Publications by authors named "Lalit M Aggarwal"

5 Publications

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A comparison of six fractions per week chemoradiation versus five fractions per week of conventional chemoradiation in carcinoma cervix: A prospective controlled study.

J Cancer Res Ther 2019 Oct-Dec;15(6):1296-1303

Department of Radiotherapy and Radiation Medicine, Banaras Hindu University, Varanasi, Uttar Pradesh, India.

Aims: The standard of care for carcinoma cervix stage IB2-IVA is five fractions per week of radiotherapy (RT) with concurrent cisplatin. We compared the standard treatment with six fractions per week of RT with concurrent Cisplatin to see whether the later had improved survival outcomes with comparable toxicities.

Settings And Design: 46 patients of carcinoma cervix with stage IB2-IVAwere randomized into two arms.

Materials And Methods: Study arm: 46 Gy/23 fractions/26 days, 6 fractions/week with injection CDDP 40 mg/m and Control arm: 46 Gy/23 fractions/31 days, 5 fractions/week with injection Cisplatin 40mg/m. Patients in both the arms received LDR brachytherapy to a dose of 29 Gy at point A.

Statistical Analysis Used: The primary end points were disease-free survival (DFS) and overall survival (OS). Compliance to treatment and treatment toxicities were the secondary end points. P value ≤0.05 were considered significant.

Results: The study was carried out during June, 2014-April, 2015. Statistical analysis was done in May, 2019. Of 46 patients, 39 patients completed the treatment. The study and control arms had 17 and 22 patients, respectively. Median follow-up period is 45 months (range: 1-54 months). 3-year DFS rates and OS was 69.5% vs. 72.7% (P = 0.73) and 63% vs. 68% (P = 0.45) in study and in control arm, respectively. There was no significant difference in acute and late radiation toxicities between two arms.

Conclusion: Chemoradiotherapy with six fractions per week seems feasible and equally efficacious in terms of survival outcomes and toxicity profile. Further prospective randomized controlled study is required to prove the merit of altered fractionation with concurrent cisplatin.
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http://dx.doi.org/10.4103/jcrt.JCRT_698_19DOI Listing
May 2020

Design and development of novel p-aminobenzoic acid derivatives as potential cholinesterase inhibitors for the treatment of Alzheimer's disease.

Bioorg Chem 2019 02 9;82:211-223. Epub 2018 Oct 9.

Stanley S. Scott Cancer Center, Louisiana State University Health Sciences Center, 1700 Tulane Avenue, New Orleans, LA 70112, USA.

Based on the quantitative structure-activity relationship (QSAR), some novel p-aminobenzoic acid derivatives as promising cholinesterase enzyme inhibitors were designed, synthesized, characterized and evaluated to enhance learning and memory. The in vitro enzyme kinetic study of the synthesized compounds revealed the type of inhibition on the respective acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. The in vivo studies of the synthesized compounds exhibited significant reversal of cognitive deficits in the animal models of amnesia as compared to standard drug donepezil. Further, the ex vivo studies in the specific brain regions like the hippocampus, hypothalamus, and prefrontal cortex regions also exhibited AChE inhibition comparable to standard donepezil. The in silico molecular docking and dynamics simulations studies of the most potent compound 22 revealed the consensual interactions at the active site pocket of the AChE.
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http://dx.doi.org/10.1016/j.bioorg.2018.10.009DOI Listing
February 2019

Polylactide-co-glycolide nanoparticles of antitubercular drugs: formulation, characterization and biodistribution studies.

Ther Deliv 2014 Dec;5(12):1247-59

Department of Pharmaceutics, Indian Institute of Technology, Banaras Hindu University, Varanasi, UP 221 005, India.

Background: The present study was designed to prepare and characterize poly lactide-co-glycolide nanoparticles of antitubercular drugs (ATDs) for delivery through oral route to alveolar macrophages.

Methods: Nanoparticles were prepared by double emulsification solvent evaporation method. Ex vivo and in vivo drug accumulation studies were performed in alveolar macrophages, harvested by broncheoalveolar lavaging. Internalization of nanoparticles was studied by confocal laser scanning microscopy. γ-scintigraphy imaging using technetium-99m was done to study the biodistribution pattern of nanoparticles.

Results: High intracellular concentrations of ATDs were observed in macrophages within 30 min of administration of nanoparticles. Intense radioactivity recorded in liver, spleen and lungs revealed uptake of nanoparticles in macrophages, abundantly present in mononuclear phagocyte system present in these organs.

Conclusion: Targeted delivery of ATDs will help reduce dose and associated side effects including hepatotoxicity of ATDs. Further studies are required to assess the potential therapeutic advantages for treatment of TB.
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http://dx.doi.org/10.4155/tde.14.88DOI Listing
December 2014

Automated medical image segmentation techniques.

J Med Phys 2010 Jan;35(1):3-14

School of Biomedical Engineering, Institute of Technology, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221 005, UP, India.

Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.
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http://dx.doi.org/10.4103/0971-6203.58777DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2825001PMC
January 2010

Segmentation and classification of medical images using texture-primitive features: Application of BAM-type artificial neural network.

J Med Phys 2008 Jul;33(3):119-26

School of Biomedical Engineering, Institute of Technology, Banaras Hindu University, Varanasi (UP), India.

The objective of developing this software is to achieve auto-segmentation and tissue characterization. Therefore, the present algorithm has been designed and developed for analysis of medical images based on hybridization of syntactic and statistical approaches, using artificial neural network (ANN). This algorithm performs segmentation and classification as is done in human vision system, which recognizes objects; perceives depth; identifies different textures, curved surfaces, or a surface inclination by texture information and brightness. The analysis of medical image is directly based on four steps: 1) image filtering, 2) segmentation, 3) feature extraction, and 4) analysis of extracted features by pattern recognition system or classifier. In this paper, an attempt has been made to present an approach for soft tissue characterization utilizing texture-primitive features with ANN as segmentation and classifier tool. The present approach directly combines second, third, and fourth steps into one algorithm. This is a semisupervised approach in which supervision is involved only at the level of defining texture-primitive cell; afterwards, algorithm itself scans the whole image and performs the segmentation and classification in unsupervised mode. The algorithm was first tested on Markov textures, and the success rate achieved in classification was 100%; further, the algorithm was able to give results on the test images impregnated with distorted Markov texture cell. In addition to this, the output also indicated the level of distortion in distorted Markov texture cell as compared to standard Markov texture cell. Finally, algorithm was applied to selected medical images for segmentation and classification. Results were in agreement with those with manual segmentation and were clinically correlated.
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http://dx.doi.org/10.4103/0971-6203.42763DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2772042PMC
July 2008