Browsing by Author "Anil Kumar Maurya"

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A new method to correct the attenuation map in simultaneous transmission/emission tomography using 153Gd/ 67Ga radioisotopes
(2012) Subhash Chand Kheruka; Brian F. Hutton; Umesh Chand Naithani; Lalit Mohan Aggarwal; Nirmal Kumar Painuly; Anil Kumar Maurya; Sanjay Gambhir
Reconstruction of the tomographic images without attenuation correction can cause erroneously high count densities and reduced image contrast in low attenuation regions. In order to solve the problem of photon attenuation, one needs to know the attenuation coefficient for the individual patient being studied. Therefore, we made an attempt to correct the attenuation map in simultaneous transmission/emission tomography with 153Gd/ 67Ga using maximum likelihood method using the expectation maximization (ML-EM) algorithm to correct the transmission window for both the spillover and downscatter. Spillover fraction, scatter fraction and parameters for the scatter function (A, b and c) were determined experimentally and optimized using the optimization program written in IDL based on simplex theory. All measurements were performed on a Vertex gamma camera using the anthropomorphic thorax phantom for validation of data obtained by the proposed method. It was observed that without spillover and downscatter correction, the mean counts were 19.29 in liver and 26.90 in lung, whereas after after applying the corrections, the mean counts were reduced to 3.80 and 15.10 in liver and lung, respectively, which were close to true mean counts (liver 2.15 and lung 14.89). In this proposed method, we introduced the set of F t (spillover) and K t (downscatter) to account for the variations in projection pixels (f t and k t) with the density and thickness. The F t and K t were determined using the transmission data by an iterative process. The quantitative error was reduced by 98.0% for lung and 90.0% for liver when the corrected transmission images were obtained after the subtraction of spillover and downscatter fraction.
An investigation of a sinogram discontinuity artifact on myocardial perfusion imaging
(2012) Subhash Chand Kheruka; Umesh Chand Naithani; Lalit Mohan Aggarwal; Nirmal Kumar Painuly; Anil Kumar Maurya; Sanjay Gambhir
Our purpose was to find out the cause of an unusual distinct break seen on a patient's sinogram despite within-tolerance results on all quality assurance tests during myocardial perfusion imaging (MPI) and corrective measures. Methods: SPECT quality control is a prerequisite to obtaining high-quality diagnostic images. Daily uniformity and energy-peaking tests and weekly center-of-rotation (COR) tests are run to check the performance of the SPECT system. A distinct break in the sinogram of an MPI study was noticed for 1 patient, despite routine quality control tests that showed the system to be well within tolerance limits. Critical inspection of the g-camera revealed that the 2 detector heads did not make complete contact with each other at a 90° position and that a gap of as much as 10.0 mm was left between the 2 edges of the detectors even though COR testing showed the system to be within tolerance limits. After this gap had been minimized (210-mm position), the MPI study of this patient was repeated. Results: Reduction of the gap between detectors corrected the sinogram discontinuity. On the MPI study, the break in the sinogram existed because the 2 detectors were not acquiring the data at the same position in their useful fields of view. When one of the detectors was tilted to exactly 45°, the gap was reduced and the data were acquired at the same useful field of view for both detectors. Conclusion: The sinogram artifact may arise even after perfect COR calibration, and in the reported case, the discontinuity in the sinogram was rectified by correcting the angle of the detectors. Meticulous investigation for artifacts must be performed to minimize the probability of false results. © 2012 by the Society of Nuclear Medicine, Inc.
