Science Explorer Interactive view Map

MRI in cancer diagnosis

MRI in cancer diagnosis is a research topic within Radiology, Nuclear Medicine and Imaging. Science Explorer counts 33k research works in it since 1951. 18.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the use of breast magnetic resonance imaging (MRI) in oncology, particularly in the context of cancer biomarkers, diagnostic accuracy for breast lesions, monitoring tumor response to neoadjuvant chemotherapy, and the application of diffusion-weighted and dynamic contrast-enhanced MRI for assessing perfusion and tumor characteristics. The research also explores the potential of breast MRI as a tool for predicting and monitoring treatment response in breast cancer patients.

  • Breast MRI
  • Diffusion-Weighted Imaging
  • Dynamic Contrast-Enhanced MRI
  • Cancer Biomarkers
  • Breast Lesions
  • Diagnostic Accuracy
  • Neoadjuvant Chemotherapy
  • Tumor Response
  • Perfusion Imaging
  • Magnetic Resonance Imaging
Research works
33k
fractional, since 1951
In the world top 10%
5.9k
per year above
Top-10% rate
18.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-4%
the tick is no change

This ranks research output and citation impact. It says nothing about the quality of diagnosis, treatment or care.

Which countries lead MRI in cancer diagnosis research?

By volume, China and the United States publish the most (1.4k and 1.1k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.4k works
  2. 2 United States 1.1k works
  3. 3 Germany 303 works
  4. 4 Japan 279 works
  5. 5 Italy 211 works
  6. 6 United Kingdom 203 works
  7. 7 South Korea 179 works
  8. 8 India 176 works
  9. 9 Netherlands 131 works
  10. 10 France 129 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 34.9%United States: 25.9%Germany: 7.4%Japan: 6.8%6 others listed: 25.0%35%largest
China1,438 · 34.9%United States1,067 · 25.9%Germany303 · 7.4%Japan279 · 6.8%6 others listed1,030 · 25.0%

Shares of the rows listed above, not of the whole node.

Which institutions lead MRI in cancer diagnosis research?

By volume in 2022–2025, Memorial Sloan Kettering Cancer Center publishes the most MRI in cancer diagnosis research, followed by Sun Yat-sen University and The University of Texas MD Anderson Cancer Center.

Who are the leading researchers in MRI in cancer diagnosis?

The most-cited researchers publishing on MRI in cancer diagnosis include Lawrence H. Schwartz, John C. Morris and Marcus E. Raichle.

  1. 1 Lawrence H. Schwartz United States 5.8k citations
  2. 2 John C. Morris United States 5.1k citations
  3. 3 Marcus E. Raichle United States 3.6k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is MRI in cancer diagnosis research done?

The largest centres of MRI in cancer diagnosis research in 2022–2025 are Shanghai (China), Beijing (China), Guangzhou (China) and Seoul (South Korea). Among places with at least 20 works in it, it is an unusually large share of all research in Forchheim and Heidelberg.

Largest cities, 2022–2025

  1. 1 Shanghai China 174 works
  2. 2 Beijing China 144 works
  3. 3 Guangzhou China 125 works
  4. 4 Seoul South Korea 104 works
  5. 5 New York United States 84 works
  6. 6 London United Kingdom 83 works
  7. 7 Tokyo Japan 62 works
  8. 8 Hangzhou China 55 works
  9. 9 Nanjing China 54 works
  10. 10 Chengdu China 53 works

Where it is the local speciality

  1. ForchheimDE · 23.1 works195×
  2. HeidelbergDE · 36.7 works7.1×
← less than its size predictsmore →

Location quotient: how much more of its research is in MRI in cancer diagnosis than the world average.

See MRI in cancer diagnosis on the map

Where is the best place to study MRI in cancer diagnosis?

Among universities, judged by research, Nanjing Medical University, Medical University of Vienna and Harvard University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 24.59%fractional works in this node (log) →share in the world top 10% →Nanjing Medical University: 20, 19.1%Medical University of Vienna: 13, 17.0%Harvard University: 19, 28.2%China Medical University: 11, 37.5%Fujian Medical University: 16, 21.3%University College London: 15, 32.3%Sun Yat-sen University: 30, 21.5%Heidelberg University: 14, 25.4%Chinese University of Hong Kong: 10, 35.0%Medical College of Wisconsin: 14, 8.6%China Medical Univer…Harvard UniversityNanjing Medical Univ…Medical University o…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Nanjing Medical UniversityChina 53.619.1%7.7×20 +50.4%
2 Medical University of ViennaAustria 52.517.0%8.8×13 +8.0%
3 Harvard UniversityUnited States 50.828.2%3.0×19 +24.7%
4 China Medical UniversityChina 50.637.5%6.7×11 -43.5%
5 Fujian Medical UniversityChina 50.321.3%8.9×16 -30.3%
6 University College LondonUnited Kingdom 49.432.3%2.2×15 +25.0%
7 Sun Yat-sen UniversityChina 48.621.5%3.8×30 -8.9%
8 Heidelberg UniversityGermany 47.925.4%5.3×14 -18.4%
9 Chinese University of Hong KongHong Kong 46.535.0%2.8×10 -34.3%
10 Medical College of WisconsinUnited States 45.88.6%10.9×14 +34.3%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is MRI in cancer diagnosis research growing?

Output in 2018–2022 was 4% lower than in 2013–2017, peaking in 2014. The fastest-growing topics are MRI in cancer diagnosis.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.