ArticlePhysica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)2018
Quantifying the robustness of [
Article in Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03967951 (CT Radiomic Features of Pancreatic Neuroendocrine Neoplasms), which is not on this map. Cited by 34 papers.
What it found
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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.
CT Radiomic Features of Pancreatic Neuroendocrine Neoplasms
Who cites it
34 citing papers in PubMed.
- Article
- The effect of harmonization on the variability of PET radiomic features extracted using various segmentation methods.Annals of nuclear medicine · 2024Article
- Multicentric development and evaluation of [European journal of nuclear medicine and molecular imaging · 2024Article
- Interobserver agreement on definition of the target volume in stereotactic radiotherapy for pancreatic adenocarcinoma using different imaging modalities.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2023Article
- Sensitivity of standardised radiomics algorithms to mask generation across different software platforms.Scientific reports · 2023Article
- Multicentric development and evaluation ofEuropean journal of nuclear medicine and molecular imaging · 2023Article
- Role of PET/CT in Oropharyngeal Cancers.Cancers · 2023Review
- CT radiomic predictors of local relapse after SBRT for lung oligometastases from colorectal cancer: a single institute pilot study.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2023Article
- External validation of anEuropean journal of nuclear medicine and molecular imaging · 2023Article
- Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features.European journal of hybrid imaging · 2023Article
- Radiomics: a primer on high-throughput image phenotyping.Abdominal radiology (New York) · 2022Review
- Artificial Intelligence Applied to Pancreatic Imaging: A Narrative Review.Healthcare (Basel, Switzerland) · 2022Review
- Analysis of Cross-Combinations of Feature Selection and Machine-Learning Classification Methods Based on [Cancers · 2022Article
- Quantitative Radiomics Features in Diffuse Large B-Cell Lymphoma: Does Segmentation Method Matter?Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022Article
- Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study.Clinical & experimental metastasis · 2021Article
- Radiomics feature reliability assessed by intraclass correlation coefficient: a systematic review.Quantitative imaging in medicine and surgery · 2021Review
- A systematic review and quality of reporting checklist for repeatability and reproducibility of radiomic features.Physics and imaging in radiation oncology · 2021Review
- The exploration of quantitative intra-tumoral metabolic heterogeneity in dual-timeAbdominal radiology (New York) · 2021Article
- Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods.Journal of personalized medicine · 2021Review
- Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer.Scientific reports · 2021Article
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo investigate the robustness of PET radiomic features (RF) against tumour delineation uncertainty in two clinically relevant situations.
methodsTwenty-five head-and-neck (HN) and 25 pancreatic cancer patients previously treated with
resultsA large disagreement between manual and SUV_max method was found for thresholds ≥50%. Inter-observer variability showed median DICE values between 0.81 (HN-T) and 0.73 (pancreas). Volumes defined by PET_Edge were better consistent with the manual ones compared to SUV40%. Regarding RF, 19%/19%/47% of the features showed ICC < 0.80 between observers for HN-N/HN-T/pancreas, mostly in the Voxel-alignment matrix and in the intensity-size zone matrix families. RFs with ICC < 0.80 against manual delineation (taking the worst value) increased to 44%/36%/61% for PET_Edge and to 69%/53%/75% for SUV40%.
conclusionsAbout 80%/50% of 72 RF were consistent between observers for HN/pancreas patients. PET_edge was sufficiently robust against manual delineation while SUV40% showed a worse performance. This result suggests the possibility to replace manual with semi-automatic delineation of HN and pancreas tumours in studies including PET radiomic analyses.
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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.