Assessment of depression anxiety and stress levels among patients with epilepsy in a case control study
(Discover, 2025) Shani Vishwakarma; Abhishek Pathak; Anil Kumar Maurya; Nitish Kumar Singh; Ashish Ashish; Royana Singh
Introduction: People with epilepsy frequently experience depression, anxiety, and stress, which can significantly impact their quality of life and overall well-being. This study aimed to identify psychiatric comorbidities in individuals with epilepsy by assessing their prevalence and comparing them with a healthy control group. Methodology: This case-control study was conducted in the department of Anatomy, and patients were recruited from the Out-Patient Department of Neurology, from August 2022 to February 2024. The total number of participants was 388, including 194 Cases. 194 healthy controls were matched for age and sex, with participants under the age of 18 excluded. Psychiatric comorbidity was evaluated using standardized assessment tools and analyzed with Chi-square and one-way ANOVA. Results: The study involved 194 patients and 194 healthy controls, with a mean age of 25.11 ± 10.28 years. Among the patients, 58.2% were female and 41.8% were male. A significant difference in depression levels was found between patients on monotherapy and polytherapy (p = 0.003). However, no significant differences were found in anxiety (p = 0.214) and stress (p = 0.139). There are no significant links between depression, anxiety, stress and antiepileptic drugs. Patients with epilepsy exhibited significantly higher levels of depression, anxiety, and stress compared to healthy controls, with a statistical significance of p = 0.001. Conclusion: The study highlights the elevated levels of depression, anxiety, and stress among patients with epilepsy. Clinicians and healthcare practitioners should adopt comprehensive and holistic assessment methods to address and mitigate these psychiatric comorbidities in epilepsy patients. © The Author(s) 2025.
Body Composition Analysis Techniques and Its Application in Oncology: A Review
(Taylor and Francis Ltd., 2024) Anil Kumar Maurya; Lalit Mohan Aggarwal; Sunil Choudhary
The oncology community has shown growing interest to understand how body composition measures can be utilized to improve cancer treatment and survivorship care for about 20 million individuals diagnosed with cancer annually. Recent observational studies demonstrate that muscle and adipose tissue distribution are risk factors for clinical outcomes such as postoperative complications, and worse overall survival. There is an emergent recognition that body mass index (BMI) is neither adequate to identify patients with adverse health outcomes due to poor muscle health or excess adiposity, nor does BMI accurately classify the distribution of adiposity. Abdominal CT is a most frequently imaging examination for a wide variety of clinical indications, but it is only used to diagnose the immediate problem. Additionally, each CT examination contains very robust data on body composition which generally goes unused in routine clinical practice. The field is eager to identify therapeutic interventions that modify body composition and reduce the incidence of poor clinical outcomes in this population. Large scale population based screening is feasible now by making all of these relevant biometric measures fully automated through the use of artificial intelligence algorithms, which provide rapid and objective assessment. © 2024 Taylor & Francis Group, LLC.
Cytokine profiles and metabolic dysregulation in endometriosis: insights into diagnostic and therapeutic targets
(Springer Science and Business Media B.V., 2025) Ashish Ashish; Sangeeta Rai; Shivani Mishra; Anil Kumar Maurya; Abhay Kumar Yadav; Shani Vishwakarma; Royana Singh
Introduction: Endometriosis is a chronic inflammatory disorder marked by the ectopic growth of endometrial-like tissue, affecting 10–15% of women of reproductive age. Pro-inflammatory cytokines (TNF-α, IL-1β, IL-6) drive inflammation and disease progression, while anti-inflammatory cytokines (TGF-β, IL-10) maintain immune balance. Metabolic markers like homocysteine, folic acid, and vitamin B12 may influence immune regulation and contribute to endometriosis pathophysiology. Methodology: Serum levels of TNF-α, IL-1β, IL-6, IL-10, TGF-β, CRP, Ferritin, IL-4, IFN-γ, Homocysteine, Folic Acid, and Vitamin B12 were quantified using ELISA kits. Unpaired t-tests and Pearson correlation were used to assess immune-metabolic differences between endometriosis patients and healthy controls. Results: TNFα, IL-6, IL-1β, IL-10, homocysteine, ferritin, and reduced IFN-γ and CRP levels in the case group compared to controls (p < 0.05). TNFα (p = 0.0008), IL-1β (p = 0.0005), and homocysteine (p < 0.0001) were notably higher in cases. IFN-γ (p < 0.0001) and CRP (p < 0.0001) were significantly lower in cases. IL-6 (p = 0.0020), IL-10 (p = 0.0051), ferritin (p = 0.0338), and folate (p = 0.0134) also showed significant differences. TGF-β, IL-4, and Vit-B12 levels did not differ significantly (p > 0.05). These findings suggest altered cytokine and biochemical profiles in disease pathophysiology. Conclusion: The study highlights significant alterations in inflammatory cytokines and metabolic markers in endometriosis patients compared to healthy controls. Elevated pro-inflammatory and altered anti-inflammatory cytokine levels, along with metabolic imbalance, suggest immune-metabolic dysregulation in disease pathogenesis. These findings may aid in identifying potential biomarkers and therapeutic targets for endometriosis. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
