Adrenocortical Adenoma Arising from Adrenohepatic Fusion: A Mimic of Hepatocellular Carcinoma-Case Report.

AIM: We present a case of adrenocortical adenoma originating from the adrenohepatic fusion (AHF) region, accompanied by advanced hepatosteatosis in the liver tissue, and discuss its distinction from hepatocellular carcinoma.  Case Experience: A 68-year-old male patient was admitted to the hospital following a fall from a height. He was referred to our hospital after an incidental discovery of a liver mass during an abdominal ultrasound examination. Subsequently, magnetic resonance imaging (MRI) imaging was conducted, followed by segmental liver resection with right adrenalectomy, and histological analysis of a biopsy from the lesion.  Results: Upon histologic examination, the case was determined to be an adrenocortical adenoma originating from the AHF.  Discussion: Adrenohepatic fusion (AHF) denotes the histological amalgamation of cells from the right adrenal cortex and right hepatic parenchyma. Only a limited number of cases of neoplasia originating from this region have been documented. These rare instances often present a diagnostic challenge, with preoperative imaging frequently misidentifying them as primary malignancies of either hepatic or adrenal origin, potentially leading to unnecessary extensive resections. The integration of immunohistochemical staining alongside clinical and radiological data proves helpful for accurately diagnosing this condition.  Conclusion: Awareness among clinicians, radiologists, and pathologists regarding the tumors that may arise from this region can mitigate the risk of performing extensive resections unnecessarily.

Steroid profiling in adrenal disease.

The measurement of steroid hormones in blood and urine, which reflects steroid biosynthesis and metabolism, has been recognized as a valuable tool for identifying and distinguishing steroidogenic disorders. The application of mass spectrometry enables the reliable and simultaneous analysis of large panels of steroids, ushering in a new era for diagnosing adrenal diseases. However, the interpretation of complex hormone results necessitates the expertise and experience of skilled clinicians. In this scenario, machine learning techniques are gaining worldwide attention within healthcare fields. The clinical values of combining mass spectrometry-based steroid profiles analysis with machine learning models, also known as steroid metabolomics, have been investigated for identifying and discriminating adrenal disorders such as adrenocortical carcinomas, adrenocortical adenomas, and congenital adrenal hyperplasia. This promising approach is expected to lead to enhanced clinical decision-making in the field of adrenal diseases. This review will focus on the clinical performances of steroid profiling, which is measured using mass spectrometry and analyzed by machine learning techniques, in the realm of decision-making for adrenal diseases.

Single-Nucleus Analysis Reveals Tumor Heterogeneity of Aldosterone-Producing Adenoma.

BACKGROUND: Recent advances in omics techniques have allowed detailed genetic characterization of aldosterone-producing adenoma (APA). The pathogenesis of APA is characterized by tumorigenesis-associated aldosterone synthesis. The pathophysiological intricacies of APAs have not yet been elucidated at the level of individual cells. Therefore, a single-cell level analysis is speculated to be valuable in studying the differentiation process of APA. METHODS: We conducted single-nucleus RNA sequencing of APAs with KCNJ5 mutation and nonfunctional adenomas obtained from 3 and 2 patients, respectively. RESULTS: The single-nucleus RNA sequencing revealed the intratumoral heterogeneity of APA and identified cell populations consisting of a shared cluster of nonfunctional adenoma and APA. In addition, we extracted 2 cell fates in APA and obtained a cell population specialized in aldosterone synthesis. Genes related to ribosomes and neurodegenerative diseases were upregulated in 1 of these fates, whereas those related to the regulation of glycolysis were upregulated in the other fate. Furthermore, the total RNA reads in the nucleus were higher in hormonally activated clusters, indicating a marked activation of transcription per cell. CONCLUSIONS: The single-nucleus RNA sequencing revealed intratumoral heterogeneity of APA with KCNJ5 mutation. The observation of 2 cell fates in KCNJ5-mutated APAs provides the postulation that a heterogeneous process of cellular differentiation was implicated in the pathophysiological mechanisms underlying APA tumors.

The new histological system for the diagnosis of adrenocortical cancer.

