Jayant Narang

814 citations

25 papers · 658 indexed · h-index 13

Impact in

Genetics top 2%
- Glioma Diagnosis and Treatment
Radiology, Nuclear Medicine and Imaging top 2%
- MRI in cancer diagnosis
- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Medical Imaging Techniques and Applications

Papers in ⓘ

Radiology, Nuclear Medicine and Imaging 18
- MRI in cancer diagnosis 12
- Radiomics and Machine Learning in Medical Imaging 7
- Advanced MRI Techniques and Applications 6
- Advanced Neuroimaging Techniques and Applications 4
- Medical Imaging Techniques and Applications 2
Genetics 11
- Glioma Diagnosis and Treatment 10

Co-authors: Rajan Jain (15 shared papers)Tom Mikkelsen (14 shared papers)Lisa Scarpace (10 shared papers)Lonni Schultz (6 shared papers)David Hearshen (3 shared papers)Mark L. Rosenblum (4 shared papers)Sona Saksena (4 shared papers)Ali S. Arbab (3 shared papers)
Journals: Journal of Clinical Oncology (4 papers)Journal of Neuro-Oncology (3 papers)Annals of Oncology (3 papers)American Journal of Neuroradiology (3 papers)Academic Radiology (2 papers)
Partner nations: United States Italy United Kingdom

In The Last Decade

Jayant Narang

20 papers receiving 640 citations

Peers

Countries citing papers authored by Jayant Narang

Since Specialization

Citations

This map shows the geographic impact of Jayant Narang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jayant Narang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jayant Narang more than expected).

Fields of papers citing papers by Jayant Narang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jayant Narang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jayant Narang. The network helps show where Jayant Narang may publish in the future.

