High-resolution Computed Tomography Scans Research Articles

Long-term outcome of pulmonary involvement in patients with coronavirus disease 2019: The role of high-resolution computed tomography and functional status - A prospective single-center observational study.

Since its first outbreak, coronavirus disease 2019 (COVID-19) has led to a great deal of published literature highlighting the short-term determinants of morbidity and mortality. Recently, several studies have reported radiological and functional sequelae from 3 months to 1 year among hospitalized COVID-19 survivors; however, long-term (more than 1 year) respiratory consequences in this population remain to be evaluated. To assess the long-term radiological and pulmonary function outcomes of patients with COVID-19 2 years after resolution of the initial infection. Hospitalized COVID-19 patients with moderate to severe disease who survived acute illness were included in this prospective and partially retrospective study. Clinical assessment, laboratory tests, high-resolution computed tomography scans, and pulmonary function tests (PFTs) were performed at baseline, followed by radiological and lung function assessments at 6 and 24 months. Among 106 enrolled participants (mean age 62 ± 13.5 years; males: 61), 44 (41.5%) and 27 (25.4%) underwent radiological assessment at 6 and 24 months, respectively. Overall, 22.6% (24) of patients had residual radiological abnormalities. Overt fibrosis was observed in 12.2% of patients. Computed tomography disease severity and extent diminished significantly at 6 (13 ± 6, P < 0.001) and 24 months (11 ± 6, P < 0.001) from baseline. PFTs were performed in 65 (61.3%), 22 (20.7%), and 34 (32%) patients at baseline, 6 and 24 months, respectively. Impaired diffusion capacity (median diffusion capacity for carbon monoxide: 60%, interquartile range [IQR]: 51-80), restrictive lung defect (mean total lung capacity: 73.4% ± 18% predicted), and reduced exercise tolerance (median 6-min walk distance: 360 m, IQR: 210-400) were the predominant features at baseline. With the exception of exercise tolerance, a statistically significant improvement was observed in lung function parameters at the extended follow-up (2 years). Hospitalized COVID-19 survivors are at increased risk of developing long-term pulmonary complications, including lung fibrosis. A protocol-based approach to the management of post-COVID-19 patients is mandatory to improve future outcomes.

The lateral retrocanthal transorbital endoscopic approach to the middle fossa: cadaveric stepwise approach and review of quantitative cadaveric data.

The lateral retrocanthal transorbital endoscopic approach (LRCTEA) facilitates trajectory to the middle fossa, preserving the lateral canthal tendon and thus avoiding postoperative complications such as eyelid malposition. Here, the authors sought to define the surgical anatomy and technique of LRCTEA using a stepwise approach in cadaveric heads and offer an in-depth examination of existing quantitative data from cadaveric studies. The authors performed LRCTEA to the middle cranial fossa under neuronavigation in 7 cadaveric head specimens that underwent high-resolution (1-mm) CT scans preceding the dissections. The LRCTEA provided access to middle fossa regions including the cavernous sinus, Meckel's cave, and medial temporal lobe. The trajectories and endpoints of the approach were confirmed using electromagnetic neuronavigation. A stepwise approach was delineated and recorded. The authors' cadaveric study delineates the surgical anatomy and technique of the LRCTEA, providing a stepwise approach for its implementation. As these approaches continue to evolve, their development and refinement will play an important role in expanding the surgical options available to neurosurgeons, ultimately improving outcomes for patients with complex skull base pathologies. The LRCTEA presents a promising advancement in skull base surgery, particularly for accessing challenging middle fossa regions. However, surgeons must remain vigilant to potential complications, including transient diplopia, orbital hematoma, or damage to the optic apparatus.