Introduction: Adrenocortical cancer (ACC) is a rare malignant tumor that originates in the adrenal cortex. Despite extensive molecular-genetic, pathomorphological, and clinical research, assessing the malignant potential of adrenal neoplasms in clinical practice remains a daunting task in histological diagnosis. Although the Weiss score is the most prevalent method for diagnosing ACC, its limitations necessitate additional algorithms for specific histological variants. Unequal diagnostic value, subjectivity in evaluation, and interpretation challenges contribute to a gray zone where the reliable assessment of a tumor's malignant potential is unattainable. In this study, we introduce a universal mathematical model for the differential diagnosis of all morphological types of ACC in adults. Methods: This model was developed by analyzing a retrospective sample of data from 143 patients who underwent histological and immunohistochemical examinations of surgically removed adrenal neoplasms. Statistical analysis was carried out on Python 3.1 in the Google Colab environment. The cutting point was chosen according to Youden's index. Scikit-learn 1.0.2 was used for building the multidimensional model for Python. Logistical regression analysis was executed with L1-regularization, which is an effective method for extracting the most significant features of the model. Results: The new system we have developed is a diagnostically meaningful set of indicators that takes into account a smaller number of criteria from the currently used Weiss scale. To validate the obtained model, we divided the initial sample set into training and test sets in a 9:1 ratio, respectively. The diagnostic algorithm is highly accurate [overall accuracy 100% (95% CI: 96%-100%)]. Discussion: Our method involves determining eight diagnostically significant indicators that enable the calculation of ACC development probability using specified formulas. This approach may potentially enhance diagnostic precision and facilitate improved clinical outcomes in ACC management.

Deep learning approach for differentiating indeterminate adrenal masses using CT imaging.

PURPOSE: Distinguishing stage 1-2 adrenocortical carcinoma (ACC) and large, lipid poor adrenal adenoma (LPAA) via imaging is challenging due to overlapping imaging characteristics. This study investigated the ability of deep learning to distinguish ACC and LPAA on single time-point CT images. METHODS: Retrospective cohort study from 1994 to 2022. Imaging studies of patients with adrenal masses who had available adequate CT studies and histology as the reference standard by method of adrenal biopsy and/or adrenalectomy were included as well as four patients with LPAA determined by stability or regression on follow-up imaging. Forty-eight (48) subjects with pathology-proven, stage 1-2 ACC and 43 subjects with adrenal adenoma >3 cm in size demonstrating a mean non-contrast CT attenuation > 20 Hounsfield Units centrally were included. We used annotated single time-point contrast-enhanced CT images of these adrenal masses as input to a 3D Densenet121 model for classifying as ACC or LPAA with five-fold cross-validation. For each fold, two checkpoints were reported, highest accuracy with highest sensitivity (accuracy focused) and highest sensitivity with the highest accuracy (sensitivity focused). RESULTS: We trained a deep learning model (3D Densenet121) to predict ACC versus LPAA. The sensitivity-focused model achieved mean accuracy: 87.2% and mean sensitivity: 100%. The accuracy-focused model achieved mean accuracy: 91% and mean sensitivity: 96%. CONCLUSION: Deep learning demonstrates promising results distinguishing between ACC and large LPAA using single time-point CT images. Before being widely adopted in clinical practice, multicentric and external validation are needed.

A Rare Case of Primary Adrenal Epithelioid Angiosarcoma.

