ArticleInsights into imaging2025
Insulinoma detection on low-dose pancreatic CT perfusion: comparing with conventional contrast-enhanced CT and MRI.
Article in Insights into imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
objectivesTo evaluate the efficacy of low-dose pancreatic CT perfusion (pCTP) in detecting insulinomas in patients with recurrent hypoglycemia, and to compare its diagnostic performance with conventional contrast-enhanced CT (CECT) and MRI.
methodsThis study retrospectively collected 53 patients with recurrent hypoglycemia (28 with insulinomas; 25 without insulinomas). PCTP image analysis was conducted by two radiologists. Quantitative perfusion parameters of insulinomas vs. tumor-free pancreatic parenchyma were analyzed. For cases where both pCTP and CECT/MRI were performed, six radiologists blinded to the patients' diagnosis independently evaluated the pCTP and CECT/MRI to determine the presence and location of insulinoma. The diagnostic performance of insulinoma detection between pCTP and CECT/MRI was compared.
resultsFor patients who underwent both CECT and pCTP, the sensitivity (CECT 0.167-0.333 vs. pCTP 0.667-1.000) of tumor detection was higher for five of six radiologists on pCTP than on CECT. For patients who underwent both MRI and pCTP, four radiologists showed higher sensitivity (MRI 0.400-600 vs. pCTP 0.700-0.800) of tumor detection on pCTP than on MRI, while two radiologists showed slightly lower sensitivity (MRI 0.800, 1.000 vs. pCTP 0.700, 0.900) on pCTP. Among perfusion parameters, peak enhancement, blood flow, and mean transit time exhibited higher AUC than blood volume and time to peak.
conclusionPCTP demonstrated superior diagnostic performance in insulinoma detection among less-experienced radiologists compared to CECT and MRI, while more-experienced radiologists achieved marginally better results with MRI. These findings suggest pCTP's potential as a complementary imaging modality, particularly beneficial for junior radiologists in insulinoma detection. CRITICAL RELEVANCE STATEMENT: Pancreatic CT perfusion exhibited promising diagnostic performance in insulinoma detection, particularly among junior radiologists, demonstrating the potential to complement conventional imaging modalities and serve as a valuable clinical tool for the detection and localization of insulinoma. KEY POINTS: Accurate preoperative identification and localization of insulinomas is important for appropriate treatment. Peak enhancement, blood flow, and mean transit time outperformed blood volume and time to peak in insulinoma detection. Pancreatic CT perfusion has the potential to complement conventional imaging modalities for insulinoma detection.
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.