Evaluation of single-photon emission computed tomography images obtained with and without copper filter by segmentation
(Medknow Publications, 2016) Subhash Chand Kheruka; Lalit Mohan Aggarwal; Neeraj Sharma; Umesh Chand Naithani; Anil Kumar Maurya; Sanjay Gambhir
Background: Measurement of accurate attenuation of photon flux in tissue is important to obtain reconstructed images using single-photon emission computed tomography (SPECT). Computed tomography (CT) scanner provides attenuation correction data for SPECT as well as anatomic information for diagnostic purposes. Segmentation is a process of dividing an image into regions having similar properties such as gray level, color, texture, brightness, and contrast. Image segmentation is an important tool for evaluation of medical images. X-ray beam used in CT scan is poly-energetic; therefore, we have used a copper filter to remove the low energy X-rays for obtaining correct attenuation factor. Images obtained with and without filters were quantitatively evaluated by segmentation method to avoid human error. Materials and Methods: Axial images of AAPM CT phantom were acquired with 3 mm copper filter (low intensity) and without copper filter (high intensity) using low-dose CT (140 kvp and 2.5 mA) of SPECT/CT system (Hawkeye, GE Healthcare). For segmentation Simulated Annealing Based Fuzzy c-means, algorithm is applied. Quantitative measurement of quality is done based on universal image quality index. Further, for the validation of attenuation correction map of filtered CT images, Jaszczak SPECT phantom was filled with 500 MBq of 99m Tc and SPECT study was acquired. Low dose CT images were acquired for attenuation correction to be used for reconstruction of SPECT images. Another set of CT images were acquired after applying additional 3 mm copper filter. Two sets of axial SPECT images were reconstructed using attenuation map from both the CT images obtained without and with a filter. Results and Conclusions: When we applied Simulated Annealing Based Fuzzy c-means segmentation on both the CT images, the CT images with filter shows remarkable improvement and all the six section of the spheres in the Jaszczak SPECT phantom were clearly visualized.
Exploring the multifaceted links between comorbidities and cognitive aging
(Elsevier, 2025) Ashish Ashish; Nitish Kumar Singh; Anil Kumar Maurya; Shivani Mishra; Royana Singh
Cognitive aging is a multifactorial process influenced by various physiological, psychological, pathological, and genetic factors. Comorbidities such as cardiovascular diseases, diabetes, hypertension, depression, drug addiction, family, and social environment, which are prevalent in the elderly population, have been implicated in accelerating cognitive decline. Understanding these associations is crucial for developing targeted interventions. This chapter provides a thorough review of existing literature, synthesizing data from gerontology, neurology, and psychiatry to examine the impact of comorbidities on cognitive functions. The findings highlight that cardiovascular diseases and diabetes are strongly associated with an increased risk of cognitive impairment and dementia. Hypertension contributes to vascular dementia through mechanisms involving reduced cerebral blood flow and white matter lesions. Depression, both a risk factor and a consequence of cognitive decline, is linked to shared pathophysiological pathways such as chronic inflammation and neuroendocrine dysregulation. The chapter emphasizes the bidirectional nature of these relationships, underscoring the need for holistic approaches in managing comorbidities to mitigate their impact on cognitive health. Potential mechanisms, including oxidative stress, inflammation, and vascular changes, are explored, and the role of genetic predispositions and lifestyle factors in moderating these effects is considered. Addressing comorbid conditions through integrated healthcare strategies is essential for preserving cognitive functions in aging populations. Future research should focus on personalized medicine approaches and the exploration of novel therapeutic targets to prevent or delay cognitive decline. However, the chapter’s limitations include the lack of standardized methodologies across studies and the need for further exploration into the molecular mechanisms involved. © 2026 Elsevier Inc. All rights reserved..