BACKGROUND Primary adrenal epithelioid angiosarcoma (PAEA) is a very uncommon primary adrenal gland tumor that usually occurs around the age of 60 years and is more common among males. Owing to its rarity and histopathological features, PAEA could be misdiagnosed as adrenal cortical adenoma, adrenal cortical carcinoma, or other metastatic cancers, such as metastatic malignant melanoma and epithelioid hemangioendothelioma. CASE REPORT A 59-year-old male patient presented to our hospital with a complaint of abdominal bloating that started 2 months prior. His vital signs and the results of his physical and neurological examinations were unremarkable. A computed tomography scan showed a lobulated mass arising from the hepatic limb of the right adrenal gland but no evidence of metastasis to the chest or abdomen. The patient underwent right adrenalectomy, and the macroscopic pathological findings from a right adrenalectomy specimen revealed atypical tumor cells with an epithelioid appearance in the background of an adrenal cortical adenoma. Immunohistochemical staining was performed to confirm the diagnosis. The final diagnosis was epithelioid angiosarcoma involving the right adrenal gland with a background adrenal cortical adenoma. The patient had no postoperative complications, pain in the surgical wound, or fever. Therefore, he was discharged with a schedule for followup appointments. CONCLUSIONS PAEA may be misinterpreted as adrenal cortical carcinoma, metastatic carcinoma, or malignant melanoma radiologically and histologically. Immunohistochemical stains are essential for diagnosing PAEA. Surgery and strict monitoring are the main treatments. In addition, early diagnosis is essential for patient recovery.

Diagnostic accuracy of using multiple cytokines to predict aldosterone-producing adenoma.

Here, we aimed to study the important cytokines in plasma to identify the aldosterone-producing adenoma (APA). 19 unilateral primary aldosteronism (UPA) patients and 19 healthy people were divided into UPA group and Control group, and the serum of bilateral adrenal veins and inferior vena cava collected by adrenal blood sampling (AVS) in UPA patients and the serum from the healthy subjects were all used to detect multiple cytokines by Luminex immunoassays. Additionally, The UPA patients subjected to laparoscopic adrenalectomy were divided into different groups by pathological results for further study. According our results, IP-10, CXCL9 and RANTES were significantly higher in UPA group compared with control group, and the combination of the three cytokines have significant predictive power for predicting UPA, while the correlational analyses demonstrated that IP-10 and CXCL9 were positively correlated with BP and HR, while EGF was positively correlated with HDL. Additionally, IL-1b was suggested to be the most potential diagnostic biomarker to discriminate the APA and unilateral adrenal hyperplasia (UAH). The present findings might suggest a possibility of IP-10, CXCL9 and RANTES served as a sign to help UPA diagnosis and finally used to assist the diagnosis of APA, while IL-1b was suggested to be the most potential diagnostic biomarker to identify the APA from the UAH patients.

[Adrenohepatic fusion - an unknown but not uncommon phenomenon of clinical importance]. / Adrenohepatisk fusion ­ ett okänt fenomen med klinisk betydelse.

Adrenohepatic fusion (AHF) is a union of the right adrenal gland and the liver with intermingling of parenchymal adrenal and liver cells. The phenomenon can be of clinical importance when evaluating patients with adrenal tumors. Using conventional imaging techniques such as computed tomography, a benign adrenal adenoma developing in an adrenohepatic fusion may mimic an invasive hepatocellular carcinoma or adrenal cortical carcinoma. This study presents a comprehensive review of the literature and shows a prevalence of 5.6 percent in autopsy studies. Moreover, 19 patients with adrenal masses in AHF are presented together with their clinical data.

Rare benign adrenal lesions.

While most benign lesions of the adrenal glands represent either an adrenocortical adenoma or a myelolipoma, the advent and frequent use of high-resolution radiological investigations have led to relatively increased incidental discovery of rare adrenal lesions, specifically benign adrenal cysts, adrenal ganglioneuromas, adrenal schwannomas, adrenal hemorrhage, and adrenal calcifications. Radiological characteristics of the different rare benign adrenal lesions could vary from distinct to indeterminate. Though typically nonfunctional, these rare lesions require evaluation for adrenal hormone excess, as they may phenotypically appear similar to pheochromocytoma or adrenocortical carcinoma and could sometimes be associated with or conceal an underlying functional adrenal tumor. In this review, we discuss the various rare benign adrenal lesions, emphasizing a practical perspective.

Simplified urinary steroid profiling by LC-MS as diagnostic tool for malignancy in adrenocortical tumors.

