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Liposarcoma is the commonest soft tissue neoplasm, usually located in the deep soft tissue of the limbs. The central nervous system (CNS) as the primary site is exceedingly rare. We report a 35-year-old male patient who presented with seizure and weakness of the left half of the body for three months. The magnetic resonance imaging of the brain revealed a large solid partially necrotic lesion in the right posterior frontal lobe with perilesional edema. The tumour was firm, intra-axial, not adherent to the dura, and was completely excised. Based on the morphology, immunohistochemistry, and imaging findings, the diagnosis of primary intracerebral pleomorphic liposarcoma was rendered. Post-operatively, the patient had an uneventful follow-up. Pleomorphic liposarcoma is a rare CNS tumor with aggressive behavior, high potential for local recurrence, and distant metastasis. However, the acquaintance with intracranial liposarcoma is limited because of its rarity, and thus, no standard treatment protocol is of consensus. [ABSTRACT FROM AUTHOR]

Thalassemic osteopathy includes low bone mass and impaired bone microarchitecture. We aimed to evaluate the prevalence and determinants of bone quantity (osteoporosis) and quality (microarchitecture) in a cohort of adult patients with transfusion-dependent thalassemia (TDT). Patients with TDT (n = 63) and age- and BMI-matched controls (n = 63) were recruited in the study. Areal bone mineral density (BMD) was measured using DXA Hologic scanner. P1NP and β-CTX were estimated by electrochemiluminescence assay. Bone geometry and volumetric BMD (vBMD) were estimated by second-generation high-resolution peripheral quantitative computed tomography. Bone turnover marker β-CTX was significantly lower in the TDT group, but there was no difference in P1NP levels. Low bone mass (Z ≤ −2) was present in greater proportion of patients both at lumbar spine (LS) (54 vs 0%; p = .001) and femoral neck (FN) (33 vs 8%; p = .001). Hypogonadism was associated with low BMD at FN (OR 10.0; 95% CI, 1.2–86; p = .01) and low hemoglobin with low BMD at LS (OR 1.58; 95% CI, 0.96–2.60; p = .07). The mean trabecular bone score was also significantly lower in patients compared with controls (1.261 ± 0.072 vs 1.389 ± 0.058). Total, cortical and trabecular vBMD were significantly lower in cases than controls. The trabecular number and cortical thickness were significantly lower and trabecular separation higher in cases than controls. Adults with TDT have significantly lower areal, cortical and trabecular vBMD. The bone microarchitecture is also significantly impaired in terms of lower number and wider spacing of trabeculae as well as lower cortical thickness and area at both radius and tibia. Graphical Abstract Lay Summary: Bone quantity and quality are likely to be affected in patients with thalassemia who are dependent on regular blood transfusions. This study evaluated bone health in adults with transfusion-dependent thalassemia (TDT) by comparing bone density and microarchitecture with age- and BMI-matched controls. Adults with TDT had significantly lower bone mineral density (both areal and volumetric), suggesting low bone quantity compared to healthy controls. Trabecular and cortical microarchitecture were also adversely affected, suggesting impaired bone quality. Overall, the study highlights that adults with TDT have significantly compromised bone quantity and quality, increasing their risk for osteoporosis and related fractures. [ABSTRACT FROM AUTHOR]

A multiscale feature fusion of Efficient‐Residual Net is proposed for classifying tumors on brain Magnetic resonance images with solid or cystic masses, inadequate borders, unpredictable cystic and necrotic regions, and variable heterogeneity. Therefore, in this research, Efficient‐Residual Net is proposed by efficaciously amalgamating features of two Deep Convolution Neural Networks—ResNet50 and EffficientNetB0. The skip connections in ResNet50 have reduced the chances of vanishing gradient and overfitting problems considerably thus learning of a higher number of features from input MR images. In addition, EffficientNetB0 uses a compound scaling coefficient for uniformly scaling the dimensions of the network such as depth, width, and resolution. The hybrid model has improved classification results on brain tumors with similar morphology and is tested on three internet repository datasets, namely, Kaggle, BraTS 2018, BraTS 2021, and real‐time dataset from Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh. It is observed that the proposed system delivers an overall accuracy of 96.40%, 97.59%, 97.75%, and 97.99% on the four datasets, respectively. The proposed hybrid methodology has given assuring results of 98%–99% of other statistical such parameters as precision, negatively predicted values, and F1 score. The cloud‐based web page is also created using the Django framework in Python programming language for accurate prediction and classification of different types of brain tumors. [ABSTRACT FROM AUTHOR]

