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Characteristic CT features of pheochromocytomas - probability model calculation tool based on a multicentric study.

ABSTRACT: OBJECTIVES:The aim of the study was to evaluate the CT features of adrenal tumors in an effort to identify features specific to pheochromocytomas and second, to define a feasible probability calculation model. METHODS:This multicentric retrospective study included patients from the period 2003 to 2017 with an appropriate CT examination and a histological diagnosis of an adrenal adenoma, pheochromocytoma, adrenocortical carcinoma, or metastasis. In total, 346 patients were suitable for the CT image analysis, which included evaluation of the largest diameter, the shape of the lesion, the presence of central necrosis and its margins, and the presence of an enhancing peripheral rim ("ring sign"). RESULTS:Pheochromocytomas have a significantly more spherical shape (P<0.001), whereas an elliptical shape significantly reduces the probability of a pheochromocytoma (odds ratio = 0.015), as does another shape (odds ratio = 0.006). A "ring sign" is also more frequent in pheochromocytomas compared to other adrenal tumors (P=0.001, odds ratio = 6.49). A sharp necrosis also increases the probability of a pheochromocytoma more than unsharp necrosis (odds ratio 231.6 vs. 20.2). The probability calculation model created on the basis of the results confirms a high sensitivity and specificity (80% and 95%). CONCLUSION:This study confirms the value of anatomical features in the assessment of adrenal masses with the ability to significantly improve the identification of pheochromocytomas. Advanced assessment of the tumor shape was defined and a original comprehensive calculating tool of the pheochromocytoma probability was created on the basis of the results presented here and could be used in clinical routine.

SUBMITTER: Ctvrtlik F

PROVIDER: S-EPMC6875693 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Characteristic CT features of pheochromocytomas - probability model calculation tool based on a multicentric study.

Ctvrtlik Filip F Tudos Zbynek Z Szasz Paulina P Sedlackova Zuzana Z Hartmann Igor I Schovanek Jan J Frysak Zdenek Z Macova Iva I Zelinka Tomas T Hora Milan M Kocova Eva E Pacovsky Jaroslav J Krsek Michal M Lehotska Viera V Mojtova Emilia E Molnar Josef J Vanek Vladimir V Pacak Karel K Baxa Jan J

Biomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia 20190923 3

<h4>Objectives</h4>The aim of the study was to evaluate the CT features of adrenal tumors in an effort to identify features specific to pheochromocytomas and second, to define a feasible probability calculation model.<h4>Methods</h4>This multicentric retrospective study included patients from the period 2003 to 2017 with an appropriate CT examination and a histological diagnosis of an adrenal adenoma, pheochromocytoma, adrenocortical carcinoma, or metastasis. In total, 346 patients were suitable ...[more]

PMID: 31544898

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Project description:The Leksell GammaPlan software version 10 introduces a CT image-based segmentation tool for automatic skull definition and a convolution dose calculation algorithm for tissue inhomogeneity correction. The purpose of this work was to evaluate the impact of these new approaches on routine clinical Gamma Knife treatment planning. Sixty-five patients who underwent CT image-guided Gamma Knife radiosurgeries at the University of Pittsburgh Medical Center in recent years were retrospectively investigated. The diagnoses for these cases include trigeminal neuralgia, meningioma, acoustic neuroma, AVM, glioma, and benign and metastatic brain tumors. Dose calculations were performed for each patient with the same dose prescriptions and the same shot arrangements using three different approaches: 1) TMR 10 dose calculation with imaging skull definition; 2) convolution dose calculation with imaging skull definition; 3) TMR 10 dose calculation with conventional measurement-based skull definition. For each treatment matrix, the total treatment time, the target coverage index, the selectivity index, the gradient index, and a set of dose statistics parameters were compared between the three calculations. The dose statistics parameters investigated include the prescription isodose volume, the 12 Gy isodose volume, the minimum, maximum and mean doses on the treatment targets, and the critical structures under consideration. The difference between the convolution and the TMR 10 dose calculations for the 104 treatment matrices were found to vary with the patient anatomy, location of the treatment shots, and the tissue inhomogeneities around the treatment target. An average difference of 8.4% was observed for the total treatment times between the convolution and the TMR algorithms. The maximum differences in the treatment times, the prescription isodose volumes, the 12 Gy isodose volumes, the target coverage indices, the selectivity indices, and the gradient indices from the convolution and the TMR 10 calculations are 14.9%, 16.4%, 11.1%, 16.8, 6.9%, and 11.4%, respectively. The maximum differences in the minimum and the mean target doses between the two calculation algorithms are 8.1% and 4.2% of the corresponding prescription doses. The maximum differences in the maximum and the mean doses for the critical structures between the two calculation algorithms are 1.3 Gy and 0.7 Gy. The results from the two skull definition methods with the TMR 10 algorithm agree either within ± 2.5% or 0.3 Gy for the dose values, except for a 4.9% difference in the treatment times for a lower cerebellar lesion. The imaging skull definition method does not affect Gamma Knife dose calculation considerably when compared to the conventional measurement-based skull definition method, except in some extreme cases. Large differences were observed between the TMR 10 and the convolution calculation method for the same dose prescription and the same shot arrangements, indicating that the implementation of the convolution algorithm in routine clinical use might be desirable for optimal dose calculation results.

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Characteristic CT features of pheochromocytomas - probability model calculation tool based on a multicentric study.

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Characteristic CT features of pheochromocytomas - probability model calculation tool based on a multicentric study.

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