OBJECTIVES: Preoperative identification of malignant adrenal tumors is challenging. 24-h urinary steroid profiling by LC-MS/MS and machine learning has demonstrated high diagnostic power, but the unavailability of bioinformatic models for public use has limited its routine application. We here aimed to increase usability with a novel classification model for the differentiation of adrenocortical adenoma (ACA) and adrenocortical carcinoma (ACC). METHODS: Eleven steroids (5-pregnenetriol, dehydroepiandrosterone, cortisone, cortisol, α-cortolone, tetrahydro-11-deoxycortisol, etiocholanolone, pregnenolone, pregnanetriol, pregnanediol, and 5-pregnenediol) were quantified by LC-MS/MS in 24-h urine samples from 352 patients with adrenal tumor (281 ACA, 71 ACC). Random forest modelling and decision tree algorithms were applied in training (n = 188) and test sets (n = 80) and independently validated in 84 patients with paired 24-h and spot urine. RESULTS: After examining different models, a decision tree using excretions of only 5-pregnenetriol and tetrahydro-11-deoxycortisol classified three groups with low, intermediate, and high risk for malignancy. 148/217 ACA were classified as being at low, 67 intermediate, and 2 high risk of malignancy. Conversely, none of the ACC demonstrated a low-risk profile leading to a negative predictive value of 100% for malignancy. In the independent validation cohort, the negative predictive value was again 100% in both 24-h urine and spot urine with a positive predictive value of 87.5% and 86.7%, respectively. CONCLUSIONS: This simplified LC-MS/MS-based classification model using 24-h-urine provided excellent results for exclusion of ACC and can help to avoid unnecessary surgeries. Analysis of spot urine led to similarly satisfactory results suggesting that cumbersome 24-h urine collection might be dispensable after future validation.

Different cell compositions and a novel somatic KCNJ5 variant found in a patient with bilateral adrenocortical adenomas secreting aldosterone and cortisol.

Introduction: This study aimed to explore the possible pathogenesis of a rare case of co-existing Cushing's syndrome (CS) and primary aldosteronism (PA) caused by bilateral adrenocortical adenomas secreting aldosterone and cortisol, respectively. Methods: A 41-year-old Chinese woman with severe hypertension and hypokalemia for 5 and 2 years, respectively, was referred to our hospital. She had a Cushingoid appearance. Preoperative endocrinological examinations revealed autonomous cortisol and aldosterone secretion. Computed tomography revealed bilateral adrenal adenomas. Subsequently, adrenal vein sampling and sequential left and right partial adrenalectomy indicated the presence of a left aldosterone-producing tumor and a right cortisol-producing tumor. Pathological examination included immunohistochemical analysis of the resected specimens. Secretions of aldosterone and cortisol were observed both in vivo and in vitro. Further, whole-exome sequencing was performed for DNA that was extracted from peripheral blood leukocytes and bilateral adrenal adenomas in order to determine whether the patient had relevant variants associated with PA and CS. Results: Immunohistochemical staining revealed that the left adenoma primarily comprised clear cells expressing CYP11B2, whereas the right adenoma comprised both eosinophilic compact and clear cells expressing CYP11B1. The mRNA levels of steroidogenic enzymes (including CYP11B1 and CYP17A1) were high in the right adenoma, whereas CYP11B2 was highly expressed in the left adenoma. A novel somatic heterozygous missense variant-KCNJ5 c.503T > G (p.L168R)-was detected in the left adrenal adenoma, but no other causative variants associated with PA and CS were detected in the peripheral blood or right adrenocortical adenoma. In the primary cell culture of the resected hyperplastic adrenal adenomas, verapamil and nifedipine, which are two calcium channel blockers, markedly inhibited the secretion of both aldosterone and cortisol. Conclusion: We present an extremely rare case of bilateral adrenocortical adenomas with distinct secretion of aldosterone and cortisol. The heterogeneity of the tumor cell compositions of aldosterone- and cortisol-producing adenoma (A/CPA) and somatic mutation of KCNJ5 may have led to different hormone secretions in the bilateral adrenal adenomas.

A Two-in-One Tumor in the Adrenal: A Functional Adrenocortical Adenoma with Myelolipomatous Differentiation.

