Prashant Nagpal

1.8k total citations
92 papers, 921 citations indexed

About

Prashant Nagpal is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Prashant Nagpal has authored 92 papers receiving a total of 921 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Radiology, Nuclear Medicine and Imaging, 34 papers in Pulmonary and Respiratory Medicine and 26 papers in Surgery. Recurrent topics in Prashant Nagpal's work include Cardiac Imaging and Diagnostics (20 papers), Advanced X-ray and CT Imaging (15 papers) and Radiation Dose and Imaging (14 papers). Prashant Nagpal is often cited by papers focused on Cardiac Imaging and Diagnostics (20 papers), Advanced X-ray and CT Imaging (15 papers) and Radiation Dose and Imaging (14 papers). Prashant Nagpal collaborates with scholars based in United States, Canada and India. Prashant Nagpal's co-authors include Ashish Khandelwal, Sarv Priya, Michael L. Steigner, Sachin S. Saboo, Girish Bathla, Eric A. Hoffman, Arun Sharma, Richard Thomas, Mathews Jacob and Junfeng Guo and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.

In The Last Decade

Prashant Nagpal

87 papers receiving 901 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Prashant Nagpal United States 18 393 313 281 156 142 92 921
Christine P. Chao United States 8 251 0.6× 246 0.8× 285 1.0× 112 0.7× 63 0.4× 11 762
Thomas Song United States 15 204 0.5× 183 0.6× 456 1.6× 427 2.7× 189 1.3× 31 997
Gaetano Rea Italy 18 632 1.6× 218 0.7× 131 0.5× 210 1.3× 113 0.8× 105 997
Ki Yeol Lee South Korea 18 279 0.7× 372 1.2× 247 0.9× 103 0.7× 79 0.6× 62 915
Katharina Otani Japan 16 282 0.7× 134 0.4× 446 1.6× 121 0.8× 68 0.5× 61 909
Arlene Sirajuddin United States 21 338 0.9× 167 0.5× 549 2.0× 474 3.0× 154 1.1× 71 1.4k
Tom Routledge United Kingdom 20 827 2.1× 399 1.3× 122 0.4× 109 0.7× 89 0.6× 67 1.1k
Farid Gharagozloo United States 20 913 2.3× 784 2.5× 161 0.6× 135 0.9× 141 1.0× 100 1.4k
Michael A. Bolen United States 23 330 0.8× 374 1.2× 504 1.8× 850 5.4× 423 3.0× 80 1.3k
Sun Ho Ahn United States 16 199 0.5× 301 1.0× 95 0.3× 49 0.3× 114 0.8× 48 686

Countries citing papers authored by Prashant Nagpal

Since Specialization
Citations

This map shows the geographic impact of Prashant Nagpal'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 Prashant Nagpal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prashant Nagpal more than expected).

Fields of papers citing papers by Prashant Nagpal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Prashant Nagpal. 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 Prashant Nagpal. The network helps show where Prashant Nagpal may publish in the future.