Myositis-associated interstitial lung disease

Introduction/ObjectiveTo review the epidemiology, general clinical aspects and diagnosis, impact on morbidity and mortality, and general treatment approaches for myositis-associated ILD. Materials and methodsThe relevant literature was reviewed. ResultsThe clinical, radiographic, and histopathological features of interstitial lung disease (ILD) in idiopathic inflammatory myopathies (IIM) are similar to idiopathic ILD. Patients with a known diagnosis of myositis require prompt clinical evaluation including the determination of myositis-associated autoantibodies. Patients possessing autoantibodies associated with ILD or those with any pulmonary symptoms should undergo a pulmonary function test and high-resolution CT (HRCT) scanning of their lungs. ConclusionDespite the lack of placebo-controlled trials, systemic glucocorticoids are considered the mainstay of initial treatment of myositis-associated ILD. Glucocorticoid-sparing agents are often concomitantly administered, particularly in patients with severe disease. The first-line conventional immunosuppressive drugs include either mycophenolate mofetil or azathioprine. If these agents fail or if the pulmonary features are severe or rapidly progressive, then more aggressive immunosuppressive or immunomodulatory therapy including cyclophosphamide, tacrolimus or cyclosporine, rituximab, IVIg, or tofacitinib can be considered. Further investigations are required to assess the role of novel therapies in the treatment of myositis-associated ILD.

Automated detection of otosclerosis with interpretable deep learning using temporal bone computed tomography images

ObjectiveThis study aimed to develop an automated detection schema for otosclerosis with interpretable deep learning using temporal bone computed tomography images. MethodsWith approval from the institutional review board, we retrospectively analyzed high-resolution computed tomography scans of the temporal bone of 182 participants with otosclerosis (67 male subjects and 115 female subjects; average age, 36.42 years) and 157 participants without otosclerosis (52 male subjects and 102 female subjects; average age, 30.61 years) using deep learning. Transfer learning with the pretrained VGG19, Mask RCNN, and EfficientNet models was used. In addition, 3 clinical experts compared the system's performance by reading the same computed tomography images for a subset of 35 unseen subjects. An area under the receiver operating characteristic curve and a saliency map were used to further evaluate the diagnostic performance. ResultsIn prospective unseen test data, the diagnostic performance of the automatically interpretable otosclerosis detection system at the optimal threshold was 0.97 and 0.98 for sensitivity and specificity, respectively. In comparison with the clinical acumen of otolaryngologists at P < 0.05, the proposed system was not significantly different. Moreover, the area under the receiver operating characteristic curve for the proposed system was 0.99, indicating satisfactory diagnostic accuracy. ConclusionOur research develops and evaluates a deep learning system that detects otosclerosis at a level comparable with clinical otolaryngologists. Our system is an effective schema for the differential diagnosis of otosclerosis in computed tomography examinations.

Generation and applications of synthetic computed tomography images for neurosurgical planning.

CT and MRI are synergistic in the information provided for neurosurgical planning. While obtaining both types of images lends unique data from each, doing so adds to cost and exposes patients to additional ionizing radiation after MRI has been performed. Cross-modal synthesis of high-resolution CT images from MRI sequences offers an appealing solution. The authors therefore sought to develop a deep learning conditional generative adversarial network (cGAN) which performs this synthesis. Preoperative paired CT and contrast-enhanced MR images were collected for patients with meningioma, pituitary tumor, vestibular schwannoma, and cerebrovascular disease. CT and MR images were denoised, field corrected, and coregistered. MR images were fed to a cGAN that exported a "synthetic" CT scan. The accuracy of synthetic CT images was assessed objectively using the quantitative similarity metrics as well as by clinical features such as sella and internal auditory canal (IAC) dimensions and mastoid/clinoid/sphenoid aeration. A total of 92,981 paired CT/MR images obtained in 80 patients were used for training/testing, and 10,068 paired images from 10 patients were used for external validation. Synthetic CT images reconstructed the bony skull base and convexity with relatively high accuracy. Measurements of the sella and IAC showed a median relative error between synthetic CT scans and ground truth images of 6%, with greater variability in IAC reconstruction compared with the sella. Aerations in the mastoid, clinoid, and sphenoid regions were generally captured, although there was heterogeneity in finer air cell septations. Performance varied based on pathology studied, with the highest limitation observed in evaluating meningiomas with intratumoral calcifications or calvarial invasion. The generation of high-resolution CT scans from MR images through cGAN offers promise for a wide range of applications in cranial and spinal neurosurgery, especially as an adjunct for preoperative evaluation. Optimizing cGAN performance on specific anatomical regions may increase its clinical viability.

Survival and Lung Function Changes in Hypersensitivity Pneumonitis According to Radiological Phenotypes Compared With Idiopathic Pulmonary Fibrosis.