BACKGROUND: Adrenocortical adenoma (ADA) and myelolipoma are two common benign neoplasms of the adrenal cortex that have been reported to occur together. CASE REPORT: A 14-year-old girl presented with the features of ACTH-independent endogenous Cushing syndrome. Abdominal CECT revealed a left adrenal 2.3 × 1.8 × 1.5 cm arterially enhancing nodular lesion with central hypodensity. Histologically, this was an ADA with oncocytic change and myelolipomatous differentiation/metaplasia. DISCUSSION/CONCLUSION: ADA with myelolipomatous differentiation/metaplasia can occur in the pediatric age group.

In Situ Metabolomics of Cortisol-Producing Adenomas.

BACKGROUND: Recent advances in omics techniques have allowed detailed genetic characterization of cortisol-producing adrenal adenoma (CPA). In contrast, the pathophysiology of CPAs has not been elucidated in detail on the level of tumor metabolic alterations. METHODS: The current study conducted a comprehensive mass spectrometry imaging (MSI) map of CPAs in relation to clinical phenotypes and immunohistochemical profiles of steroidogenic enzymes. The study cohort comprised 46 patients with adrenal tumors including CPAs (n 35) and nonfunctional adenomas (n 11). RESULTS: Severity of cortisol hypersecretion was significantly correlated with 29 metabolites (adjusted P 0.05). Adrenal androgens derived from the classic androgen pathway were inversely correlated with both cortisol secretion (rs 0.41, adjusted P 0.035) and CYP11B1 expression (rs 0.77, adjusted P 2.00E-08). The extent of cortisol excess and tumor CYP11B1 expression further correlated with serotonin (rs 0.48 and 0.62, adjusted P 0.008 and 2.41E-05). Tumor size was found to be correlated with abundance of 13 fatty acids (adjusted P 0.05) and negatively associated with 9 polyunsaturated fatty acids including phosphatidic acid 38:8 (rs 0.56, adjusted P 0.009). CONCLUSIONS: MSI reveals novel metabolic links between endocrine function and tumorigenesis, which will further support the understanding of CPA pathophysiology.

Vascular and hormonal interactions in the adrenal gland.

Primary aldosteronism is the most common form of secondary arterial hypertension, due to excessive aldosterone production from the adrenal gland. Although somatic mutations have been identified in aldosterone producing adenoma, the exact mechanisms leading to increased cell proliferation and nodule formation remain to be established. One hypothesis is that changes in vascular supply to the adrenal cortex, due to phenomena of atherosclerosis or high blood pressure, may influence the morphology of the adrenal cortex, resulting in a compensatory growth and nodule formation in response to local hypoxia. In this review, we will summarize our knowledge on the mechanisms regulating adrenal cortex development and function, describe adrenal vascularization in normal and pathological conditions and address the mechanisms allowing the cross-talk between the hormonal and vascular components to allow the extreme tissue plasticity of the adrenal cortex in response to endogenous and exogenous stimuli. We will then address recent evidence suggesting a role for alterations in the vascular compartment that could eventually be involved in nodule formation and the development of primary aldosteronism.

Altered expression of the IGF2­H19 locus and mitochondrial respiratory complexes in adrenocortical carcinoma.

Abnormalities of the insulin­like growth factor 2 (IGF2)­H19 locus with the overexpression of IGF2 are frequent findings in adrenocortical carcinoma (ACC). The present study assessed the expression of RNAs and microRNAs (miRNAs/miRs) from the IGF2­H19 locus using PCR­based methods in ACC and adrenocortical adenoma (ACA). The results were associated with proteomics data. IGF2 was overexpressed in ACC, and its expression correlated with that of miR­483­3p and miR­483­5p hosted by IGF2. The downregulated expression of H19 in ACC compared to ACA correlated with miR­675 expression hosted by H19. Several proteins exhibited an inverse correlation in expression and were predicted as targets of miR­483­3p, miR­483­5p or miR­675. Subsets of these proteins were differentially expressed between ACC and ACA. These included several proteins involved in mitochondrial metabolism. Among the mitochondrial respiratory complexes, complex I and IV were significantly decreased in ACC compared to ACA. The protein expression of NADH:ubiquinone oxidoreductase subunit C1 (NDUFC1), a subunit of mitochondrial respiratory complex I, was further validated as being lower in ACC compared to ACA and normal adrenals. The silencing of miR­483­5p increased NDUFC1 protein expression and reduced both oxygen consumption and glycolysis rates. On the whole, the findings of the present study reveal the dysregulation of the IGF2­H19 locus and mitochondrial respiration in ACC. These findings may provide a basis for the further understanding of the pathogenesis of ACC and may have potential values for diagnostics and treatment.

