atrophy leading to degenerative disease in clinical practice. Methods A total of 600 MRI scans from healthy individuals were examined and the measurements of subcortical nuclei were taken and subsequently analysed. Results A statistically significant difference between the genders was observed in the sizes of the axial diameters of caudate nucleus, putamen and globus pallidus. Caudate nucleus transverse diameter showed a moderate negative correlation with age in males. Globus pallidus axial diameter with age showed weak positive correlation for males. Globus pallidus transverse diameter showed weak positive correlation with age for both males and females, but it was stronger for males compared to females. Conclusions These results will help neurologists and neurosurgeons in analysing various early degenerative diseases and treat them accordingly.

Background: Aging is a non-modifiable risk factor for neurodegenerative disease. It is well established that the brain undergoes physiological atrophy with age. So, this study was conducted to analyse the correlation between the age of the person and the size of the various subcortical nuclei of the brain and whether these measurements can serve as a useful indicator for physiological atrophy leading to degenerative disease in clinical practice. Methods: A total of 600 MRI scans from healthy individuals were examined and the measurements of subcortical nuclei were taken and subsequently analysed. Results: A statistically significant difference between the genders was observed in the sizes of the axial diameters of caudate nucleus, putamen and globus pallidus. Caudate nucleus transverse diameter showed a moderate negative correlation with age in males. Globus pallidus axial diameter with age showed weak positive correlation for males. Globus pallidus transverse diameter showed weak positive correlation with age for both males and females, but it was stronger for males compared to females. Conclusions: These results will help neurologists and neurosurgeons in analysing various early degenerative diseases and treat them accordingly.

Byline: Priyanka. Shridharan, Radhika. Nair, Sankar. Gorthi, K. Prakashini, Aparajita. Chatterjee Background: A high dose of statin is used to obtain an intensive lipid-lowering in stroke patients, even in patients [...]

Byline: Priyanka. Shridharan, Tarun. Gangil, Sankar. Gorthi, K. Prakashini Introduction: Diffusion-weighted image or DWI is commonly used to provide valuable and diverse information on acute stroke in tertiary care hospitals. [...]

Aim This article retrospectively evaluates the radiological imaging features in establishing the diagnosis of pancreatic duct disconnection along with outlining the effective management protocols.

Background: The liver is primarily or secondarily involved by numerous vascular, metabolic, infectious, and neoplastic processes resulting in formation of focal liver masses, and the detection of such focal liver lesions is frequently accomplished with sonography. However, the categorization a liver mass as benign or malignant on ultrasound has always been a diagnostic dilemma. Objective: This study aimed to assess if the addition of compression sonoelastography to conventional B-mode ultrasound aided in diagnostic accuracy of the focal hepatic lesions. Materials and Methods: We evaluated B-mode characteristics of 52 liver lesions followed by calculation of their strain values on compression sonoelastography. The lesions were categorized as benign or malignant by ascertaining a cutoff strain value and the comparison was made with the histopathological diagnosis/contrast-enhanced computed tomography characteristics of the lesions. Results: The mean strain index value of malignant hepatic lesions (2.12 ± 1.06) was statistically higher than the benign lesions (0.92 ± 1.06) with 2-tailed P = 0.002. The sensitivity, specificity, and positive and negative predictive values of compression sonoelastography in diagnosing a malignant pathology were 74.4%, 88.9%, 94.6%, and 46.7%, respectively, and the additional evaluation of B-mode features yielded higher sensitivity (95.4% vs. 83.7%) and negative predictive value (75% vs. 46.7%). Conclusion: Compression sonoelastography is an efficient and beneficial complementary tool to B-mode imaging in evaluating solid liver lesions. [ABSTRACT FROM AUTHOR]

Background: Brain tumors present a complex challenge in clinical oncology, where precise diagnosis and classification are pivotal for effective treatment planning. Radiomics, a burgeoning field in neuro-oncology, involves extracting and analyzing numerous quantitative features from medical images. This approach captures subtle spatial and textural information imperceptible to the human eye. However, implementation in clinical practice is still distant, and concerns have been raised regarding the methodological quality of radiomic studies. Methodology: A systematic literature search was performed to identify original articles focused on the use of radiomics for brain tumors from 2015 based on the inclusion and exclusion criteria. The radiomic features train machine learning models for glioma classification, and data are split into training and testing subsets to validate the model accuracy, reliability, and generalizability. The present study systematically reviews the status of radiomic studies concerning brain tumors, also using the radiomics quality score (RQS) to assess the quality of the methodology used in each study. Results: A systematic search of PubMed identified 300 articles, with 18 studies meeting the inclusion criteria for qualitative synthesis. These studies collectively demonstrate the potential of radiomics-based machine learning models in accurately distinguishing between glioma subtypes and grades. Various imaging modalities, including MRI, PET/CT, and advanced techniques like ASL and DTI, were utilized to extract radiomic features for analysis. Machine learning algorithms such as deep learning networks, support vector machines, random forests, and logistic regression were applied to develop predictive models. Conclusions: The present study indicates high accuracies in glioma classification, outperforming traditional imaging methods and inexperienced radiologists in some cases. Further validation and standardization efforts are warranted to facilitate the clinical integration of radiomics into routine practice, ultimately enhancing glioma management and patient outcomes. Open science practices: Machine learning using MRI radiomic features provides a simple, noninvasive, and cost-effective method for glioma classification, enhancing transparency, reproducibility, and collaboration within the scientific community.