The main objective of this study was to estimate survival and changes in lung function in patients with chronic hypersensitivity pneumonitis (HP), both fibrotic (f-HP) and nonfibrotic (nf-HP), and to compare them with those in patients with idiopathic pulmonary fibrosis (IPF). HP was diagnosed based on antigen exposure, HRCT (high-resolution CT scan), BAL (bronchoalveolar lavage), and histology. According to HRCT, HP was classified into fibrotic and non-fibrotic phenotypes. In most cases, IPF was diagnosed based on HRCT findings. We identified 84 patients: 46 with IPF, 18 with f-HP, and 20 with nf-HP. Five-year survival was 23.9% in IPF, 72% in f-HP, and 100% in nf-HP (p <0.0001). Honeycombing was associated with decreased survival in IPF (p <0.001) and in f-HP (p <0.0001). The mean loss of FVC (forced vital capacity) % pred. (percent predicted) was -18.3% in IPF (p =0.001), -4.8% in f-HP, and -6.0% in nf-HP. The mean change in DLCO (diffusion capacity for carbon monoxide) % pred. was -10.2% in IPF (p <0.002), -0.5% in f-HP, and +1.9% in nf-HP. The agreement between radiological phenotypes and histology in HP was 89.6%. We found shorter survival in IPF, followed by f-HP, and nf-HP. Over time, we did not find significant changes in FVC% pred. or DLCO% pred. in HP, while a significant decline in IPF was noted. In HP, we found strong agreement between radiological phenotypes and histology. Radiological signs suggestive of lung fibrosis in HP were reliable for the diagnosis of f-HP and seem to have intrinsic prognostic value.

Three-Dimensional Osseointegration Patterns of Cementless Femoral Stems: An ex Vivo Study with High-Resolution Imaging and Histological Evaluation.

Osseointegration is essential for the long-term survival of cementless femoral stems and is dependent on periprosthetic bone quality and correct implantation technique. The aim of this study was to evaluate the 3-dimensional long-term fixation patterns of, and bone microarchitecture around, cementless hip stems. Four specimens with varying degrees of bone quality and fixation characteristics from body donors who had received Alloclassic Zweymüller hip stems during their lifetime (mean time in situ at the time of death: 12.73 years) were evaluated with use of radiographs, high-resolution computed tomography (CT) scans, and hard-tissue histology. The CT voxel size was 85 µm, and the following parameters were calculated: total bone volume, total bone volume fraction, trabecular bone volume, trabecular bone volume fraction, cortical bone volume, cortical bone volume fraction, and cortical thickness. Bone-implant contact and canal fill index values for each Gruen zone of the specimens were calculated with use of histological samples. Femoral stems with apparently good cortical contact on clinical radiographs showed higher values for cortical bone volume, trabecular bone volume, and cortical thickness in the high-resolution CT analysis than femoral stems with apparently weak cortical contact on clinical radiographs. Based on the histological evaluation, the mean bone-implant contact ranged from 22.94% to 57.24% and the mean canal fill index ranged from 52.33% to 69.67% among the specimens. This study demonstrated different osseointegration patterns of cementless femoral stems on the basis of radiographs, high-resolution CT scans, and histological evaluation. Femora with high cortical bone volume and cortical thickness were associated with higher canal fill indices, whereas femora with low cortical bone volume and cortical thickness had lower canal fill indices and showed a characteristic corner-anchorage pattern. Osseointegration patterns and thus the long-term survival of cementless femoral stems are dependent on cortical bone volume and cortical thickness.

Characteristics of Patients with Hypertension Admitted for COVID-19 Treatment in Khulna: Single-Centre Cross-Sectional Study