Diagnostic value of the relative enhancement ratio of the portal venous phase to unenhanced CT in the identification of lipid-poor adrenal tumors.

PURPOSE: Adrenal incidentalomas are common lesions found on abdominal imaging, most of which are lipid-rich adrenal adenomas. Imaging diagnoses differentiating lipid-poor adrenal adenomas (LPA) from non-adenomas (NA) are presently challenging to perform. The aim of the study was to investigate the diagnostic performance of the relative enhancement ratio parameter in identifying LPA from NA. METHODS: We retrospectively evaluated consecutively presenting patients with lipid-poor adrenal lesions (January 2015 to August 2021). Lesions were divided into LPA and NA (including hyperenhancing and hypoenhancing NA). Kruskal-Wallis and Bonferroni tests were used to determine the differences in feature parameters between these three groups. Receiver operating characteristic curve analysis was performed to determine the sensitivity for diagnosing LPA and NA at 95% specificity; the parameters were compared using the McNemar test. RESULTS: A total of 253 patients (mean age, 55 ± 12 years; 135 men), 121 with LPA and 132 with NA, were analyzed herein. The sensitivity (achieved at 95% specificity) of the relative enhancement ratio was higher than that of unenhanced attenuation in differentiating LPA from NA (60% vs. 52%, p = 0.064). The relative enhancement ratio yielded a higher sensitivity than unenhanced attenuation (79% vs. 59%, p < 0.001) in differentiating LPA from hypoenhancing NA, and a lower sensitivity (26% vs. 69%, p < 0.001) in differentiating LPA from hyperenhancing NA. CONCLUSION: The relative enhancement ratio showed better diagnostic performance than unenhanced attenuation in differentiating LPA from hypoenhancing NA, while simultaneously showing poor diagnostic performance in identifying LPA from all NA.

Histopathology and Genetic Causes of Primary Aldosteronism in Young Adults.

CONTEXT: Due to its rare incidence, molecular features of primary aldosteronism (PA) in young adults are largely unknown. Recently developed targeted mutational analysis identified aldosterone-driver somatic mutations in aldosterone-producing lesions, including aldosterone-producing adenomas (APAs), aldosterone-producing nodules (APNs), and aldosterone-producing micronodules, formerly known as aldosterone-producing cell clusters. OBJECTIVE: To investigate histologic and genetic characteristics of lateralized PA in young adults. METHODS: Formalin-fixed, paraffin-embedded adrenal tissue sections from 74 young patients with lateralized PA (<35 years old) were used for this study. Immunohistochemistry (IHC) for aldosterone synthase (CYP11B2) was performed to define the histopathologic diagnosis. Somatic mutations in aldosterone-producing lesions were further determined by CYP11B2 IHC-guided DNA sequencing. RESULTS: Based on the CYP11B2 IHC results, histopathologic classification was made as follows: 48 APAs, 20 APNs, 2 multiple aldosterone-producing nodules (MAPN), 1 double APN, 1 APA with MAPN, and 2 nonfunctioning adenomas (NFAs). Of 45 APAs with successful sequencing, 43 (96%) had somatic mutations, with KCNJ5 mutations being the most common genetic cause of young-onset APA (35/45, 78%). Of 18 APNs with successful sequencing, all of them harbored somatic mutations, with CACNA1D mutations being the most frequent genetic alteration in young-onset APN (8/18, 44%). Multiple CYP11B2-expressing lesions in patients with MAPN showed several aldosterone-driver mutations. No somatic mutations were identified in NFAs. CONCLUSION: APA is the most common histologic feature of lateralized PA in young adults. Somatic KCNJ5 mutations are common in APAs, whereas CACNA1D mutations are often seen in APNs in this young PA population.

