Evidence map›Paper›PMID 34988888›Full record

ArticleAnnals of nuclear medicine2022

Dual time point imaging of staging PSMA PET/CT quantification; spread and radiomic analyses.

Ayşegül Aksu, Özge Vural Topuz, Gülşah Yılmaz, Gamze Çapa Kaya, Burçak Yılmaz

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Article in Annals of nuclear medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. PSMA-PET-derived distance features as biomarkers for predicting outcomes in primary prostate cancer post-radical prostatectomy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Article
  5. Review
  6. Article
  7. PrognosticDiagnostics (Basel, Switzerland) · 2023
    Article
  8. Article
  9. Review
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

5 authors.

Ayşegül AksuDepartment of Nuclear Medicine, Başakşehir Cam and Sakura City Hospital, Istanbul, Turkey. aaysegulgedikli@gmail.com.ORCID http://orcid.org/0000-0002-6239-0660
Özge Vural TopuzDepartment of Nuclear Medicine, Başakşehir Cam and Sakura City Hospital, Istanbul, Turkey.
Gülşah YılmazDepartment of Nuclear Medicine, Başakşehir Cam and Sakura City Hospital, Istanbul, Turkey.
Gamze Çapa KayaDepartment of Nuclear Medicine, School of Medicine, Dokuz Eylul University, Izmir, Turkey.
Burçak YılmazDepartment of Nuclear Medicine, Başakşehir Cam and Sakura City Hospital, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe aims were to evaluate the performance of models that predict Gleason Grade (GG) groups with radiomic data obtained from the prostate gland in dual time 68Ga-Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography/Computerized Tomography (PET/CT) images for prostate cancer (PCa) staging, and to analyze the contribution of late imaging to the radiomic model and to evaluate the relationship of the distance between tumor foci in the body (Dmax) obtained in early PET images with histopathology and prostate specific antigen (PSA) value.

methodsBetween October 2020 and August 2021, 41 patients who underwent 68Ga-PSMA PET/CT for staging of PCa were retrospectively analyzed. Volumetric and radiomics data were obtained from early and late PSMA PET images. The differences between age, metastasis status, PSA, standard uptake value (SUV), volumetric and radiomics parameters between GG groups were analyzed. Early and late PET radiomic models were created, area under curve (AUC), sensitivity, specificity and accuracy values of the models were obtained. In addition, the correlation of Dmax values with total PSMA-tumor volume (TV), Total lesion (TL)-PSMA and PSA values was evaluated. In metastatic patients, the difference in Dmax between GG groups was analyzed.

resultsThere was a significant difference between patients with GG ≤ 3 and > 3 in 35 of the early PET radiomic features. In the early PET model, multivariate analyses showed that GLRLM_RLNU and PSA were the most meaningful parameters. The AUC, sensitivity, specificity and accuracy values of the early model in detecting patients with GG > 3 were calculated as 0.902, 76.2%, 84% and 78.1%, respectively. In 36 late PET radiomic features, there was a significant difference between patients with GG ≤ 3 and > 3. In multivariate analyses; SHAPE_compacity and PSA were obtained as the most meaningful parameters. The AUC, sensitivity, specificity and accuracy values of the late model in detecting patients with GG > 3 were calculated as 0.924, 85.7%, 85% and 85.4%. There was a strong correlation between Dmax and PSA values (p < 0.001, rho: 0.793). Dmax showed strong correlation with PSMA-TVtotal and TL-PSMAtotal (p < 0.001, rho: 0.797; p < 0.001, rho: 0.763, respectively). In patients with metastasis, median Dmax values of the GG > 3 group were higher than GG ≤ 3 group; A statistically significant difference was obtained between these two groups (p = 0.023).

conclusionsModel generated from the late PSMA PET radiomic data had better performance in the current study. Without the use of invasive methods, the heterogeneity and aggressiveness of the primary tumor and the prediction of GG groups may be possible with 68Ga-PSMA PET/CT images obtained for diagnostic purposes especially with late PSMA PET/CT imaging.

Indexed as

Positron Emission Tomography Computed TomographyProstatic NeoplasmsGallium IsotopesGallium RadioisotopesHumansMaleRetrospective Studiesgallium 68 PSMA-11Gallium IsotopesGallium RadioisotopesDmaxDual time point imagingPETPSMARadiomic

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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.