Background: The outbreak of coronavirus disease 2019 (COVID-19) has become a large threat to global health due to its high contagious nature and varied mortality. Arterial hypertension represents one of the most common comorbidities in patients with COVID-19. Close connections between inflammation and blood pressure (BP) have been described, and inflammation plays a key role in the outcome for patients with COVID-19. Objective: This study aims to investigate the clinical characteristics of patients with hypertension admitted for COVID-19 treatment in Gazi Medical College Hospital (GMCH), Khulna, Bangladesh. Methods: This was a cross-sectional type of observational study on patients with hypertension who were diagnosed with COVID-19 based on laboratory and/or radiological findings and admitted to Gazi Medical College Hospital, Khulna, Bangladesh, from July 1 to July 31, 2021. In that timeframe, overall, 215 patients with COVID-19 were admitted. Among them, 37 patients having hypertension fulfilled the inclusion criteria for the study. Demographic, clinical, laboratory and radiological data of those 37 patients were recorded and analyzed. Results: Among 37 study subjects, 54.1% were female. The mean age of the patients was 59.6±13.9 years. Among the study subjects, diabetes (56.8%) was the most common comorbidity. Regarding laboratory parameters, the mean Hb of the patients was 11.4±1.9 g/dl. In addition, the mean random blood sugar (RBS) level was 11.6±2.9 mmol/l. Neutrophilia and lymphocytopenia were observed in 86.5% and 83.8% cases, respectively. The mean D-dimer (2.4 mg/l) and CRP (72.5 mg/l) levels were well above their normal limits. In high resolution CT scan of the chest (HRCT chest), bilateral lung involvement was present in 89.2% cases. Ground-glass appearance was the most frequent (91.9%) radiologic pattern. Among antihypertensive drugs, losartan potassium was the most frequently used category (29.7%). Total 7 (18.9%) patients were severely affected with COVID-19 and admitted to the ICU, requiring mechanical ventilation. During our study, 2 patients (5.4%) died either due to multiple organ dysfunction syndrome or cardio-respiratory failure. Conclusion: The study provides key information to better understand the clinical characteristics of patients with hypertension admitted for COVID-19 treatment, which may help physicians to identify the factors associated with adverse outcomes in this disease. Mediscope 2024;11(1): 34-40

Clinical Diagnosis and Treatment of 43 Cases of Occipital Condylar Fractures: A Single-Center Retrospective Study

This study aimed to examine the mechanism of occipital condyle fractures (OCFs), their clinical symptoms, computer tomography (CT) scan findings, treatment options, and classification. A retrospective analysis was conducted on 43 patients with OCFs who were admitted to our neurosurgery center between 2017 and2023. The investigation covered their clinical symptoms, CT scan results, and treatment outcomes. It was found that 25.6% of the patients suffered from severe craniocerebral injuries with Glasgow Coma Scale (GCS) scores of 3-8 points, 9.3% had moderate injuries with GCS scores of 9-12 points, and 65.1% exhibited mild injuries with GCS scores of 13-15 points. Of these patients, 90.7% showed improvement upon discharge, 4.7% succumbed to their injuries, and another 4.7% developed paraplegia. Symptoms indicative of OCF in individuals with CCJ injuries included neck pain, swelling, cranial nerve palsy, and posterior pharyngeal wall swelling. Frequently observed complications in OCF patients included cerebral contusion, occipital bone fractures, and skull base fractures. Employing thin-layer CT scans of the CCJ area, along with sagittal and coronal CT reconstructions, is essential for identifying OCFs. The fractures were classified into 3 types based on the Anderson-Montesano classification, which, when modified, provides enhanced treatment guidance. OCFs are predominantly present in cases of high-energy trauma, with high-resolution thin-layer CT scans serving as the preferred diagnostic method. The application of the modified Anderson-Montesano classification, distinguishing between stable and unstable fractures, facilitates the determination of suitable treatment strategies. Stable OCFs can be managed using a rigid neck brace, while unstable OCFs may require Halo-vest frame fixation or surgical intervention.

RPA3-UMAD1 rs12702634 and rheumatoid arthritis–associated interstitial lung disease in European ancestry

Abstract Objective Recently, a genome-wide association study identified an association between RA-associated interstitial lung disease (ILD) and RPA3-UMAD1 rs12702634 in the Japanese population, especially for patients with a usual interstitial pneumonia (UIP) pattern. We aimed to replicate this association in a European population and test for interaction with MUC5B rs35705950. Methods In this genetic case–control association study, patients with RA and ILD and controls with RA and no ILD were included from France, the USA and the Netherlands. Only cases and controls from European genetic ancestries determined by principal components analysis were included in the analyses. RA was defined by the 1987 ACR or 2010 ACR/EULAR criteria and ILD by chest high-resolution CT scan, except in the control dataset from the Netherlands, where the absence of ILD was determined by chart review. Patients were genotyped for RPA3-UMAD1 rs12702634 and MUC5B rs35705950. Associations were tested using logistic regression adjusted for sex, age at RA onset, age at ILD onset or at certified absence of ILD, tobacco smoking status and country of origin. Results Among the 883 patients included, 322 were RA-ILD cases (36.5%). MUC5B rs35705950 was strongly associated with RA-ILD in all datasets {combined adjusted odds ratio [OR] 2.9 [95% CI 2.1, 3.9], P = 1.1 × 10−11. No association between RPA3-UMAD1 rs12702634 and RA-ILD was observed [combined OR 1.2 (95% CI 0.8, 1.6), P = 0.31. No interaction was found between RPA3-UMAD1 rs12702634 and MUC5B rs35705950 (P = 0.70). Conclusion Our findings did not support a contribution of RPA3-UMAD1 rs12702634 to the overall RA-ILD susceptibility in the European population.

