Elizabeth R. Gerstner

18.5k total citations · 2 hit papers
147 papers, 5.9k citations indexed

About

Elizabeth R. Gerstner is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Elizabeth R. Gerstner has authored 147 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 100 papers in Genetics, 62 papers in Radiology, Nuclear Medicine and Imaging and 35 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Elizabeth R. Gerstner's work include Glioma Diagnosis and Treatment (100 papers), MRI in cancer diagnosis (35 papers) and Brain Metastases and Treatment (31 papers). Elizabeth R. Gerstner is often cited by papers focused on Glioma Diagnosis and Treatment (100 papers), MRI in cancer diagnosis (35 papers) and Brain Metastases and Treatment (31 papers). Elizabeth R. Gerstner collaborates with scholars based in United States, Norway and Germany. Elizabeth R. Gerstner's co-authors include Tracy T. Batchelor, A. Gregory Sorensen, Patrick Y. Wen, Rakesh K. Jain, Ovidiu C. Andronesi, Robert L. Fine, Dan G. Duda, Bruce R. Rosen, Jayashree Kalpathy–Cramer and Kyrre E. Emblem and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Elizabeth R. Gerstner

142 papers receiving 5.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Intraventricular CARv3-TEAM-E T Cells in Recurrent Glioblastoma

2024 210 citations Bryan D. Choi, Elizabeth R. Gerstner et al. profile →
A review of deep learning for brain tumor analysis in MRI

2025 16 citations Jayashree Kalpathy-Cramer, Elizabeth R. Gerstner et al. npj Precision Oncology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Elizabeth R. Gerstner United States	41	3.0k	1.6k	1.3k	1.2k	1.0k	147	5.9k
Jong Hee Chang South Korea	46	3.5k 1.2×	2.1k 1.3×	1.4k 1.0×	1.6k 1.3×	1.2k 1.2×	320	7.8k
Seok‐Gu Kang South Korea	43	2.7k 0.9×	1.4k 0.9×	1.8k 1.3×	501 0.4×	817 0.8×	211	6.2k
Enrico Franceschi Italy	38	4.1k 1.4×	1.1k 0.7×	1.4k 1.0×	809 0.7×	2.0k 1.9×	193	5.8k
Eric T. Wong United States	40	4.9k 1.6×	1.9k 1.2×	1.8k 1.4×	977 0.8×	2.4k 2.3×	157	8.3k
Yoshitaka Narita Japan	37	2.6k 0.9×	658 0.4×	2.0k 1.5×	753 0.6×	1.2k 1.1×	234	5.6k
Jens Schittenhelm Germany	36	2.4k 0.8×	1.0k 0.6×	1.2k 0.9×	905 0.7×	740 0.7×	190	4.7k
Jörg C. Tonn Germany	38	2.9k 1.0×	1.1k 0.7×	1.9k 1.4×	621 0.5×	925 0.9×	59	5.3k
Stephen W. Coons United States	44	3.4k 1.1×	1.5k 0.9×	1.9k 1.4×	1.0k 0.8×	1.2k 1.2×	148	6.9k
Frank S. Lieberman United States	38	2.5k 0.8×	689 0.4×	1.5k 1.1×	709 0.6×	931 0.9×	139	5.0k
Roland Goldbrunner Germany	38	2.6k 0.9×	956 0.6×	1.9k 1.4×	1.6k 1.3×	1.2k 1.2×	242	7.4k

Countries citing papers authored by Elizabeth R. Gerstner

Since Specialization

Citations

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

Fields of papers citing papers by Elizabeth R. Gerstner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Elizabeth R. Gerstner. 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 Elizabeth R. Gerstner. The network helps show where Elizabeth R. Gerstner may publish in the future.

Co-authorship network of co-authors of Elizabeth R. Gerstner

This figure shows the co-authorship network connecting the top 25 collaborators of Elizabeth R. Gerstner. A scholar is included among the top collaborators of Elizabeth R. Gerstner 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 Elizabeth R. Gerstner. Elizabeth R. Gerstner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kalpathy-Cramer, Jayashree, et al.. (2025). A review of deep learning for brain tumor analysis in MRI. npj Precision Oncology. 9(1). 2–2. 16 indexed citations breakdown →

Nahed, Brian V., Bob S. Carter, Elizabeth R. Gerstner, et al.. (2024). Clinical progress in the development of CAR T cells to treat malignant glioma. Journal of Neuro-Oncology. 171(3). 571–579. 1 indexed citations

Numan, Tianne, Jolanda Derks, Menno M. Schoonheim, et al.. (2022). Regional healthy brain activity, glioma occurrence and symptomatology. Brain. 145(10). 3654–3665. 35 indexed citations

