Evidence map›Paper›PMID 36591527›Full record

ArticleFrontiers in oncology2022

Theranostic digital twins for personalized radiopharmaceutical therapies: Reimagining theranostics

Arman Rahmim, Julia Brosch-Lenz, Ali Fele-Paranj, Fereshteh Yousefirizi, Madjid Soltani, Carlos Uribe, Babak Saboury

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
4.7field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 48 citations in OpenAlex.

  1. Review
  2. Review
  3. Digital Twin Technology In Radiology.Journal of imaging informatics in medicine · 2026
    Review
  4. Review
  5. Article
  6. Review
  7. The Role of Artificial Intelligence in Theranostics.Journal of nuclear medicine technology · 2025
    Review
  8. Enhancing randomized clinical trials with digital twins.NPJ systems biology and applications · 2025
    Review
  9. Article
  10. CanJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025
    Article
  11. Article
  12. Article
  13. Review
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  15. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Arman RahmimDepartment of Radiology, University of British Columbia, Vancouver, BC, Canada.
Julia Brosch-LenzDepartment of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
Ali Fele-ParanjDepartment of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
Fereshteh YousefiriziDepartment of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
Madjid SoltaniDepartment of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
Carlos UribeDepartment of Radiology, University of British Columbia, Vancouver, BC, Canada.
Babak SabouryDepartment of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
University of British Columbia · CANational Institutes of Health Clinical Center · USUniversity of Waterloo · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work emphasizes that patient data, including images, are not operable (clinically), but that digital twins are. Based on the former, the latter can be created. Subsequently, virtual clinical operations can be performed towards selection of optimal therapies. Digital twins are beginning to emerge in the field of medicine. We suggest that theranostic digital twins (TDTs) are amongst the most natural and feasible flavors of digitals twins. We elaborate on the importance of TDTs in a future where 'one-size-fits-all' therapeutic schemes, as prevalent nowadays, are transcended in radiopharmaceutical therapies (RPTs). Personalized RPTs will be deployed, including optimized intervention parameters. Examples include optimization of injected radioactivities, sites of injection, injection intervals and profiles, and combination therapies. Multi-modal multi-scale images, combined with other data and aided by artificial intelligence (AI) techniques, will be utilized towards routine digital twinning of our patients, and will enable improved deliveries of RPTs and overall healthcare.

Indexed as

digitals twinsmolecular imagingpersonalized medicineradiopharmaceutical therapiestheranostics

Identifiers

PMID36591527
PMCPMC9797662
OpenAlexW4311504925

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.