Novel 3D-based deep learning for classification of acute exacerbation of idiopathic pulmonary fibrosis using high-resolution CT

PurposeAcute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is the primary cause of death in patients with IPF, characterised by diffuse, bilateral ground-glass opacification on high-resolution CT (HRCT). This study proposes...

Clinical evaluation of pulmonary quantitative computed tomography parameters for diagnosing eosinophilic chronic obstructive pulmonary disease: Characteristics and diagnostic performance.

To investigate the characteristics and diagnostic performance of quantitativecomputed tomography (QCT) parameters in eosinophilic chronic obstructive pulmonary disease (COPD) patients. High-resolution CT scans of COPD patients were retrospectively analyzed, and various emphysematous parenchyma measurements, including lung volume (LC), lung mean density (LMD), lung standard deviation (LSD), full-width half maximum (FWHM), and lung relative voxel number (LRVN) were performed. The QCT parameters were compared between eosinophilic and noneosinophilic COPD patients, using a definition of eosinophilic COPD as blood eosinophil values ≥ 300 cells·µL-1 on at least three times. Receiver operating characteristic curves and area under the curve (ROC-AUC) and python were used to evaluate discriminative efficacy of QCT. Noneosinophilic COPD patients had a significantly lower TLMD (-846.3 ± 47.9 Hounsfield Unit[HU]) and TFWHM(162.5 ± 30.6 HU) compared to eosinophilic COPD patients (-817.8 ± 54.4, 177.3 ± 33.1 HU, respectively) (p = 0.018, 0.03, respectively). Moreover, the total LC (TLC) and TLSD were significantly lower in eosinophilic COPD group (3234.4 ± 1145.8, 183.8 ± 33.9 HU, respectively) than the noneosinophilic COPD group (5600.2 ± 1248.4, 203.5 ± 20.4 HU, respectively) (p = 0.009, 0.002, respectively). The ROC-AUC values for TLC, TLMD, TLSD, and TFWHM were 0.91 (95% confidence interval [CI], 0.828-0.936), 0.66 (95% CI, 0.546-0.761), 0.64 (95% CI, 0.524-0.742), and 0.63 (95% CI, 0.511-0.731), respectively. When the TLC value was 4110 mL, the sensitivity was 90.7% (95% CI, 79.7-96.9), specificity was 77.8% (95% CI, 57.7-91.4) and accuracy was 86.4%. Notably, TLC demonstrated the highest discriminative efficiency with an F1 Score of 0.79, diagnostic Odds Ratio of 34.3 and Matthews Correlation Coefficient of 0.69, surpassing TLMD (0.55, 3.66, 0.25), TLSD (0.56, 3.95, 0.26), and TFWHM (0.56, 4.16, 0.33). Eosinophilic COPD patients exhibit lower levels of emphysema and a more uniform density distribution throughout the lungs compared to noneosinophilic COPD patients. Furthermore, TLC demonstrated the highest diagnostic efficiency and may serve as a valuable diagnostic marker for distinguishing between the two groups.