Inter-individual comparison of diagnostic accuracy of adrenal washout CT compared to chemical shift MRI plus the T2-weighted (T2W) adrenal MRI calculator in indeterminate adrenal masses: a retrospective non-inferiority study.

OBJECTIVE: To compare diagnostic accuracy of washout (WO)-CT to chemical shift (CS)-MRI + T2W adrenal MRI Calculator (T2W-Calculator) to diagnose adrenal adenoma in indeterminate adrenal masses. METHODS: This retrospective, cross-sectional, non-inferiority study evaluated 40 consecutive indeterminate adrenal masses; each with WO-CT and MRI. Two blinded radiologists independently evaluated in mixed order: pre-contrast attenuation (Hounsfield Units, HU) and absolute WO ([Peak.HU-Delay.HU]/[Peak.HU-Pre.HU] × 100%), Chemical Shift Signal Intensity (CS-SI) Index, T2W SI ratio, and Entropy (which were imputed into the T2W-Calculator). Diagnostic accuracy for adrenal adenoma was tabulated using 2 × 2 tables. True -positive diagnoses of adenoma were CT = Pre-HU < 10 or absolute WO ≥ 60%, MRI = SI index ≥ 16.5% or T2W-Calculator < 0.631. RESULTS: There were 73% (29/40) adenomas and 27% (11/40) other masses (5 pheochromocytoma, 3 solitary fibrous tumor, 1 metastasis, 1 cavernous hemangioma, and 1 adrenocortical carcinoma). Sensitivity, specificity, and accuracy for diagnosis of adenoma using CT-WO were 78% (95% confidence intervals [CI] 56-93%), 35% (14-62%), and 57% (42-71%) Reader 1 and 72% (53-87%), 46% (17-77%), and 59% (41-76%) Reader 2. Sensitivity, specificity, and accuracy for diagnosis of adenoma using MRI were 100% (88-100%), 64% (34-90%), and 82% (67-97%) Reader 1 and 86% (68-96%), 73% (39-94%), and 80% (64-95%) Reader 2. MRI had higher overall accuracy (p = 0.02 Reader 1, 0.05 Reader 2) compared to CT-WO. CONCLUSION: Chemical shift MRI combined with the T2W adrenal MRI calculator is not inferior to CT Washout for diagnosis of adrenal adenoma among indeterminate adrenal masses.

Association of Nrf2 expression and mutation with Weiss and Helsinki scores in adrenocortical carcinoma.

Adrenocortical carcinoma (ACC) is a rare malignant tumor. Genetic abnormalities that may represent therapeutic targets and prognostic factors in ACC remain unclear. Besides being one of the main cellular defense mechanisms that regulates antioxidant pathways for detoxifying reactive oxygen species (ROS), the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) promotes tumor proliferation by increasing metabolic activity. In surgical specimens from 12 cases of nonmetastatic ACCs and nine cases of benign adrenocortical adenoma (ACA), we investigated gene mutation and protein expressions for Nrf2 and the preoperative maximum standard glucose uptake (SUVmax) on [18 F]fluorodeoxy-glucose positron emission tomography. Three of five ACCs with a Weiss score of 7 to 9 were Nrf2 mutants; these ACCs had higher expression of Nrf2 and higher preoperative SUVmax. The other seven ACCs had a Weiss score of 3 to 6; these seven ACCs and all the ACAs were non-Nrf2 gene mutants. Patients with a Weiss score of 7 to 9 and Nrf2 mutant ACC had shorter overall survival. Based on Helsinki scoring, three ACCs with a Helsinki score greater than 17 had Nrf2 mutants, higher expression of Nrf2, higher preoperative SUVmax, and shorter overall survival. Our findings indicate that Nrf2 activation and the associated increase in metabolism play roles in ACC, in particular in ACC with a Weiss score of 7 to 9 and a Helsinki score of greater than 17.

Overview of the 2022 WHO Classification of Adrenal Cortical Tumors.