Background: Brain metastases (BM) are common in metastatic nonsmall cell lung cancer (NSCLC). However, routine neuroimaging in asymptomatic patients with metastatic NSCLC is controversial as there is no conclusive evidence of benefit from the detection and treatment of asymptomatic BM. Herein, we evaluated the prevalence of asymptomatic BM and its treatment implications in a resource-limited setting. Methods: Consecutive patients with newly diagnosed, treatment-naïve, metastatic, nonsquamous NSCLC (NS-NSCLC) were included. Subjects who already had clinical or radiological features suggestive of BM were excluded from the study. All eligible subjects underwent contrast-enhanced magnetic resonance imaging (MRI) of the brain. Management of the detected BM was at the discretion of the treating clinicians. Results: Among 809 subjects who were screened, 100 (12.4%) were included in the study and underwent MRI. BM was present in 30 (30%) of the subjects and absent in the remaining 70 subjects. A majority of BM were multiple (70%), involved the frontal lobe commonly (73.3%), and had a mean (standard deviation) size of 13.2 (7.3) mm. Detection of BM resulted in a treatment alteration in 17 (17%) of the study subjects (brain irradiation, n = 17, change in targeted therapy, n = 3) with BM. There was no difference in survival of patients who underwent treatment alteration for management of BM compared to those who did not (P = 0.132). Conclusions: About one-third of patients with metastatic NS-NSCLC had BM in MRI despite the absence of symptoms. Despite treatment of the majority of the patients with BM with brain irradiation, there was no demonstrable survival benefit. Hence, we conclude that although routine neuroimaging of asymptomatic patients with newly diagnosed metastatic NSCLC may result in treatment alteration (primarily brain irradiation) in a small proportion of patients, it may not influence outcomes in resource-constrained settings. [ABSTRACT FROM AUTHOR]

Background: Acromegaly is a rare chronic endocrine disorder with variable biochemical remission rates from 40% to 85%. Hence, understanding the factors predicting biochemical cures helps in planning targeted and personalized treatment. We aimed to study the various clinico-radio-pathological predictors of outcomes in patients with pituitary neuroendocrine tumor (PitNET) who underwent transsphenoidal surgery (TSS) at 3 months follow-up. Methods: Our cohort included 61 consecutive patients with acromegaly treated at an institute in northwest India between January 2019 and June 2021. The outcomes of TSS were assessed at the end of 3 months postoperatively as defined by Endocrine Society Guidelines 2014. Results: The mean age at diagnosis was 38 ± 12 years, with the majority being females (67.2%). The median tumor volume was 2376 mm3 with high insulin-like growth factor-1 levels (3.12 ± 1.76 times the upper reference limit). Forty-two patients (68.8%) had radiological evidence of cavernous sinus invasion. Overall, the biochemical remission rate at 3 months was 34.4%. Unlike preoperative Knosp grading, T2-hypointensity was not predictive of biochemical remission. The granularity of PitNET, as well as immunohistochemical (IHC) markers such as Ki-67 index somatostatin receptor subtype (SSTR2/5) and low-molecular-weight cytokeratin (CAM5.2) expression, failed to show any significant correlation with remission. Conclusion: Overall, bulky tumors, higher hormone burden, and advanced Knosp grades translated to lower rates of biochemical remission in the present study cohort. Contrary to earlier studies, conventional IHC markers such as Ki-67, SSTR2/5, and CAM5.2 were not useful for predicting biochemical remission at 3 months. [ABSTRACT FROM AUTHOR]

Background: Giant intracranial 'IgG4-related' lesions are uncommon. They may present as pachymeningitis or localized mass. Here we report, probably, the largest IgG4 skull base mass ever to be reported. Case: A 40-year male presented with headache, diplopia, right-sided sensori-neuronal hearing loss, and left spastic hemiparesis. Magnetic resonance imaging showed a lesion of 8.5 cm extending from the paranasal sinuses to the right petroclival region with uniform contrast enhancement and T2 hypointensity. Endonasal biopsy revealed respiratory epithelium with fibrosis, and lymphoplasmacytic infiltrate having IgG4 positive cells >30/HPF suggestive of 'IgG4-related' disease. Serum IgG4 was within normal levels. With oral prednisolone 60 mg given daily for 6 weeks and then tapered off over 8 weeks, he improved symptomatically. Conclusion: Though rare, 'IgG4-related' disease can also present as a giant skull base mass and should be kept as a differential to fungal granulomas and meningiomas. As they improve dramatically with medical management, extensive skull base resection should not be planned before obtaining a tissue biopsy, especially when there is extension into paranasal sinuses and T2 hypointensity. [ABSTRACT FROM AUTHOR]

