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11 citation(s) found for "Jagtap, Jaidip M".

Myocardial Pyruvate Metabolism Before and After CABG in Three-Vessel Disease Using Hyperpolarized Carbon-13 MRI
Sharma, Gaurav , Jagtap, Jaidip, Park, Jae Mo , Harrison, Crystal, Leary, Jennine, McNeil, Sarah, Mozingo, Corey, Malloy, Craig, Peltz, Matthias , Jessen, Michael, Park, Jae Mo , Lin, Sung‐Han , Harrison, Crystal E. , McNeil, Sarah S., Malloy, Craig R.

No container title available | May 13, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-9570351/v1 | PMID 42183355 Get It

Abstract Hyperpolarized [1-¹³C]pyruvate MRI provides real-time, radiation-free insight into myocardial pyruvate metabolism and mitochondrial oxidative capacity, yet its utility in patients with severe multivessel coronary artery disease before and after surgical revascularization remains unknown. Here we show, in the first prospective study applying this technique to three-vessel disease, that serial imaging is feasible and safe with no serious adverse events in 22 injections. Healthy myocardium displayed a bicarbonate-to-total hyperpolarized carbon product ratio of 0.66 ± 0.13, indicating that the majority of pyruvate undergoes oxidation. Patients exhibited significantly lower ratios in the inferolateral segment (P = 0.03) with reciprocal increases in lactate, and global ratios correlated with left ventricular ejection fraction (r = 0.695, P = 0.006). Post-revascularization changes were heterogeneous across individuals. These findings establish hyperpolarized 13C MRI as a powerful tool for noninvasive assessment of myocardial metabolism in multivessel coronary artery disease and support its potential for longitudinal therapeutic monitoring.
Abstract 4365204: HP- 13 CMRAnalyst : A MATLAB Application for Dynamic Cardiac Metabolic Imaging Analysis Usin
Jessen, Michael E. , Sharma, Gaurav , Jagtap, Jaidip , Peltz, Matthias , Malloy, Craig R.

Circulation | November 3, 2025 | Volume: 152 | Issue: Suppl_3 | Pages: No page available

10.1161/circ.152.suppl_3.4365204 Get It

Introduction: Hyperpolarized [1- 13 C] pyruvate magnetic resonance imaging (HP- 13 C MRI) enables real-time, noninvasive assessment of myocardial metabolism. While the technique is increasingly applied in cardiac research, dedicated tools for standardized analysis remain limited. We developed HP- 13 CMRAnalyst , a MATLAB-based application that supports dynamic 13 C data processing through semi-automated segmentation, time-course extraction, and metabolic ratio mapping (Figure 1A). Hypothesis: An integrated platform combining multi-frame 13 C data import, cine co-registration, multi-segment analysis, and voxel-level ratio mapping facilitates reproducible quantification of myocardial metabolism. Methods: HP- 13 CMRAnalyst was implemented in MATLAB App Designer and distributed as an .mlappinstall package. It accepts DICOM or NIfTI dynamic pyruvate, lactate, and bicarbonate images (∼3 s resolution; ≤ 60 s)(Figure 1B). Cine-registered T 1 -weighted images guide AHA 17-segment LV segmentation on short axis (SAX) and long axis (LAX) views (Figure 1C). A time slider displays metabolite overlays. Peak intensities are extracted per segment to compute bicarbonate/lactate and bicarbonate/pyruvate ratios. Pixel-wise ratio maps are exported as CSV, MATLAB struct, and PDF summaries. Results: Eight subjects (n = 4 healthy; n = 4 coronary artery disease [CAD]), each imaged pre- and post-CABG (total n = 12 datasets; age 55 ± 12 years), were processed in < 5 min per dataset on a standard desktop (MATLAB R2024b). Semi-automated versus manual segmentation agreement was high (Dice 0.89–0.93). Inter-observer variability for segmental bicarbonate/(bicarbonate + lactate) ratios were minimal biases < 0.005 and limits of agreement within ± 0.083 across all observer pairs (Figure 1D). Ratio maps qualitatively revealed regional metabolic heterogeneity. Automated reports accurately reflected metadata and segmental summaries. The GUI, logs, and summary files streamline standardized processing. Conclusions: HP- 13 CMRAnalyst delivers a rapid (< 5 min), reproducible framework for dynamic HP- 13 C MRI analysis. By combining semi-automated segmentation and pixel-level ratio mapping with low inter-observer variability, this platform may accelerate adoption of 13 C metabolic imaging in human cardiac research.
Dynamic multispectral NIR/SWIR for in vivo lymphovascular architectural and functional quantification
Hansen, Christopher B. , Sharma, Gayatri , Shafiee, Shayan , Sinha, Sayantan, Himburg, Heather A. , Hansen, Christopher , Parchur, Abdul , Shafiee, Shayan , Sinha, Sayantan , Himburg, Heather , Jagtap, Jaidip , Parchur, Abdul K. , Joshi, Amit

Journal of Biomedical Optics | September 26, 2024 | Volume: 29 | Issue: 10 | Pages: No page available

10.1117/1.jbo.29.10.106001 | PMID 39347012 Get It

A Comparison of Artificial Intelligence (AI) vs. Human-Derived Measures of Nephron Size
Janowczyk, Andrew , Chen, Yijiang , Ramanathan, Sumana, Kline, Timothy L. , Jagtap, Jaidip , Đenić, Aleksandar , Asghar, Muhammad Sohaib , Mullan, Aidan F. , Erickson, Bradley J. , Barisoni, Laura , Rule, Andrew D.

