ArticleJapanese journal of radiology2026
Article in Japanese journal of radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- The SPECT/CT radiomics-based classification of skeletal metastases and benign bone lesions.Scientific reports · 2026Article
- Artificial intelligence across oncologic theranostics: evidence for patient stratification, dosimetry, and adaptive radiopharmaceutical therapy.Frontiers in nuclear medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposePredicting treatment response in patients with colorectal cancer liver metastases (CRCLM) who have undergone transarterial radioembolization (TARE) based on pre-procedural fluorine-18-fluoro-deoxy glucose positron emission tomography ( MATERIALS AND
methodsPatients with CRCLM who underwent TARE, between March 2015 and May 2025, were consecutively included. Largest tumors were segmented semiautomatically using pre-procedural
resultsSeventy-four patients out of 96 patients were included. Top five selected features in the radiomics-only dataset were Coarseness, IMC1, Zone Entropy, Size-Zone Non-Uniformity, and Strength. In the clinico-radiomic dataset, AST and ALT levels were substituted among the top five features. Radiomics-only features demonstrated AUCs ranging from 0.90 (95% CI 0.71-1) to 0.81 (95% CI 0.51-1) in the test-set while clinico-radiomics dataset AUCs varied between 0.88 (95% CI 0.51-1) and 0.84 (0.62-1).
conclusion
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.