The CT Scan Lung Severity Score and Vaccination Status in COVID-19 patients in India: Perspective of an Independent Radiology Practice

Background Patients with COVID-19 often undergo a high-resolution CT scan to determine the extent of lung involvement. The aim of this study was to determine lung involvement in confirmed/suspected COVID-19 patients (encountered at an independent radiology practice) and its correlation to vaccination status amidst the second COVID-19 wave in India. Methods We retrospectively queried our data from April 2021 to identify adult patients (&gt;17 years) who had confirmed (positive RT-PCR or antigen test) or suspected COVID-19 (classic symptoms but negative RT-PCR) and received a high-resolution CT scan to determine the extent of lung involvement using the CT severity (CT-SS) score. The patients were classified into three groups based on their vaccination status to determine their correlation with the CT-SS score: fully vaccinated, partially vaccinated, and unvaccinated. Basic descriptive statistics, univariate tests, and multivariate linear regression analyses were performed. Results We identified 229 patients (median age, 45 years; 60% male), of whom 205 (89%) had confirmed COVID-19 (positive RT-PCR) and 24 had suspected disease (negative RT-PCT but classic symptoms). Of 229 patients, 29 (13%) had complete vaccination, 38 (17%) had partial vaccination, and 162 (70%) had no vaccination. The CT score of the completely vaccinated patients was significantly lower than that of the partially or unvaccinated patients (median 0 v. 3.5 v. 10, respectively p&lt;.01). Conclusion Here, we present real-world findings from an independent radiology practice (a unique and common practice model) in India amid the second COVID-19 wave, showing significantly lower CT severity scores in fully or partially vaccinated patients compared to unvaccinated patients. Complete vaccination of patients may be critical in preventing severe lung disease.

Deep learning-based harmonization of trabecular bone microstructures between high- and low-resolution CT imaging.

Osteoporosis is a bone disease related to increased bone loss and fracture-risk. The variability in bone strength is partially explained by bone mineral density (BMD), and the remainder is contributed by bone microstructure. Recently, clinical CT has emerged as a viable option for in vivo bone microstructural imaging. Wide variations in spatial-resolution and other imaging features among different CT scanners add inconsistency to derived bone microstructural metrics, urging the need for harmonization of image data from different scanners. This paper presents a new deep learning (DL) method for the harmonization of bone microstructural images derived from low- and high-resolution CT scanners and evaluates the method's performance at the levels of image data as well as derived microstructural metrics. We generalized a three-dimensional (3D) version of GAN-CIRCLE that applies two generative adversarial networks (GANs) constrained by the identical, residual, and cycle learning ensemble (CIRCLE). Two GAN modules simultaneously learn to map low-resolution CT (LRCT) to high-resolution CT (HRCT) and vice versa. Twenty volunteers were recruited. LRCT and HRCT scans of the distal tibia of their left legs were acquired. Five-hundred pairs of LRCT and HRCT image blocks of voxels were sampled for each of the twelve volunteers and used for training in supervised as well as unsupervised setups. LRCT and HRCT images of the remaining eight volunteers were used for evaluation. LRCT blocks were sampled at 32 voxel intervals in each coordinate direction and predicted HRCT blocks were stitched to generate a predicted HRCT image. Mean±standard deviation of structural similarity (SSIM) values between predicted and true HRCT using both 3DGAN-CIRCLE-based supervised (0.84±0.03) and unsupervised (0.83±0.04) methods were significantly (p<0.001) higher than the mean SSIM value between LRCT and true HRCT (0.75±0.03). All Tb measures derived from predicted HRCT by the supervised 3DGAN-CIRCLE showed higher agreement (CCC [0.956 0.991]) with the reference values from true HRCT as compared to LRCT-derived values (CCC [0.732 0.989]). For all Tb measures, except Tb plate-width (CCC=0.866), the unsupervised 3DGAN-CIRCLE showed high agreement (CCC [0.920 0.964]) with the true HRCT-derived reference measures. Moreover, Bland-Altman plots showed that supervised 3DGAN-CIRCLE predicted HRCT reduces bias and variability in residual values of different Tb measures as compared to LRCT and unsupervised 3DGAN-CIRCLE predicted HRCT. The supervised 3DGAN-CIRCLE method produced significantly improved performance (p<0.001) for all Tb measures as compared to the two DL-based supervised methods available in the literature. 3DGAN-CIRCLE, trained in either unsupervised or supervised fashion, generates HRCT images with high structural similarity to the reference true HRCT images. The supervised 3DGAN-CIRCLE improves agreements of computed Tb microstructural measures with their reference values and outperforms the unsupervised 3DGAN-CIRCLE. 3DGAN-CIRCLE offers a viable DL solution to retrospectively improve image resolution, which may aid in data harmonization in multi-site longitudinal studies where scanner mismatch is unavoidable.

Normative reference data for intracranial volume in children: The results of CT volumetry.