Objective: To derive a clinical score from parameters that favor remission of Cushing's disease (CD) after pituitary surgery. Methods: This is an analysis of 11 clinical, hormonal, and post-operative parameters that each favored remission in a cohort of 145 patients with CD treated by trans-sphenoidal surgery (TSS). Each parameter was designated as a categorical variable (presence/absence), and several favorable parameters present for each patient were calculated. From this, a median parameter score (clinical score) of the entire cohort was derived, which was then compared to the event of remission/persistence of CD. Results: The median number of favorable parameters present in the entire cohort was 3 (0-7). The significant count of patients in remission increased with the increasing number of parameters. The receiver-operator characteristic curve showed that the presence of =3 parameters was associated with remission in CD with a sensitivity of 84.2% and a specificity of 80%. Patients with a clinical score =3 had significantly higher remission rates (88.9%) than those who had persistent disease (27.3%; P = 0.001). Conclusion: A clinical score of =3 predicts remission in CD treated by TSS; however, it requires validation in other large cohorts. Rather than assessing individual parameters to predict remission in CD, an integrated clinical score is a better tool for follow-up and patient counseling. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: More than half of the bipolar depression (BD) subjects are misdiagnosed as unipolar depression (UD) due to lack of objective diagnostic criteria. We aimed to identify microstructural neuronal changes differentiating BD from UD groups using diffusion kurtosis imaging (DKI). The objective of the study is to identify an objective neuro-imaging marker to differentiate BD from UD. Materials and Methods: A prospective, cross-sectional study included total of 62 subjects with diagnosis of bipolar depression (n = 21), unipolar depression (n = 21), and healthy controls (n = 20). All subjects underwent diffusion-weighted imaging (b = 0,1000,2000) of the whole brain on 3-Tesla MR scanner. DKI data was analyzed using 189 region whole-brain atlas. Eight diffusion and kurtosis metrics including mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), fractional anisotropy (FA), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), and kurtosis fractional anisotropy (FKA) were measured against these 189 regions. Principle component analysis (PCA) was utilized to identify the most significant regions of the brain. ANOVA with post hoc tests was used for analyzing these regions. Results: BD group showed increased MD, RD, decreased AK at the left amygdala and decreased MK and RK at the right hemi-cerebellum. UD group showed increased MK and RK at the right external capsule; and increased AK, MK, and RK at the right amygdala. Conclusion: The right and left amygdala, right external capsule, and right hemi-cerebellum showed microstructural abnormalities capable of differentiating BD and UD groups. Diffusion imaging especially DKI can aid in management of depression patients. [ABSTRACT FROM AUTHOR]

The diagnosis' treatment planning, follow‐up and prognostication of Gliomas is significantly enhanced on Magnetic Resonance Imaging. In the present research, deep learning‐based variant of convolutional neural network methodology is proposed for glioma segmentation where pretrained autoencoder acts as backbone to the 3D‐Unet which performs the segmentation task as well as image restoration. Further, Unet accepts input as the combination of three non‐native MR images (T2, T1CE, and FLAIR) to extract maximum and superior features for segmenting tumor regions. Further, weighted dice loss employed, focusses on segregating tumor region into three regions of interest namely whole tumor with oedema (WT), enhancing tumor (ET), and tumor core (TC). The optimizer preferred in the proposed methodology is Adam and the learning rate is initially set to 1e−4, progressively reduced by a cosine decay after 50 epochs. The learning parameters are reduced to a larger extent (up to 9.8 M as compared to 27 M). The experimental results show that the proposed model achieved Dice similarity coefficients: 0.77, 0.92, and 0.84; sensitivity: 0.90, 0.95, and 0.89; specificity: 0.97, 0.99, and 0.99; Hausdorff95: 5.74, 4.89, and 6.00, in the three regions including ET, WT, TC. This proposed Glioma segmentation method is efficient for segregation of tumors. Significance: The 3D tumor‐Glioma segmentation is a voxel‐based problem where the tumor is segmented into whole tumor with oedema, enhancing tumor, and tumor core on magnetic resonance images. In the present study, pretrained autoencoder is developed which acts as an anchor for 3D‐Unet for segmenting the tumor boundaries and restoring of an image. Further, during pre‐training, the loss function namely "Mean Squared Error" loss function procured a restored image. The false positive as well as false negative samples during segmentation are obtained due to consideration of improved weighted loss dice function. The learning parameters reduced to a to 9.8 M as compared to 27 M from state of art methods. This resulted in better output visually as well as in terms of other statistical parameters such as Dice similarity coefficient, specificity, sensitivity, and Hausdorff95. [ABSTRACT FROM AUTHOR]