الملخص: أهداف البحث: مرض باركنسون والشلل العصبي العلوي التدرجي هما حالتان عصبية تتدهور وتتشابه في السمات السريرية والتصوير. هذا ينتج عنه صعوبة في تشخيص الشلل العصبي العلوي التدرجي من مرض باركنسون. لذا، تهدف الدراسة إلى التحقق من القيمة الأمثل للقياس الخطي للرنين المغناطيسي ومؤشر باركنسون الذي يمكن أن يميز بين الشلل العصبي العلوي التدرجي ومرض باركنسون. طرق البحث: تضمنت الدراسة الاستعادية مجموعة من 84 مريضا، كان 27 مريضا من كل من الشلل العصبي العلوي التدرجي، ومرض باركنسون، والمراقبين الطبيعيين الذين خضعوا لفحص الرنين المغناطيسي للدماغ. تم قياس منطقة الجسم الثنائي، ومنطقة الدماغ الوسطى، ومنطقة الجسر، وعرض دماغ العصب القحفي الأوسط وعرض الدماغ القحفي العلوي على صورة الرنين المغناطيسي للدماغ. تم حساب نسبة منطقة الجسر إلى الدماغ الوسطى، ونسبة عرض دماغ العصب القحفي الأوسط إلى عرض الدماغ القحفي العلوي ومؤشر باركنسون على الرنين المغناطيسي. النتائج: تم استخدام تحليل منحنى الخصائص التشغيلية للمستقبل لتحديد القيمة التشخيصية لكل علامة حيوية. أظهر مؤشر باركنسون على الرنين المغناطيسي حساسية تبلغ 70.4 ٪، وتحديدية تبلغ 88.9 ٪، ودقة تشخيص تبلغ 79.6 ٪ مع قيمة قطع مثلى تبلغ 24.3 للتمييز بين الشلل العصبي العلوي التدرجي ومرض باركنسون. أظهرت نسبة منطقة الجسر إلى الدماغ الوسطى حساسية تبلغ 74.1 ٪، وتحديدية تبلغ 77.8 ٪، ودقة تشخيص تبلغ 75.9 ٪ مع قيمة قطع مثلى تبلغ 24.3 للتمييز بين الشلل العصبي العلوي التدرجي ومرض باركنسون. أظهرت نسبة عرض دماغ العصب القحفي الأوسط إلى عرض الدماغ القحفي العلوي حساسية تبلغ 66.7 ٪، وتحديدية تبلغ 77.8 ٪، ودقة تبلغ 72.2 ٪ مع قيمة قطع مثلى تبلغ 4.65 للتمييز بين الشلل العصبي العلوي التدرجي ومرض باركنسون. الاستنتاجات: كشفت الدراسة أن مؤشر باركنسون على الرنين المغناطيسي ونسبة منطقة الجسر إلى الدماغ الوسطى هما علامات دقيقة للتمييز بين الشلل العصبي العلوي التدرجي ومرض باركنسون وأيضا يمكن أن تساعد القيم الأمثل المشتقة من دراستنا في التشخيص المبكر لمرض باركنسون. Abstract: Objectives: Parkinson's disease (PD) and progressive supranuclear palsy (PSP) are neurodegenerative conditions that have overlapping clinical and imaging features, thus making it difficult to distinguish and diagnose PSP from PD. Therefore, in this study, we aimed to investigate the optimal value of magnetic resonance planimetry and the parkinsonism index to differentiate between PSP and PD. Methods: In this retrospective study, we recruited a total of 84 patients (27 patients with PSP, 27 patients with PD and 27 normal controls) who underwent MRI brain examinations. For each subject, we calculated the corpus callosum area, midbrain area, pons area, middle cerebellar peduncle (MCP) width and superior cerebellar peduncle (SCP) width on MRI brain images. We also calculated the pons to midbrain area (P/M) ratio, MCP/SCP ratio and magnetic resonance parkinsonism index (MRPI). Results: Receiver operating characteristic curve (ROC) analysis was used to identify the diagnostic value of each biomarker. MRPI had a sensitivity of 70.4%, a specificity of 88.9%, and a diagnostic accuracy of 79.6% with an optimum cut off of 24.3 for differentiating PSP from PD. P/M ratio had a sensitivity of 74.1%, a specificity of 77.8%, and a diagnostic accuracy of 75.9% with an optimal cutoff of 24.3 for differentiating PSP from PD. The MCP/SCP ratio had a sensitivity of 66.7%, a specificity of 77.8%, and an accuracy of 72.2% with an optimal cut off of 4.65 for differentiating PSP from PD. Conclusions: The study revealed that MRPI and P/M ratio are accurate markers for differentiating PSP from PD. The optimal cut-off values derived from our study can help in the early diagnosis of PD.