Adrenal Imaging

Brain tissue heterotopic in the adrenal gland in a child: a scarce case report

Heterotopic brain tissue is rare and has not been reported. Our center made the first report. 4 years and 2 months old Girl presented with a cystic mass in the right adrenal gland 2 weeks after right upper abdominal pain. The operation was successful, and the diagnosis was confirmed by postoperative pathology. 6 months after the procedure, the incision healed well without recurrence. This case report has a detailed diagnosis and treatment process and satisfactory examination results. It can provide a reference for diagnosing and treating clinical HBT and reduce the risk of misdiagnosis and mistreatment.

Pheochromocytoma With Brown Adipose Tissue Stimulation: A Case Report

Brown adipose tissue represents about 1% of the adult body mass and decreases with age. Under variable circumstances, this amount changes, for example, with age or environmental conditions. Pathological states with hypersecretion of catecholamines can induce hypertrophy and hyperplasia in mature brown adipocytes. Consequently, this response can have imaging representation as pseudonodules, a pitfall in imaging interpretation, and may be confused with neoplastic involvement. A case of pheochromocytoma with brown fat stimulation and catecholamine cardiomyopathy is presented.

Adrenal lesion classification with abdomen caps and the effect of ROI size

Accurate classification of adrenal lesions on magnetic resonance (MR) images are very important for diagnosis and treatment planning. The detection and classification of lesions in medical imaging heavily rely on several key factors, including the specialist's level of experience, work intensity, and fatigue of the clinician. These factors are critical determinants of the accuracy and effectiveness of the diagnostic process, which in turn has a direct impact on patient health outcomes. With the spread of artificial intelligence, the use of computer-aided diagnosis (CAD) systems in disease diagnosis has also increased. In this study, adrenal lesion classification was performed using deep learning on MR images. The data set used was obtained from the Department of Radiology, Faculty of Medicine, Selcuk University, and all adrenal lesions were identified and reviewed in consensus by two radiologists experienced with abdominal MR. Studies were carried out on two different data sets created by T1- and T2-weighted MR images. The data set consisted of 112 benign and 10 malignant lesions for each mode. Experiments were performed with regions of interest (ROIs) of different sizes to increase the working performance. Thus, the effect of the selected ROI size on the classification performance was assessed. In addition, instead of the convolutional neural network (CNN) models used in deep learning, a unique classification model structure called Abdomen Caps was proposed. When the data sets used in classification studies are manually separated for training, validation, and testing, different results are obtained with different data sets for each stage. To eliminate this imbalance, tenfold cross-validation was used in this study. The best results obtained were 0.982, 0.999, 0.969, 0.983, 0.998, and 0.964 for accuracy, precision, recall, F1-score, area under the curve (AUC) score, and kappa score, respectively.

MWA Performed at 5.8 GHz through 'Side Firing' Approach: An Exploratory Study

Recent studies have shown that ablation techniques have the potential to eradicate adrenal adenomas while preserving the functionalities of the adrenal gland and the surrounding anatomical structures. This study explores a new microwave ablation (MWA) approach operating at 5.8 GHz and using anatomical and dielectric characteristics of the target tissue to create directional heating patterns. Numerical simulations are executed in planar and 3D adrenal models, considering two energy doses. The numerical study is refined accounting for the vaporization of the tissue water content. Ex vivo experimental evaluations on porcine adrenal models complete the study. The numerical and experimental results show that spherical ablation zones are able to cover the target for both energy doses considered. Nonetheless, most of the non-targeted tissues can be preserved from excessive heating when low energy level is used. Numerical models accounting for water vaporization are capable to foresee the experimental temperature values. This study shows that the proposed MWA directional approach operating at 5.8 GHz can be considered for creating effective and selective ablation zones.

Adrenal Lesions: A Review of Imaging

Adrenal lesions are frequently incidentally diagnosed during investigations for other clinical conditions. Despite being usually benign, nonfunctioning, and silent, they can occasionally cause discomfort or be responsible for various clinical conditions due to hormonal dysregulation; therefore, their characterization is of paramount importance for establishing the best therapeutic strategy. Imaging techniques such as ultrasound, computed tomography, magnetic resonance, and PET-TC, providing anatomical and functional information, play a central role in the diagnostic workup, allowing clinicians and surgeons to choose the optimal lesion management. This review aims at providing an overview of the most encountered adrenal lesions, both benign and malignant, including describing their imaging characteristics.

Computer-assisted Reporting and Decision Support Increases Compliance with Follow-up Imaging and Hormonal Screening of Adrenal Incidentalomas

OBJECTIVE

To assess the impact of using a computer-assisted reporting and decision support (CAR/DS) tool at the radiologist point-of-care on ordering provider compliance with recommendations for adrenal incidentaloma workup.