Intracranial volume (ICV) is an important indicator of the development of the brain and skull in children. At present, there is a lack of ICV growth standards based on large infant and children samples. Our aim was to assess the normal range of the ICV variation in Russian children using a modern automatic system for constructing the endocranial cavity (Endex) and to provide growth standards of the ICV for clinical practice. High-resolution head CT scans were obtained from 673 apparently healthy children (380 boys and 293 girls) aged 0-17years and transformed into the ICV estimates using the Endex software. The open-source software RefCurv utilizing R and the GAMLSS add-on package with the LMS method was then used for the construction of smooth centile growth references for ICV according to age and sex. We demonstrated that the ICVs estimates calculated using the Endex software are perfectly comparable with those obtained by a conventional technique (i.e. seed feeling). Sex-specific pediatric growth charts for ICV were constructed. This study makes available for use in clinical practice ICV growth charts for the age from 0 to 17 based on a sample of 673 high-resolution CT images.

Assessment of sleep quality in severe COVID-19 hospitalised patients.

To evaluate the quality of sleep in patients hospitalised with coronavirus disease-2019, and its impact on hospitalisation duration, need for intensive care unit admission and mortality. The cross-sectional study was conducted at the Pakistan Institute of Medical Sciences, Islamabad, Pakistan, from May 2, 2021 to April 30, 2022, and comprised hospitalised coronavirus disease-2019 patients. Data was gathered using the Pittsburgh Sleep Quality Index questionnaire, including demographics, comorbidities, length of hospital stay, need for intensive care unit admission, C-reactive protein and D-dimer values at admission, and the outcome. The patients were divided into group A having good sleep quality score >5 and group B having poor sleep quality score <5. Data was analysed using SPSS 25. Of the 1,250 patients, 559(44.7%) were males and 691(55.3%) were females. There were 560(44.8%) patients in group A with mean age 53.80±14.85 years, and 690(55.2%) patients in group B with mean age 53.71±14.32 years. There were no significant intergroup differences in terms of age and high-resolution computed tomography scan (p>0.05). The difference was significant with respect to gender, comorbid conditions, education status as well C-reactive protein and D-dimer levels (p<0.001). Group B patients had a longer duration of hospitalisation (p<0.001) and a higher need for intensive care unit admission (p<0.001) compared to group A. The outcome was death in 166(13.28%) patients in group B compared to 40(3.2%) in group A (p<0.001). Poor sleep quality was found to be associated with longer hospital stay, increased need for mechanical ventilation, and higher mortality rate in coronavirus disease-2019 patients.

RADIOLOGICAL EVALUATION OF INTERSTITIAL LUNG DISEASES ON HIGH-RESOLUTION COMPUTED TOMOGRAPHY IN TERTIARY CARE CENTER OF NORTH INDIA

Objective: This study assessed the various high-resolution computed tomography (HRCT) patterns of interstitial lung diseases (ILDs) and to differentially diagnose ILD based on their clinical findings and distribution patterns. Methods: The study was conducted in the Department of Radiodiagnosis, Government Medical College and Rajindra Hospital, Patiala, Punjab, India. Forty-three patients with clinical suspicion of ILD were enrolled in the study. HRCT scans of the chest were done in all the cases taken in the study. Results: The mean age (±he age group of 51–60 years. We found slight female preponderance with females accounting for 53.5% and males accounting for 46.5% of the caseload. The most common presenting complaint was dyspnea on exertion (83.7%) followed by cough in 69.8%. The most frequent HRCT finding was septal thickening (90.7%), followed by tractional bronchiectasis (83.7%), fibrotic changes (72.1%), ground-glass opacities (65.1%), and honeycombing (58.1%). Based on HRCT findings, the most common HRCT pattern was the typical usual interstitial pneumonia pattern (58.1%), followed by the non-specific interstitial pneumonia pattern. The final diagnoses were made based on clinic-radiological findings and by the exclusion of other possibilities. The most common ILD reported was idiopathic pulmonary fibrosis (39.5%), followed by connective tissue disorder-ILD (20.9%), and SR-ILD (13.9%). This is followed by idiopathic non-specific interstitial pneumonia (11.6%), hypersensitivity pneumonitis (6.9%), and cryptogenic organizing pneumonia (2.3%). Conclusion: HRCT is a valuable technique for evaluating various ILDs even when chest X-rays are normal. It can differentially diagnose ILDs based on their clinical findings and distribution patterns.