Co-authorship network of co-authors of Prashant Nagpal

This figure shows the co-authorship network connecting the top 25 collaborators of Prashant Nagpal. A scholar is included among the top collaborators of Prashant Nagpal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Prashant Nagpal. Prashant Nagpal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Heidenreich, Julius F., Jan‐Peter Grunz, Jitka Starekova, et al.. (2025). Gadopiclenol Enables Reduced Gadolinium Dose While Maintaining Quality of Pulmonary Arterial Enhancement for Pulmonary MRA. Investigative Radiology. 60(12). 823–830. 2 indexed citations
2.
Starekova, Jitka, Thomas M. Grist, Mark L. Schiebler, et al.. (2025). Accelerated deep-learning reconstructed cine balanced steady-state free precession cine imaging: Potential for workflow improvement.. Journal of Cardiovascular Magnetic Resonance. 27. 101590–101590. 2 indexed citations
3.
Garg, Ishan, Thomas M. Grist, & Prashant Nagpal. (2023). MR Angiography for Aortic Diseases. Magnetic Resonance Imaging Clinics of North America. 31(3). 373–394. 5 indexed citations
4.
Priya, Sarv, et al.. (2023). Optimizing Deep Learning for Cardiac MRI Segmentation: The Impact of Automated Slice Range Classification. Academic Radiology. 31(2). 503–513. 3 indexed citations
5.
6.
Priya, Sarv, et al.. (2023). ComBat Harmonization of Myocardial Radiomic Features Sensitive to Cardiac MRI Acquisition Parameters. Radiology Cardiothoracic Imaging. 5(4). e220312–e220312. 7 indexed citations
7.
Hoffman, Eric A., Norrina B. Allen, Alain G. Bertoni, et al.. (2022). Pulmonary Blood Volume Among Older Adults in the Community: The MESA Lung Study. Circulation Cardiovascular Imaging. 15(8). e014380–e014380. 9 indexed citations
8.
Zou, Qing, et al.. (2022). Variational Manifold Learning From Incomplete Data: Application to Multislice Dynamic MRI. IEEE Transactions on Medical Imaging. 41(12). 3552–3561. 7 indexed citations
9.
Nagpal, Prashant, Junfeng Guo, Alejandro A. Pezzulo, et al.. (2022). Quantitative Chest CT Assessment of Small Airways Disease in Post-Acute SARS-CoV-2 Infection. Radiology. 304(1). 185–192. 62 indexed citations
10.
Garg, Ishan, Ankita Garg, Archana Laroia, et al.. (2022). E-cigarette or vaping product use–associated lung injury: A review of clinico-radio-pathological characteristics. Respiratory Investigation. 60(6). 738–749. 3 indexed citations
11.
Nagpal, Prashant, et al.. (2021). Left ventricular assist device pseudo-thrombosis due to use of metal artifact reduction algorithm on cardiac CT. Journal of cardiovascular computed tomography. 16(1). e1–e2. 1 indexed citations
12.
Zou, Qing, et al.. (2021). Dynamic Imaging Using a Deep Generative SToRM (Gen-SToRM) Model. IEEE Transactions on Medical Imaging. 40(11). 3102–3112. 29 indexed citations
13.
Priya, Sarv, Tanya Aggarwal, Caitlin Ward, et al.. (2021). Radiomics Detection of Pulmonary Hypertension via Texture-Based Assessments of Cardiac MRI: A Machine-Learning Model Comparison—Cardiac MRI Radiomics in Pulmonary Hypertension. Journal of Clinical Medicine. 10(9). 1921–1921. 9 indexed citations
14.
Nagpal, Prashant, Sabarish Narayanasamy, Junfeng Guo, et al.. (2020). Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances. British Journal of Radiology. 93(1113). 20200538–20200538. 34 indexed citations
15.
16.
Priya, Sarv, et al.. (2020). Pulmonary embolism rule out: positivity and factors affecting the yield of CT angiography. Postgraduate Medical Journal. 96(1140). 594–599. 9 indexed citations
17.
Bathla, Girish, et al.. (2017). Cerebrovascular Manifestations of Neurosarcoidosis: An Underrecognized Aspect of the Imaging Spectrum. American Journal of Neuroradiology. 39(7). 1194–1200. 37 indexed citations
18.
Nagpal, Prashant, Bruno Policeni, Girish Bathla, et al.. (2017). Blunt Cerebrovascular Injuries: Advances in Screening, Imaging, and Management Trends. American Journal of Neuroradiology. 39(3). 406–414. 42 indexed citations
19.
Nagpal, Prashant, Brian F. Mullan, Indrani Sen, Sachin S. Saboo, & Ashish Khandelwal. (2017). Advances in Imaging and Management Trends of Traumatic Aortic Injuries. CardioVascular and Interventional Radiology. 40(5). 643–654. 19 indexed citations
20.

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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