Evidence map›Paper›PMID 31956539›Full record

ArticleQuantitative imaging in medicine and surgery2020

BIGDOSE: software for 3D personalized targeted radionuclide therapy dosimetry.

Tiantian Li, Licheng Zhu, Zhonglin Lu, Na Song, Ko-Han Lin, Greta S P Mok

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Guideline
  2. Outcome-driven dosimetry optimization for [European journal of nuclear medicine and molecular imaging · 2026
    Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Recent advances in voxel-based targeted radionuclide therapy dosimetry.Quantitative imaging in medicine and surgery · 2021
    Article
  9. Article
  10. Article
  11. Prediction of Absorbed Dose to Normal Organs with Endocrine Tumors for I-131 by use ofIndian journal of nuclear medicine : IJNM : the official journal of the Society of Nuclear Medicine, India
    Article
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

6 authors at 3 institutions in 3 countries.

Tiantian LiBiomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, University of Macau, Macau SAR, China.
Licheng ZhuDepartment of Computer Science, Faculty of Science and Technology, University of Macau, Macau SAR, China.
Zhonglin LuBiomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, University of Macau, Macau SAR, China.
Na SongDepartment of Nuclear Medicine, Albert Einstein College of Medicine, Yeshiva University, Bronx, New York, USA.
Ko-Han LinDepartment of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
Greta S P MokBiomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, University of Macau, Macau SAR, China.
University of Macau · MOAlbert Einstein College of Medicine · USTaipei Veterans General Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdvance 3D quantitative radionuclide imaging techniques boost the accuracy of targeted radionuclide therapy (TRT) dosimetry to voxel level. The goal of this work is to develop a comprehensive 3D dosimetric software, BIGDOSE, with new features of image registration and virtual CT for patient-specific dosimetry.

methodsBIGDOSE includes a portable graphical user interface written in Python, integrating (I) input of sequential ECT/CT images; (II) segmentation; (III) non-rigid image registration; (IV) curve fitting and voxel-based integration; (V) dose conversion and (VI) 3D dose analysis. The accuracy of the software was evaluated using a simulation study with 9 XCAT phantoms. We simulated SPECT/CT acquisitions at 1, 12, 24, 72 and 144-hrs post In-111 Zevalin injection with inter-scans misalignments using an analytical projector for medium energy general purpose (MEGP) collimator, modeling attenuation, scatter and collimator-detector response. The SPECT data were reconstructed using quantitative OS-EM method. A CT organ-based registration was performed before the dose calculation. Organ absorbed doses for the corresponding Y-90 therapeutic agent were calculated on target organs and compared with those obtained from OLINDA/EXM, using dose measured from GATE as the gold standard. One patient with In-111 DTPAOC injection as well as two patients with Y-90 microsphere embolization were used to demonstrate the clinical effectiveness of our software.

resultsIn the simulation, the organ dose errors of BIGDOSE were -9.59%±9.06%, -8.36±5.82%, -23.41%±6.67%, -6.05%±2.06% for liver, spleen, kidneys and lungs, while they were -25.72%±12.52%, -14.93%±10.91%, -28.63%±12.97% and -45.30%±5.84% for OLINDA/EXM. Cumulative dose volume histograms, dose maps and iso-dose contours provided 3D dose distribution information on the simulated and patient data.

conclusionsBIGDOSE provides a one-stop platform for voxel-based dose estimation with enhanced functions. It is a promising tool to streamline the current clinical TRT dosimetric practice with high accuracy, incorporating 3D personalized imaging information for improved treatment outcome.

Indexed as

dosimetric softwareimage registrationpatient-specific internal dosimetryTargeted radionuclide therapy (TRT)

Identifiers

PMID31956539
PMCPMC6960414
OpenAlexW2989931406

What OpenQuestion holds

Textmetadata
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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.