Intensified Late-Holocene aeolian activity in Vesterålen, northern Norway – increased storminess or human impact?

This study reconstructs Mid- to Late-Holocene aeolian activity based on lacustrine sediments from a small pond, Nøkktjønna, situated ~1.5 km northeast from the coast, and stratigraphical investigations of coastal dunes at Fjærvoll, Langøya in Vesterålen, northern Norway. Several methods have been used to reconstruct catchment processes from the lacustrine record, including analyses of lithostratigraphy, organic content, magnetic susceptibility, and grain size, combined with high-resolution X-ray fluorescence (XRF) and Computed Tomography (CT) scanning. The content of coarse mineral grains (&gt;125 μm) has been quantified throughout the lacustrine core by manual wet sieving and by conducting threshold analysis from the high-resolution CT-scans. Considering the setting of the drainage basin of Nøkktjønna, the mineral grains (&gt;125 μm) in the sediment core are suggested to have been deposited by aeolian transportation from the nearby aeolian dunes and beach sand during storm events. Five periods of intensified aeolian influx (defined here as influx values above the 90th percentile) are identified. These periods occurred around ~6950, ~6500, ~6100–6000, 5800–5750 and ~350–20 cal. yr BP cal. yr BP, with the last period being the most intense. The increased influx in aeolian sand to Nøkktjønna is suggested to be associated with a combination of changes in the storm track pattern, sea-level fluctuations, conditions of snow cover/frozen surface and increased anthropogenic influence. The highest influx rates are recorded between CE 1600 and 1930, corresponding to the ‘Little Ice Age’ (LIA), which is a well-known period of high storminess in the North Atlantic region.

HRCTCov19-a high-resolution chest CT scan image dataset for COVID-19 diagnosis and differentiation.

Computed tomography (CT) was a widely used diagnostic technique for COVID-19 during the pandemic. High-Resolution Computed Tomography (HRCT), is a type of computed tomography that enhances image resolution through the utilization of advanced methods. Due to privacy concerns, publicly available COVID-19 CT image datasets are incredibly tough to come by, leading to it being challenging to research and create AI-powered COVID-19 diagnostic algorithms based on CT images. To address this issue, we created HRCTCov19, a new COVID-19 high-resolution chest CT scan image collection that includes not only COVID-19 cases of Ground Glass Opacity (GGO), Crazy Paving, and Air Space Consolidation but also CT images of cases with negative COVID-19. The HRCTCov19 dataset, which includes slice-level and patient-level labeling, has the potential to assist in COVID-19 research, in particular for diagnosis and a distinction using AI algorithms, machine learning, and deep learning methods. This dataset, which can be accessed through the web at http://databiox.com , includes 181,106 chest HRCT images from 395 patients labeled as GGO, Crazy Paving, Air Space Consolidation, and Negative.

GDF15 as a potential biomarker to distinguish fibrotic from non-fibrotic hypersensitivity pneumonitis

Hypersensitivity Pneumonitis (HP) is an immune-mediated interstitial lung disease (ILD) characterized by fibrotic HP (fHP) or non-fibrotic HP (non-fHP). Fibrosis is associated with poor prognosis, emphasizing the need for biomarkers to distinguish fHP from non-fHP. This study aimed to determine the plasma levels of GDF15 in HP patients and assess its association with lung function and phenotype classification. GDF15 levels were quantified by ELISA in HP (n = 64), idiopathic pulmonary fibrosis (n = 54), and healthy control (n = 128) groups. Clinical, demographic, and functional data were obtained from medical records. High-resolution chest CT scans were used to classify HP patients into fHP and non-fHP groups. In addition, receiver operating characteristic analysis was performed to determine the cut-off point, sensitivity, and specificity. Our results revealed significantly elevated GDF15 levels in fHP compared to non-fHP (2539 ± 821 pg/ml versus 1783 ± 801 pg/ml; p = 0.009). The estimated cut-off point for plasma GDF15 levels to distinguish fHP from non-fHP was 2193.4 pg/ml (AUC 0.75). These findings suggest that GDF15 may serve as a valuable biomarker for differentiating between fHP and non-fHP, potentially indicating its involvement in lung fibrosis development in HP.