The new WHO classification of adrenal cortical proliferations reflects translational advances in the fields of endocrine pathology, oncology and molecular biology. By adopting a question-answer framework, this review highlights advances in knowledge of histological features, ancillary studies, and associated genetic findings that increase the understanding of the adrenal cortex pathologies that are now reflected in the 2022 WHO classification. The pathological correlates of adrenal cortical proliferations include diffuse adrenal cortical hyperplasia, adrenal cortical nodular disease, adrenal cortical adenomas and adrenal cortical carcinomas. Understanding germline susceptibility and the clonal-neoplastic nature of individual adrenal cortical nodules in primary bilateral macronodular adrenal cortical disease, and recognition of the clonal-neoplastic nature of incidentally discovered non-functional subcentimeter benign adrenal cortical nodules has led to redefining the spectrum of adrenal cortical nodular disease. As a consequence, the most significant nomenclature change in the field of adrenal cortical pathology involves the refined classification of adrenal cortical nodular disease which now includes (a) sporadic nodular adrenocortical disease, (b) bilateral micronodular adrenal cortical disease, and (c) bilateral macronodular adrenal cortical disease (formerly known primary bilateral macronodular adrenal cortical hyperplasia). This group of clinicopathological entities are reflected in functional adrenal cortical pathologies. Aldosterone producing cortical lesions can be unifocal or multifocal, and may be bilateral with no imaging-detected nodule(s). Furthermore, not all grossly or radiologically identified adrenal cortical lesions may be the source of aldosterone excess. For this reason, the new WHO classification endorses the nomenclature of the HISTALDO classification which uses CYP11B2 immunohistochemistry to identify functional sites of aldosterone production to help predict the risk of bilateral disease in primary aldosteronism. Adrenal cortical carcinomas are subtyped based on their morphological features to include conventional, oncocytic, myxoid, and sarcomatoid subtypes. Although the classic histopathologic criteria for diagnosing adrenal cortical carcinomas have not changed, the 2022 WHO classification underscores the diagnostic and prognostic impact of angioinvasion (vascular invasion) in these tumors. Microscopic angioinvasion is defined as tumor cells invading through a vessel wall and forming a thrombus/fibrin-tumor complex or intravascular tumor cells admixed with platelet thrombus/fibrin. In addition to well-established Weiss and modified Weiss scoring systems, the new WHO classification also expands on the use of other multiparameter diagnostic algorithms (reticulin algorithm, Lin-Weiss-Bisceglia system, and Helsinki scoring system) to assist the workup of adrenal cortical neoplasms in adults. Accordingly, conventional carcinomas can be assessed using all multiparameter diagnostic schemes, whereas oncocytic neoplasms can be assessed using the Lin-Weiss-Bisceglia system, reticulin algorithm and Helsinki scoring system. Pediatric adrenal cortical neoplasms are assessed using the Wieneke system. Most adult adrenal cortical carcinomas show > 5 mitoses per 10 mm2 and > 5% Ki67. The 2022 WHO classification places an emphasis on an accurate assessment of tumor proliferation rate using both the mitotic count (mitoses per 10 mm2) and Ki67 labeling index which play an essential role in the dynamic risk stratification of affected patients. Low grade carcinomas have mitotic rate of ≤ 20 mitoses per 10 mm2, whereas high-grade carcinomas show > 20 mitoses per 10 mm2. Ki67-based tumor grading has not been endorsed in the new WHO classification, since the proliferation indices are continuous variables rather than being static thresholds in tumor biology. This new WHO classification emphasizes the role of diagnostic and predictive biomarkers in the workup of adrenal cortical neoplasms. Confirmation of the adrenal cortical origin of a tumor remains a critical requirement when dealing with non-functional lesions in the adrenal gland which may be mistaken for a primary adrenal cortical neoplasm. While SF1 is the most reliable biomarker in the confirmation of adrenal cortical origin, paranuclear IGF2 expression is a useful biomarker in the distinction of malignancy in adrenal cortical neoplasms. In addition to adrenal myelolipoma, the new classification of adrenal cortical tumors has introduced new sections including adrenal ectopia, based on the potential role of such ectopic tissue as a possible source of neoplastic proliferations as well as a potential mimicker of metastatic disease. Adrenal cysts are also discussed in the new classification as they may simulate primary cystic adrenal neoplasms or even adrenal cortical carcinomas in the setting of an adrenal pseudocyst.