Trace elements and cognitions in elderly population: a case–control study
(Springer Science and Business Media B.V., 2025) Anil Kumar Maurya; Mona Srivastava; Ashish Ashish; Nitish Kumar Singh; Abhay Kumar Yadav; Shani Vishwakarma; Royana Singh
There have been almost no studies with trace elements and psychological battery in cognitively impaired elderly individuals. Such research is crucial to enhance diagnostic accuracy. We aim to identify significant differences in blood serum concentration levels of trace elements, Hindi Mini-Mental State Examination (HMMSE), and psychological battery as Hindi Mattis Dementia Rating Scale (HMDRS) scores between case and control groups in the elderly. A cross-sectional research design was conducted with a total of 240 subjects, comprising 120 each from the case and control groups. Trace elements were analyzed using Atomic Absorption Spectrometry. HMMSE and HMDRS tests were administered to assess cognition scores. The chi-square test, t-test, and appropriate statistics were utilized. Our findings indicate significant differences in demographic factors (age, gender, education level) and clinical levels (p <.001), while caste, habitat, and marital status were not significant (p <.05). Concentration levels of Iron (Fe) and Copper (Cu) was higher, Zinc (Zn), Chromium (Cr), and Selenium (Se) were lower, significantly different (p <.001), but Magnesium (Mg) was not (p <.05). Additionally, third HMMSE and HMDRS were significant (p <.001) between the case and control groups in the elderly. The study suggested that higher levels of Fe and Cu, while lower Zn, Cr, and Se blood serum concentrations increased the risk of cognitive impairments in the elderly population, demonstrated by the HMMSE and HMDRS test scores which were lower in the case group. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
Unveiling the role of trace elements in modulating inflammatory and oxidative pathways in CAG repeat–driven spinocerebellar ataxia
(Academic Press, 2025) Surbhi Singh; Deepika Srivastava Joshi; Abhay Kumar Yadav; Shani Vishwakarma; Janki Makani; Janhavi Yadav; Anil Kumar Maurya; Gulabi Yadav; Chandmayee Mohanty; Anand Kumar; Royana Singh
Spinocerebellar ataxias are genetically inherited neurodegenerative disorders, primarily caused by CAG trinucleotide repeat expansions in genes. While these genetic mutations initiate disease onset, increasing evidence suggests that systemic factors, particularly trace element imbalance, oxidative stress, and immune dysregulation, play critical roles in disease progression. In this study, peripheral blood samples from genetically confirmed SCA patients (n = 15) and age- and sex-matched healthy controls (n = 18) were analyzed. Atomic Absorption Spectroscopy revealed significant alterations in plasma concentrations of both essential and toxic trace elements, suggesting their involvement in neurotoxicity, redox imbalance, and inflammation. To explore these links, oxidative stress markers, including malondialdehyde, superoxide dismutase, and glutathione peroxidase, as well as cytokines such as interleukin-6, interleukin-4, and interleukin-10, were quantified using ELISA. Receiver operating characteristic analysis demonstrated high diagnostic accuracy of these markers, particularly GPx and IL-10. A strong interconnection was observed among trace element dysregulation, oxidative stress, and inflammatory responses, indicating a synergistic role in exacerbating neurodegeneration. Molecular docking revealed that abnormal trace element levels may impair antioxidant enzyme function by disrupting metal-binding interactions, offering mechanistic insight into enzymatic dysfunction. Bioinformatics analyses, including functional enrichment and protein–protein interaction mapping, identified significant associations with mitochondrial dysfunction, reactive oxygen species metabolism, and cytokine signaling pathways. These findings suggest that SCA pathogenesis is not driven by genetic mutation alone. The combined effects of trace element imbalance, oxidative stress, and inflammation contribute to a complex pathogenic network, reinforcing the importance of targeting both genetic and systemic factors in therapeutic strategies. © 2025 Elsevier Ltd