Co-authors

The 25 scholars most cited alongside Jayant Narang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jayant Narang Line = papers co-authored together Jayant Narang links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Genomic Mapping and Survival Prediction in Glioblastoma: Molecular Subclassification Strengthened by Hemodynamic Imaging Biomarkers Radiology ·Rajan Jain, Laila Poisson, Jayant Narang, David A. Gutman, Lisa Scarpace, Scott N. Hwang, Chad A. Holder, Max Wintermark, Rivka R. Colen, Justin Kirby, John Freymann, Daniel J. Brat, C. Carl Jaffe, Tom Mikkelsen	2012	114
2	Differentiating treatment-induced necrosis from recurrent/progressive brain tumor using nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion Neuro-Oncology ·Jayant Narang, Rajan Jain, Ali S. Arbab, Tom Mikkelsen, Lisa Scarpace, Mark L. Rosenblum, David Hearshen, Abbas Babajani‐Feremi	2011	96
3	In Vivo Correlation of Tumor Blood Volume and Permeability with Histologic and Molecular Angiogenic Markers in Gliomas American Journal of Neuroradiology ·Rajan Jain, Jorge Gutierrez‐Merino, Jayant Narang, Lisa Scarpace, Lonni Schultz, Nancy Lemke, S.C. Patel, Tom Mikkelsen, J.P. Rock	2010	82
4	Model selection for DCE‐T1 studies in glioblastoma Magnetic Resonance in Medicine ·Hassan Bagher‐Ebadian, Rajan Jain, Siamak P. Nejad‐Davarani, Tom Mikkelsen, Mei Lü, Quan Jiang, Lisa Scarpace, Ali S. Arbab, Jayant Narang, Hamid Soltanian‐Zadeh, Ramesh Paudyal, James R. Ewing	2011	67
5	Predicting survival in glioblastomas using diffusion tensor imaging metrics Journal of Magnetic Resonance Imaging ·Sona Saksena, Rajan Jain, Jayant Narang, Lisa Scarpace, Lonni Schultz, Norman L. Lehman, David Hearshen, Suresh Patel, Tom Mikkelsen	2010	58
6	Treatment induced necrosis versus recurrent/progressing brain tumor: going beyond the boundaries of conventional morphologic imaging Journal of Neuro-Oncology ·Rajan Jain, Jayant Narang, Pia C. Sundgren, David Hearshen, Sona Saksena, Jack Rock, J. Antonio Gutierrez, Tom Mikkelsen	2010	45
7	Correlation of Perfusion Parameters with Genes Related to Angiogenesis Regulation in Glioblastoma: A Feasibility Study American Journal of Neuroradiology ·Rajan Jain, Laila Poisson, Jayant Narang, Lisa Scarpace, M. L. Rosenblum, Sandra A. Rempel, Tom Mikkelsen	2012	42
8	Permeability Estimates in Histopathology-Proved Treatment-Induced Necrosis Using Perfusion CT: Can These Add to Other Perfusion Parameters in Differentiating from Recurrent/Progressive Tumors? American Journal of Neuroradiology ·Rajan Jain, Jayant Narang, L. Schultz, Lisa Scarpace, Sona Saksena, Stephen Brown, Jack Rock, Mark L. Rosenblum, Jorge Gutierrez‐Merino, Tom Mikkelsen	2011	35
9	Morphologic MRI features, diffusion tensor imaging and radiation dosimetric analysis to differentiate pseudo-progression from early tumor progression Journal of Neuro-Oncology ·Ajay Agarwal, Sanath Kumar, Jayant Narang, Lonni Schultz, Tom Mikkelsen, Sumei Wang, S. Siddiqui, Harish Poptani, Rajan Jain	2013	29
10	Tumor vascular leakiness and blood volume estimates in oligodendrogliomas using perfusion CT: an analysis of perfusion parameters helping further characterize genetic subtypes as well as differentiate from astroglial tumors Journal of Neuro-Oncology ·Jayant Narang, Rajan Jain, Lisa Scarpace, Sona Saksena, Lonni Schultz, Jack Rock, Mark L. Rosenblum, Suresh Patel, Tom Mikkelsen	2010	28
11	Prognostic Vascular Imaging Biomarkers in High-Grade Gliomas Academic Radiology ·Rajan Jain, Jayant Narang, Brent Griffith, Hassan Bagher‐Ebadian, Lisa Scarpace, Tom Mikkelsen, Benjamin Littenberg, Lonni Schultz	2013	16
12	Correlation of Immunohistologic and Perfusion Vascular Parameters with MR Contrast Enhancement Using Image-guided Biopsy Specimens in Gliomas Academic Radiology ·Rajan Jain, Jayant Narang, J. Antonio Gutierrez, Lonni Schultz, Lisa Scarpace, Mark L. Rosenblum, Tom Mikkelsen, Jack Rock	2011	14
13	MRI Pre‐ and Post‐Embolization Enhancement Patterns Predict Surgical Outcomes in Intracranial Meningiomas Journal of Neuroimaging ·Rushna Ali, Muhib Khan, Victor Chang, Jayant Narang, Rajan Jain, Horia Marin, Jack Rock, Max Kole	2015	14
14	Blood-Brain-Barrier Imaging in Brain Tumors: Concepts and Methods Neurographics ·Rajan Jain, Brent Griffith, Jayant Narang, Tom Mikkelsen, Hassan Bagher‐Ebadian, Siamak P. Nejad‐Davarani, James R. Ewing, Ali S. Arbab	2012	5
15	Prospective Assessment of Variability and Reproducibility of Diffusion-Weighted MRI and T2-Mapping of the Pancreas in Healthy Volunteers Jaymin Upadhyay, Sev Dolgopolov, Jayant Narang, C. Millet, Rinal Patel, Dinko Gonzalez-Trotter, Edward Ashton	2017	4
16	Meniscal ossicle Indian journal of radiology and imaging - new series/Indian journal of radiology and imaging/Indian Journal of Radiology & Imaging ·MaliniA Lawande, Sidhartha Tavri, DeepakP Patkar, SonaA Pungavkar, Jayant Narang	2008	3
17	To determine correlation of inter reader variability in sum of diameters using RECIST 1.1 with end point assessment in lung cancer. Journal of Clinical Oncology ·Manish Sharma, Anitha Singareddy, Surabhi Bajpai, Jayant Narang, Michael O’Connor, Rudresh Jarecha	2021	2
18	168P Response assessments in hepatocellular carcinoma: What are the best criteria to utilize? mRECIST or RECIST 1.1? A retrospective meta-analysis of multiple phase III trials Annals of Oncology ·Oliver Bohnsack, M. Lesch, Jayant Narang, Surabhi Bajpai, Riccardo Lencioni	2020	1
19	Comparison of response using mRECIST versus RECIST 1.1 Criteria in advanced hepatocellular carcinoma: A retrospective analysis of multicenter clinical trials. Journal of Clinical Oncology ·Jayant Narang, Surabhi Bajpai, Rudresh Jarecha, Manish Sharma, Oliver Bohnsack	2020	1
20	Magnetic resonance estimation of longitudinal relaxation time (T<inf>1</inf>) in spoiled gradient echo using an adaptive neural network Hassan Bagher‐Ebadian, Rajan Jain, Ramesh Paudyal, Siamak P. Nejad‐Davarani, Jayant Narang, Quan Jiang, Tom Mikkelsen, James R. Ewing	2011	1

About Jayant Narang

Jayant Narang is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics, Hepatology, Epidemiology and Pulmonary and Respiratory Medicine, having authored 25 papers that have together received 658 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (12 papers), Glioma Diagnosis and Treatment (10 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Advanced MRI Techniques and Applications (6 papers), Hepatocellular Carcinoma Treatment and Prognosis (5 papers), Advanced Neuroimaging Techniques and Applications (4 papers), Medical Imaging Techniques and Applications (2 papers) and Lymphoma Diagnosis and Treatment (2 papers). The work is most often cited by research in Genetics (450 citations), Radiology, Nuclear Medicine and Imaging (519 citations), Cancer Research (58 citations), Neurology (23 citations) and Pulmonary and Respiratory Medicine (87 citations). Jayant Narang has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Rajan Jain, Tom Mikkelsen, Lisa Scarpace, Lonni Schultz, David Hearshen, Mark L. Rosenblum, Sona Saksena, Ali S. Arbab, Jack Rock and Laila Poisson. Their work appears in journals such as Journal of Clinical Oncology, Journal of Neuro-Oncology, Annals of Oncology, American Journal of Neuroradiology and Academic Radiology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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