ArticleDiagnostic and interventional radiology (Ankara, Turkey)2022
Differentiation of adrenal adenomas from adrenal metastases in single-phased staging dual-energy CT and radiomics.
Article in Diagnostic and interventional radiology (Ankara, Turkey), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- Practical applications of photon-counting CT in oncology: an organ-based pictorial review.Insights into imaging · 2026Article
- Radiomic Characterization of Adrenal Incidentalomas on NECT: Retrospective Exploratory Study and Systematic Review.Journal of imaging · 2026Article
- Habitat-radiomics combining multichannel 2.5D deep learning for differentiating adrenal adenomas from metastases using automatic segmentation: a multicenter study.Frontiers in endocrinology · 2026Article
- Quantitative PCCT imaging in differentiating adrenal adenomas from metastases: diagnostic performance and its clinical applications.Abdominal radiology (New York) · 2025Article
- Adrenal lesion classification revisited: validation and adjustment of dual-energy CT derived virtual unenhanced attenuation thresholds.Abdominal radiology (New York) · 2025Article
- Evaluation of a fusion model combining deep learning models based on enhanced CT images with radiological and clinical features in distinguishing lipid-poor adrenal adenoma from metastatic lesions.BMC medical imaging · 2025Article
- The Value of PET/CT-Based Radiomics in Predicting Adrenal Metastases in Patients with Cancer.Diagnostics (Basel, Switzerland) · 2025Article
- Feasibility of extracellular volume fraction derived from single-phase spectral CT for differentiating between adrenal metastases and adenomas.Abdominal radiology (New York) · 2025Article
- The Role of Dual-Energy CT in Differentiating Adrenal Adenomas from Metastases: A Comprehensive Narrative Review.Journal of personalized medicine · 2025Review
- Review
- Evaluation of Adrenal Metastases in Prostate Cancer Patients with [68GA]GA-PSMA PET/CT Imaging.Current oncology (Toronto, Ont.) · 2025Article
- Preoperative prediction of Ki-67 expression in hepatocellular carcinoma by spectral imaging on dual-energy computed tomography (DECT).Quantitative imaging in medicine and surgery · 2024Article
- Diagnostic performance of photon-counting detector CT for differentiation between adrenal adenomas and metastases.European radiology · 2024Article
- What to Expect (and What Not) from Dual-Energy CT Imaging Now and in the Future?Journal of imaging · 2024Review
- Virtual Non-Contrast versus True Native in Photon-Counting CT: Stability of Density of Upper Abdominal Organs and Vessels.Diagnostics (Basel, Switzerland) · 2024Article
- Dual-Energy CT in Oncologic Imaging.Tomography (Ann Arbor, Mich.) · 2024Review
- Treating Primary Aldosteronism-Induced Hypertension: Novel Approaches and Future Outlooks.Endocrine reviews · 2024Article
- Fat quantification in dual-layer detector spectral CT: How to handle iron overload, varying tube voltage and radiation dose Indices.PloS one · 2024Article
- Adrenal indeterminate nodules: CT-based radiomics analysis of different machine learning models for predicting adrenal metastases in lung cancer patients.Frontiers in oncology · 2024Article
- Dual-Energy CT for Accurate Discrimination of Intraperitoneal Hematoma and Intestinal Structures.Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PURPOSE Differentiation of incidental adrenal lesions remains a challenge in diagnostic imaging, especially on single-phase portal venous computed tomography (CT) in the oncological setting. The aim of the study was to explore the ability of dual-energy CT (DECT)-based iodine quantification and virtual non-contrast (VNC) imaging and advanced radiomic analysis of DECT for differentiation of adrenal adenomas from metastases. METHODS A total of 46 patients with 49 adrenal lesions underwent clinically indicated staging DECT and magnetic resonance imaging. Median values of quantitative parameters such as VNC, fat frac- tion, and iodine density in DECT images were collected and compared between adenomas and metastases using non-parametric tests. Magnetic resonance imaging, washout CT, and clinical follow-up were used as a reference standard. Diagnostic accuracy was assessed by calculat- ing receiver operating characteristics. A DECT tumor analysis prototype software was used for semiautomatic segmentation of adrenal lesions and extraction of radiomic features. A radiomics prototype was used to analyze the data with multiple logistic regression and random forest clas- sification to determine the area under the curve (AUC). RESULTS The study cohort (60.87% women; mean age: 66.91 ± 12.93 years) consisted of 32 adenomas and 17 metastases. DECT-based VNC imaging (AUC=0.89) and fat quantification (AUC=0.86) differentiate between adrenal adenomas and metastases with high diagnostic accuracy (P < .001). Analysis of radiomic features revealed that DECT features such as VNC imaging and fat fraction (AUC = 0.87-0.89; < .001) and radiomic features such as 90th percentile and total energy (AUC = 0.88-0.93; P < .001) differentiate with high diagnostic accuracy between adrenal adeno- mas and metastases. Random forest classification revealed an AUC of 0.83 for separating adrenal adenomas from metastases. CONCLUSION Virtual non-contrast imaging and fat quantification as well as extraction of radiomic features accurately differentiate between adrenal adenomas and metastases on single-phase oncologic staging DECT.
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.