METHOD

Abdominal CT reports describing adrenal incidentalomas (2014 - 2016) were retrospectively extracted from the radiology database. Exclusion criteria were history of cancer, suspected functioning adrenal tumor, dominant nodule size < 1 cm or ≥ 4 cm, myelolipomas, cysts, and hematomas. Multivariable logistic regression models were employed to predict follow-up imaging (FUI) and hormonal screening orders as a function of patient age and sex, nodule size, and CAR/DS use. CAR/DS reports were compared to conventional reports regarding ordering provider compliance with, frequency, and completeness of, guideline-warranted recommendations for FUI and hormonal screening of adrenal incidentalomas using Chi-square test.

RESULT

Of 174 patients (mean age 62.4; 51.1% women) with adrenal incidentalomas, 62% (108/174) received CAR/DS-based recommendations versus 38% (66/174) unassisted recommendations. CAR/DS use was an independent predictor of provider compliance both with FUI (Odds Ratio [OR]=2.47, p = 0.02) and hormonal screening (OR=2.38, p = 0.04). CAR/DS reports recommended FUI (97.2%,105/108) and hormonal screening (87.0%,94/108) more often than conventional reports (respectively, 69.7% [46/66], 3.0% [2/66], both p <0.0001). CAR/DS recommendations more frequently included instructions for FUI time, protocol, and modality than conventional reports (all p <0.001).

CONCLUSION

Ordering providers were at least twice as likely to comply with report recommendations for FUI and hormonal evaluation of adrenal incidentalomas generated using CAR/DS versus unassisted reporting. CAR/DS-directed recommendations were more adherent to guidelines than those generated without.

Computed Tomography-Based Machine Learning Differentiates Adrenal Pheochromocytoma From Lipid-Poor Adenoma

OBJECTIVES

To assess the accuracy of computed tomography (CT)-based machine learning models for differentiating subclinical pheochromocytoma (sPHEO) from lipid-poor adenoma (LPA) in patients with adrenal incidentalomas.

PATIENTS AND METHODS

The study included 188 tumors in the 183 patients with LPA and 92 tumors in 86 patients with sPHEO. Pre-enhanced CT imaging features of the tumors were evaluated. Machine learning prediction models and scoring systems for differentiating sPHEO from LPA were built using logistic regression (LR), support vector machine (SVM) and random forest (RF) approaches.

RESULTS

The LR model performed better than other models. The LR model (M1) including three CT features: CT_pre value, shape, and necrosis/cystic changes had an area under the receiver operating characteristic curve (AUC) of 0.917 and an accuracy of 0.864. The LR model (M2) including three CT features: CT_pre value, shape and homogeneity had an AUC of 0.888 and an accuracy of 0.832. The S2 scoring system (sensitivity: 0.859, specificity: 0.824) had comparable diagnostic value to S1 (sensitivity: 0.815; specificity: 0.910).

CONCLUSIONS

Our results indicated the potential of using a non-invasive imaging method such as CT-based machine learning models and scoring systems for predicting histology of adrenal incidentalomas. This approach may assist the diagnosis and personalized care of patients with adrenal tumors.

[Spontaneous adrenal hematomas. Retrospective analysis of 20 cases from a tertiary center]

INTRODUCTION

Spontaneous adrenal hemorrhages (AH) are a rare condition with no consensus about their management.

METHODS

Patients were identified using the Medicalization of the Information System Program database, imaging software and a call for observations to internists, intensivists and obsetricians working at our institution. Adult patients whose medical records were complete and whose diagnosis was confirmed by medical imaging were included.

RESULTS

From 2000 to 2007, 20 patients were identified, including 15 were women. The clinical onset of AH was non-specific. In five cases, AH occurred during pregnancy; four of them were unilateral and right sided. The etiology of the other fifteen (bilateral adrenal hemorrhage in 11) were as follows: antiphospholipid syndrome (n=8), heparin-induced thrombocytopenia (n=4), essential thrombocythemia (n=3), spontaneous AH due to oral anticoagulants (n=1), complication of a surgical act (n=3), and sepsis (n=3). In seven cases, two causes were concomitant. The diagnosis of AH was often confirmed by abdominal CT. An anticoagulant treatment was initiated in 16 cases. Ten of the eleven patients presenting with bilateral adrenal hematomas were treated using a long-term substitute opotherapy. One patient died because of a catastrophic antiphospholipid syndrome.

CONCLUSION

The clinical onset of HS is heterogeneous and non-specific. The confirmatory diagnosis is often based on abdominal CT. The search for an underlying acquired thrombophilia is essential and we found in this study etiological data comparable to the main series in the literature. Adrenal insufficiency is most of the time definitive in cases of bilateral involvement.

