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Cited by 31Radiomics and Machine Learning in Medical ImagingAdrenal and Paraganglionic TumorsImage Retrieval and Classification Techniques

Differentiating pheochromocytoma from lipid-poor adrenocortical adenoma by CT texture analysis: feasibility study

Zhang, Gu-Mu-Yang, Shi, Bing, Sun, Hao, Jin, Zheng-Yu, Xue, Hua-Dan·2017·Abdominal Radiology
DOI 10.1007/s00261-017-1118-3
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Abstract

Objectives To investigate the feasibility of using CT texture analysis (CTTA) to differentiate pheochromocytoma from lipid-poor adrenocortical adenoma (lp-ACA).Methods Ninety-eight pheochromocytomas and 66 lp-ACAs were included in this retrospective study. CTTA was performed on unenhanced and enhanced images. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different for the objective. Diagnostic accuracies were evaluated using the cutoff values of texture parameters with the highest AUCs.Results Compared to lp-ACAs, pheochromocytomas had significantly higher mean gray-level intensity (Mean), entropy, and mean of positive pixels (MPP), but lower skewness and kurtosis on unenhanced images (P < 0.001). On enhanced images, these texture-quantifiers followed a similar trend where Mean, entropy, and MPP were higher, but skewness and kurtosis were lower in pheochromocytomas. Standard deviation (SD) was also significantly higher in pheochromocytomas on enhanced images. Mean and MPP quantified from no filtration on unenhanced CT images yielded the highest AUC of 0.86 ± 0.03 (95% CI 0.81-0.91) at a cutoff value of 34.0 for Mean and MPP, respectively (sensitivity = 79.6%, specificity = 83.3%, accuracy = 81.1%).Conclusions It was feasible to use CTTA to differentiate pheochromocytoma from lp-ACA.

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Crossref · 10.1007/s00261-017-1118-3

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  • In a feasibility study of 164 patients with indeterminate adrenal lesions at CT, intralesion textural features extracted from unenhanced images allowed differentiation between adenoma and pheochromocytoma with an accuracy of 81%.

    “In a feasibility study of 164 patients with indeterminate adrenal lesions at CT (98 pheochromocytoma; 66 lipid-poor adrenal adenomas), intralesion textural features (mean gray-level intensity and mean positive pixels) extracted from unenhanced images allowed differentiation between adenoma and pheochromocytoma with an accuracy of 81% (378).”

    From Adrenal incidentaloma (2020) · cites this paper as [378]

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  • Adrenal incidentaloma

    Sherlock, M., Scarsbrook, A., Abbas, A., Fraser, S., Limumpornpetch, P., Dineen, R., & Stewart, P. M. (2020) · Endocrine Reviews · doi:10.1210/endrev/bnaa008 · Cited by 347 · see citing works

    “In a feasibility study of 164 patients with indeterminate adrenal lesions at CT (98 pheochromocytoma; 66 lipid-poor adrenal adenomas), intralesion textural features (mean gray-level intensity and mean positive pixels) extracted from unenhanced images allowed differentiation between adenoma and pheochromocytoma with an…”
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Related

Authors
Zhang, G.-M.-Y., Shi, B., Sun, H., Jin, Z.-Y., & Xue, H.-D.
Affiliations
Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
Corresponding author
Sun, Hao
ORCID
Venue
Abdominal Radiology
Publisher
Springer Science and Business Media LLC
Published
2017-03-29
Volume
42
Issue
9
Pages
2305-2313
ISSN
  • 2366-004X (ISSN-L)
  • 2366-0058
DOI
10.1007/s00261-017-1118-3
OpenAlex
W2600355840
Cited by
31
References
23
Citations by year
2026: 2 · 2025: 2 · 2024: 2 · 2023: 6 · 2022: 5 · 2021: 4 · 2020: 6 · 2019: 1 · 2018: 1 · 2017: 1
FWCI
1.89
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (unspecified)
Locations
  • Abdominal Radiology (publishedVersion)
  • PubMed (publishedVersion)
Funders
The Health Industry Special Scientific Research Project of China (201402019)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
  • Health Sciences › Medicine › Surgery › Adrenal and Paraganglionic Tumors
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
Keywords
pheochromocytoma, CT texture analysis, adrenal tumors, differential diagnosis, texture features, entropy (information theory), skewness and kurtosis
MeSH terms
Adolescent, Adrenal Gland Neoplasms, Adult, Aged, Contrast Media, Diagnosis, Differential, Feasibility Studies, Female, Humans, Iohexol, Male, Middle Aged, Pheochromocytoma, Retrospective Studies, Sensitivity and Specificity, Tomography, X-Ray Computed, Adrenocortical Adenoma

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