Journal of the American Society of Nephrology | May 17, 2024 | Volume: 34 | Issue: 11S | Pages: 315-315

10.1681/asn.20233411s1315b Get It

Development and Validation of a Multilayer Segmentation Model to Quantify Chronic Changes on Kidney Biopsy
Stetzik, Lucas, Alexander, Mariam P., Janowczyk, Andrew , Asghar, Muhammad Sohaib , Jagtap, Jaidip , Barisoni, Laura , Salem, Fadi E , Smith, Maxwell L. , Mullan, Aidan F. , Đenić, Aleksandar , Rule, Andrew D.

Journal of the American Society of Nephrology | May 17, 2024 | Volume: 34 | Issue: 11S | Pages: 313-313

10.1681/asn.20233411s1313c Get It

X-ray and MR Contrast Bearing Nanoparticles Enhance the Therapeutic Response of Image-Guided Radiation Therapy for Oral Cancer
Sharma, Gayatri , Kondelaji, Mir Hadi Razeghi, Sharma, Guru Prasad , Hansen, Christopher B. , Parchur, Abdul K. , Shafiee, Shayan , Fish, Brian L. , Bergom, Carmen , Paulson, E.S. , Hall, William A. , Himburg, Heather A. , Hansen, Christopher , Jagtap, Jaidip M, Joshi, Amit , Parchur, Abdul , Shafiee, Shayan , Himburg, Heather , Bergom, Carmen , Jagtap, Jaidip , Joshi, Amit

Technology in Cancer Research & Treatment | July 20, 2023 | Volume: 22 | Issue: No issue available | Pages: No page available

10.1177/15330338231189593 | PMID 37469184 Get It

Introduction Radiation therapy for head and neck squamous cell carcinoma is constrained by radiotoxicity to normal tissue. We demonstrate 100 nm theranostic nanoparticles for image-guided radiation therapy planning and enhancement in rat head and neck squamous cell carcinoma models. Methods PEG conjugated theranostic nanoparticles comprising of Au nanorods coated with Gadolinium oxide layers were tested for radiation therapy enhancement in 2D cultures of OSC-19-GFP-luc cells, and orthotopic tongue xenografts in male immunocompromised Salt sensitive or SS rats via both intratumoral and intravenous delivery. The radiation therapy enhancement mechanism was investigated. Results Theranostic nanoparticles demonstrated both X-ray/magnetic resonance contrast in a dose-dependent manner. Magnetic resonance images depicted optimal tumor-to-background uptake at 4 h post injection. Theranostic nanoparticle + Radiation treated rats experienced reduced tumor growth compared to controls, and reduction in lung metastasis. Conclusions Theranostic nanoparticles enable preprocedure radiotherapy planning, as well as enhance radiation treatment efficacy for head and neck tumors.
Dynamic NIR Fluorescence Imaging and Machine Learning Framework for Stratifying High vs. Low Notch-Dll4 Expressing Host Microenvironment in Triple-Negative Breast Cancer
Shafiee, Shayan , Jagtap, Jaidip , Zayats, Mykhaylo , Epperlein, Jonathan P. , Banerjee, Anjishnu , Geurts, Aron M. , Flister, Michael J. , Zhuk, Sergiy , Epperlein, Jonathan , Shafiee, Shayan , Banerjee, Anjishnu , Joshi, Amit

Cancers | February 27, 2023 | Volume: 15 | Issue: 5 | Pages: 1460

10.3390/cancers15051460 | PMID 36900252 Get It

Delta like canonical notch ligand 4 (Dll4) expression levels in tumors are known to affect the efficacy of cancer therapies. This study aimed to develop a model to predict Dll4 expression levels in tumors using dynamic enhanced near-infrared (NIR) imaging with indocyanine green (ICG). Two rat-based consomic xenograft (CXM) strains of breast cancer with different Dll4 expression levels and eight congenic xenograft strains were studied. Principal component analysis (PCA) was used to visualize and segment tumors, and modified PCA techniques identified and analyzed tumor and normal regions of interest (ROIs). The average NIR intensity for each ROI was calculated from pixel brightness at each time interval, yielding easily interpretable features including the slope of initial ICG uptake, time to peak perfusion, and rate of ICG intensity change after reaching half-maximum intensity. Machine learning algorithms were applied to select discriminative features for classification, and model performance was evaluated with a confusion matrix, receiver operating characteristic curve, and area under the curve. The selected machine learning methods accurately identified host Dll4 expression alterations with sensitivity and specificity above 90%. This may enable stratification of patients for Dll4 targeted therapies. NIR imaging with ICG can noninvasively assess Dll4 expression levels in tumors and aid in effective decision making for cancer therapy.
Betti-Number Based Machine-Learning Classifier Frame-work for Predicting the Hepatic Decompensation in Patients with Primary Sclerosing Cholangitis
Singh, Yashbir , Jons, William , Sobek, Joseph D. , Eaton, John E. , Anderies, Barrett J. , Jagtap, Jaidip , Singh, Yashbir , Erickson, Bradley J.

2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC) | March 4, 2022 | Volume: No volume available | Issue: No issue available | Pages: 0159-0162

10.1109/ccwc54503.2022.9720887 Get It