Evidence map›Paper›PMID 39329992›Full record

ArticleCurrent oncology (Toronto, Ont.)2024

Could CT Radiomic Analysis of Benign Adrenal Incidentalomas Suggest the Need for Further Endocrinological Evaluation?

Alessandro Toniolo, Elena Agostini, Filippo Ceccato, Irene Tizianel, Giulio Cabrelle, Amalia Lupi, Alessia Pepe, Cristina Campi, Emilio Quaia, Filippo Crimì

Abstract read
In one paragraph

Article in Current oncology (Toronto, Ont.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

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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

10 authors.

Alessandro TonioloDepartment of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.ORCID 0009-0009-4217-2170
Elena AgostiniDepartment of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.
Filippo CeccatoEndocrinology Unit, Department of Medicine (DIMED), University of Padova, 35122 Padua, Italy.
Irene TizianelEndocrinology Unit, Department of Medicine (DIMED), University of Padova, 35122 Padua, Italy.
Giulio CabrelleDepartment of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.ORCID 0000-0002-9430-1036
Amalia LupiDepartment of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.ORCID 0000-0002-0743-9214
Alessia PepeDepartment of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.ORCID 0000-0001-6401-3829
Cristina CampiDepartment of Mathematics (DIMA), University of Genova, 16126 Genoa, Italy.ORCID 0000-0003-2105-8554
Emilio QuaiaDepartment of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.ORCID 0000-0003-2020-9365
Filippo CrimìDepartment of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.ORCID 0000-0001-6822-1430

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We studied the application of CT texture analysis in adrenal incidentalomas with baseline characteristics of benignity that are highly suggestive of adenoma to find whether there is a correlation between the extracted features and clinical data. Patients with hormonal hypersecretion may require medical attention, even if it does not cause any symptoms. A total of 206 patients affected by adrenal incidentaloma were retrospectively enrolled and divided into non-functioning adrenal adenomas (NFAIs, n = 115) and mild autonomous cortisol secretion (MACS, n = 91). A total of 136 texture parameters were extracted in the unenhanced phase for each volume of interest (VOI). Random Forest was used in the training and validation cohorts to test the accuracy of CT textural features and cortisol-related comorbidities in identifying MACS patients. Twelve parameters were retained in the Random Forest radiomic model, and in the validation cohort, a high specificity (81%) and positive predictive value (74%) were achieved. Notably, if the clinical data were added to the model, the results did not differ. Radiomic analysis of adrenal incidentalomas, in unenhanced CT scans, could screen with a good specificity those patients who will need a further endocrinological evaluation for mild autonomous cortisol secretion, regardless of the clinical information about the cortisol-related comorbidities.

Indexed as

Adrenal Gland NeoplasmsTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedRadiomicsRetrospective Studiesadenomaadrenalshormonal hypersecretionincidentalomamachine learningradiomics

Identifiers

PMID39329992
PMCPMC11431504

What Socratic holds

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Registered trials

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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 Socratic graph.