Melissa Prah

936 total citations
26 papers, 540 citations indexed

About

Melissa Prah is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Cancer Research. According to data from OpenAlex, Melissa Prah has authored 26 papers receiving a total of 540 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Genetics and 4 papers in Cancer Research. Recurrent topics in Melissa Prah's work include Glioma Diagnosis and Treatment (17 papers), MRI in cancer diagnosis (15 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Melissa Prah is often cited by papers focused on Glioma Diagnosis and Treatment (17 papers), MRI in cancer diagnosis (15 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Melissa Prah collaborates with scholars based in United States, Bulgaria and Belarus. Melissa Prah's co-authors include Kathleen M. Schmainda, Jennifer Connelly, Daniel P. Barboriak, Wade M. Mueller, Scott D. Rand, Mark G. Malkin, A. Gregory Sorensen, Jerrold L. Boxerman, Bradley S. Snyder and Raymond G. Hoffman and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Melissa Prah

24 papers receiving 537 citations

Peers

Melissa Prah
Jayant Narang United States
Theresa Kumar Norway
Elena K. Bauer Germany
Sophie Chheang United States
Taryar Zaw United States
Bart R. J. van Dijken Netherlands
Llewellyn E. Jalbert United States
Anne Baldock United States
Ginu Thomas United States
Vladimir Petrik United Kingdom
Jayant Narang United States
Melissa Prah
Citations per year, relative to Melissa Prah Melissa Prah (= 1×) peers Jayant Narang

Countries citing papers authored by Melissa Prah

Since Specialization
Citations

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

Fields of papers citing papers by Melissa Prah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Melissa Prah

This figure shows the co-authorship network connecting the top 25 collaborators of Melissa Prah. A scholar is included among the top collaborators of Melissa Prah 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 Melissa Prah. Melissa Prah 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.
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Stokes, Ashley M., John P. Karis, Laura C. Bell, et al.. (2024). Identification of a Single-Dose, Low-Flip-Angle–Based CBV Threshold for Fractional Tumor Burden Mapping in Recurrent Glioblastoma. American Journal of Neuroradiology. 45(10). 1545–1551.
3.
Al-Gizawiy, Mona, Melissa Prah, Ninh Doan, et al.. (2024). Potent in vivo efficacy of oral gallium maltolate in treatment-resistant glioblastoma. Frontiers in Oncology. 13. 1278157–1278157. 4 indexed citations
4.
Prah, Melissa & Kathleen M. Schmainda. (2024). Practical guidance to identify and troubleshoot suboptimal DSC-MRI results. SHILAP Revista de lepidopterología. 4. 1307586–1307586. 2 indexed citations
5.
Schmainda, Kathleen M., et al.. (2023). IMG-10. MAGNETIC RESONANCE FUNCTIONAL IMAGING BIOMARKER FOR DISTINGUISHING HIGH GRADE FROM LOW GRADE PEDIATRIC BRAIN TUMORS. Neuro-Oncology. 25(Supplement_1). i48–i49.
6.
Straza, Michael, Melissa Prah, Wade M. Mueller, et al.. (2022). Case report: Fractional brain tumor burden magnetic resonance mapping to assess response to pulsed low-dose-rate radiotherapy in newly-diagnosed glioblastoma. Frontiers in Oncology. 12. 1066191–1066191. 3 indexed citations
7.
Connelly, Jennifer, et al.. (2021). Magnetic Resonance Imaging Mapping of Brain Tumor Burden: Clinical Implications for Neurosurgical Management: Case Report. PubMed. 2(4). okab029–okab029. 7 indexed citations
8.
Bovi, Joseph, Melissa Prah, Kathleen M. Schmainda, et al.. (2020). Pulsed Reduced Dose Rate Radiotherapy in Conjunction With Bevacizumab or Bevacizumab Alone in Recurrent High-grade Glioma: Survival Outcomes. International Journal of Radiation Oncology*Biology*Physics. 108(4). 979–986. 18 indexed citations
9.
Schmainda, Kathleen M., Melissa Prah, Leland Hu, et al.. (2019). Moving Toward a Consensus DSC-MRI Protocol: Validation of a Low–Flip Angle Single-Dose Option as a Reference Standard for Brain Tumors. American Journal of Neuroradiology. 40(4). 626–633. 27 indexed citations
10.
Ratai, Eva‐Maria, Zheng Zhang, James R. Fink, et al.. (2018). ACRIN 6684: Multicenter, phase II assessment of tumor hypoxia in newly diagnosed glioblastoma using magnetic resonance spectroscopy. PLoS ONE. 13(6). e0198548–e0198548. 20 indexed citations
11.
Prah, Melissa, Mona Al-Gizawiy, Wade M. Mueller, et al.. (2017). Spatial discrimination of glioblastoma and treatment effect with histologically-validated perfusion and diffusion magnetic resonance imaging metrics. Journal of Neuro-Oncology. 136(1). 13–21. 32 indexed citations
12.
Malyarenko, Dariya, Andriy Fedorov, Laura C. Bell, et al.. (2017). Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies. Journal of Medical Imaging. 5(1). 1–1. 7 indexed citations
13.
Gerstner, Elizabeth R., Zheng Zhang, James R. Fink, et al.. (2016). ACRIN 6684: Assessment of Tumor Hypoxia in Newly Diagnosed Glioblastoma Using 18F-FMISO PET and MRI. Clinical Cancer Research. 22(20). 5079–5086. 85 indexed citations
14.
Prah, Melissa, Steven M. Stufflebeam, E.S. Paulson, et al.. (2015). Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma. American Journal of Neuroradiology. 36(9). 1654–1661. 40 indexed citations
15.
Gerstner, Elizabeth R., Zheng Zhang, James R. Fink, et al.. (2015). ACRIN 6684: Assessment of tumor hypoxia in newly diagnosed GBM using FMISO PET and MRI.. Journal of Clinical Oncology. 33(15_suppl). 2024–2024. 1 indexed citations
16.
17.
Schmainda, Kathleen M., Melissa Prah, Jennifer Connelly, et al.. (2014). Dynamic-susceptibility contrast agent MRI measures of relative cerebral blood volume predict response to bevacizumab in recurrent high-grade glioma. Neuro-Oncology. 16(6). 880–888. 82 indexed citations
18.
LaViolette, Peter S., Melissa Prah, Scott D. Rand, et al.. (2013). Vascular change measured with independent component analysis of dynamic susceptibility contrast MRI predicts bevacizumab response in high-grade glioma. Neuro-Oncology. 15(4). 442–450. 34 indexed citations
19.
Boxerman, J. L., E.S. Paulson, Melissa Prah, & Kathleen M. Schmainda. (2013). The Effect of Pulse Sequence Parameters and Contrast Agent Dose on Percentage Signal Recovery in DSC-MRI: Implications for Clinical Applications. American Journal of Neuroradiology. 34(7). 1364–1369. 23 indexed citations
20.
Verma, Sumit, Rachel M. Landisch, Brendan J. Quirk, et al.. (2012). Presumed Hydrogen Sulfide-mediated Neurotoxicity After Streptococcus Anginosus Group Meningitis. The Pediatric Infectious Disease Journal. 32(2). 189–191. 6 indexed citations

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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