Walbert, Tobias, Rebecca A. Harrison, David Schiff, et al.. (2021). SNO and EANO practice guideline update: Anticonvulsant prophylaxis in patients with newly diagnosed brain tumors. Neuro-Oncology. 23(11). 1835–1844. 80 indexed citations

Lim-Fat, Mary Jane, Kun Song, J. Bryan Iorgulescu, et al.. (2021). Clinical, radiological and genomic features and targeted therapy in BRAF V600E mutant adult glioblastoma. Journal of Neuro-Oncology. 152(3). 515–522. 18 indexed citations

El-Abtah, Mohamed E., Pratik Talati, Akila Weerasekera, et al.. (2021). Myo-Inositol Levels Measured with MR Spectroscopy Can Help Predict Failure of Antiangiogenic Treatment in Recurrent Glioblastoma. Radiology. 302(2). 410–418. 10 indexed citations

Ellingson, Benjamin M., Jingwen Yao, Catalina Raymond, et al.. (2020). Multiparametric MR-PET Imaging Predicts Pharmacokinetics and Clinical Response to GDC-0084 in Patients with Recurrent High-Grade Glioma. Clinical Cancer Research. 26(13). 3135–3144. 10 indexed citations

Kaufmann, Timothy J., Marion Smits, Jerrold L. Boxerman, et al.. (2020). Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases. Neuro-Oncology. 22(6). 757–772. 150 indexed citations

Huang, Raymond Y., Robert J. Young, Benjamin M. Ellingson, et al.. (2020). Volumetric analysis of IDH-mutant lower-grade glioma: a natural history study of tumor growth rates before and after treatment. Neuro-Oncology. 22(12). 1822–1830. 26 indexed citations

10.

Gilbert, Mark R., Ying Yuan, Jimin Wu, et al.. (2020). A phase II study of dose-dense temozolomide and lapatinib for recurrent low-grade and anaplastic supratentorial, infratentorial, and spinal cord ependymoma. Neuro-Oncology. 23(3). 468–477. 37 indexed citations

11.

Gerstner, Elizabeth R., Kyrre E. Emblem, Ken Chang, et al.. (2019). Bevacizumab Reduces Permeability and Concurrent Temozolomide Delivery in a Subset of Patients with Recurrent Glioblastoma. Clinical Cancer Research. 26(1). 206–212. 40 indexed citations

12.

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

13.

Curry, William T., Matthias Piesche, Tetsuro Sasada, et al.. (2016). Vaccination with Irradiated Autologous Tumor Cells Mixed with Irradiated GM-K562 Cells Stimulates Antitumor Immunity and T Lymphocyte Activation in Patients with Recurrent Malignant Glioma. Clinical Cancer Research. 22(12). 2885–2896. 45 indexed citations

14.

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

15.

Tanaka, Toru, Takuya Tanaka, Noriaki Hashimoto, et al.. (2016). Deformable image registration between pathological images and MR image via an optical macro image. Pathology - Research and Practice. 212(10). 927–936. 11 indexed citations

16.

Blakeley, Jaishri O., Xiaobu Ye, Dan G. Duda, et al.. (2016). Efficacy and Biomarker Study of Bevacizumab for Hearing Loss Resulting From Neurofibromatosis Type 2–Associated Vestibular Schwannomas. Journal of Clinical Oncology. 34(14). 1669–1675. 86 indexed citations

17.

Andronesi, Ovidiu C., Franziska Loebel, Wolfgang Bogner, et al.. (2015). Treatment Response Assessment in IDH-Mutant Glioma Patients by Noninvasive 3D Functional Spectroscopic Mapping of 2-Hydroxyglutarate. Clinical Cancer Research. 22(7). 1632–1641. 116 indexed citations

18.

Andronesi, Ovidiu C., Elizabeth R. Gerstner, Tracy T. Batchelor, et al.. (2012). Detection of 2-Hydroxyglutarate in IDH-Mutated Glioma Patients by In Vivo Spectral-Editing and 2D Correlation Magnetic Resonance Spectroscopy. DSpace@MIT (Massachusetts Institute of Technology). 69 indexed citations

19.

Batchelor, Tracy T., Dan G. Duda, Emmanuelle di Tomaso, et al.. (2010). Phase II Study of Cediranib, an Oral Pan–Vascular Endothelial Growth Factor Receptor Tyrosine Kinase Inhibitor, in Patients With Recurrent Glioblastoma. Journal of Clinical Oncology. 28(17). 2817–2823. 406 indexed citations

20.

Dalmau, Josep, Sakir H. Gultekin, Raymond Voltz, et al.. (1999). Ma1, a novel neuron- and testis-specific protein, is recognized by the serum of patients with paraneoplastic neurological disorders. Brain. 122(1). 27–39. 162 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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