Implications of Conversion during Attempted Minimally Invasive Adrenalectomy for Adrenocortical Carcinoma

BACKGROUND

Although advocated by some, minimally invasive adrenalectomy (MIA) for adrenocortical carcinoma (ACC) is controversial. Moreover, the oncologic implications for patients requiring conversion to an open procedure during attempted MIA for ACC are not extensively reported.

PATIENTS AND METHODS

The National Cancer Database was queried for patients undergoing resection for ACC. Overall survival (OS) for patients undergoing successful MIA was compared with those requiring conversion, and additionally evaluated with a multivariable Cox regression analysis including other factors associated with OS. After propensity matching, those experiencing conversion were further compared with patients who underwent planned open resection.

RESULTS

Among 196 patients undergoing attempted MIA for ACC, 38 (19.4%) required conversion. Independent of 90-day postoperative mortality, conversion was associated with significantly reduced OS compared with successful MIA (median 27.9 months versus not reached, p = 0.002). Even for tumors confined to the adrenal, conversion was associated with worse median OS compared with successful MIA (median 34.2 months versus not reached, p = 0.003). After propensity matching for clinicopathologic covariates to establish well-balanced cohorts (N = 38 per group), patients requiring conversion during MIA had significantly worse OS than those having planned open resection (27.9 months versus 50.5 months, p = 0.020). On multivariable analysis for predictors of OS, conversion during MIA (HR 2.32, p = 0.003) was independently associated with mortality.

CONCLUSIONS

ACC is a rare tumor for which adequate oncologic resection is the only chance for cure. Given the relatively high rate of conversion and its associated inferior survival, open resection should be considered standard of care for known or suspected ACC.

Sonographic appearances of adrenal schwannomas

OBJECTIVE

To evaluate the sonographic ultrasound (US) appearances of adrenal gland schwannomas.

MATERIALS AND METHODS

This was a retrospective analysis of 15 cases of schwannomas involving the adrenal gland. The following US features were assessed: size, border, echogenicity, homogeneity, intralesional cystic necrosis, presence of septa, intralesional calcification, posterior acoustic enhancement and blood supply.

RESULTS

Of the 15 tumors, seven (46.7%) were located on the left side, and the remaining eight (53.3%) on the right side. The most frequent US appearance of adrenal schwannoma was a single, well-defined and isoechoic mass. The internal echotexture was homogeneous in 2 cases, and heterogeneous in 13 cases, with intralesional cystic areas (n = 11), septa (n = 10) or calcifications (n = 6). Posterior acoustic enhancement was seen in 12 of the 15 cases (80%). On color Doppler US, 86.7% (13/15) of the lesions did not show any vascularity.

CONCLUSIONS

Adrenal schwannomas usually present on US as well-defined isoechoic masses often with posterior acoustic enhancement, cystic necrosis with septa and poor blood supply. These appearances should suggest the diagnosis of adrenal schwannomas. Nevertheless, additional information from laboratory tests and CT or MR imaging may be required to avoid unnecessary surgery.

Radiomics improves efficiency for differentiating subclinical pheochromocytoma from lipid-poor adenoma: a predictive, preventive and personalized medical approach in adrenal incidentalomas

Objectives

This study aims to define a radiomic signature for pre-operative differentiation between subclinical pheochromocytoma (sPHEO) and lipid-poor adrenal adenoma (LPA) in adrenal incidentaloma. The goal was to apply a predictive, preventive, and personalized medical approach to the management of adrenal tumors.

Patients and methods

This retrospective study consisted of 265 consecutive patients (training cohort, 212 (LPA, 145; sPHEO, 67); validation cohort, 53 (LPA, 36; sPHEO, 17)). Computed tomography (CT) imaging features were evaluated, including long diameter (LD), short diameter (SD), pre-enhanced CT value (CT_pre), enhanced CT value (CT_post), shape, homogeneity, necrosis or cystic degeneration (N/C). Radiomic features were extracted and then were used to construct a radiomic signature (Rad-score) and radiomic nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate their performance.

Results

Sixteen of three hundred forty candidate features were used to build a radiomic signature. The signature was significantly different between the sPHEO and LPA groups (AUC: training, 0.907; validation, 0.902). The radiomic nomogram based on enhanced CT features (M1) consisted of Rad-score, LD, SD, CT_pre, shape, homogeneity and N/C (AUC: training, 0.957; validation, 0.967). The pre-enhanced CT features based radiomic nomogram (M2) included Rad-score, LD, SD, CT_pre, shape, and homogeneity (AUC: training, 0.955; validation, 0.958).

Conclusions

Our radiomic nomograms based on pre-enhanced and enhanced CT images distinguished sPHEO from LPA. In addition, the promising result using pre-enhanced CT images for predictive diagnostics is important because patients could avoid the additional radiation and risk associated with enhanced CT.