Adrenocortical hyperplasia: a review of clinical presentation and imaging

The molecular genetics of adrenal cushing

Adrenal Cushing represents 20% of cases of endogenous hypercorticism. Unilateral cortisol-producing adenoma (CPA), a benign tumor, and adrenocortical carcinoma (ACC), a malignant tumor, are more frequent than bilateral adrenal nodular diseases (primary bilateral macronodular adrenal hyperplasia (PBMAH) and primary pigmented nodular adrenal disease (PPNAD)).In cortisol-producing adrenal tumors, the signaling pathways mainly altered are the protein kinase A and Wnt/β-catenin pathways. Studying components of these pathways and exploring syndromic and familial cases of these tumors has historically enabled identification of many of the predisposing genes. More recently, pangenomic sequencing revealed alterations in sporadic tumors.In ACC, mainly due to TP53 alterations causing Li-Fraumeni syndrome, germline predisposition is frequent in children, while it is rare in adults. Pathogenic variants in the DNA mismatch repair genes MLH1, MSH2, MSH6, and PMS2, which cause Lynch syndrome or alterations of IGF2 and CDKN1C (11p15 locus) in Beckwith-Wiedemann syndrome, can also cause ACC. Rarely, ACC is described in other hereditary tumor syndromes due to germline pathogenic variants in MEN1 or APC and, in very rare cases, NF1, SDH, PRKAR1A, or BRCA2. Concerning ACC somatic alterations, TP53 and genetic or epigenetic alterations at the 11p15 locus are also frequently described, as well as CTNNB1 and ZNRF3 pathogenic variants.CPAs mainly harbor somatic pathogenic variants in PRKACA and CTNNB1 and, less frequently, PRKAR1A, PRKACB, or GNAS1 pathogenic variants. Isolated PBMAH is due to ARMC5 inactivating pathogenic variants in 20 to 25% of cases and to KDM1A pathogenic variants in food-dependent Cushing. Syndromic PBMAH may be due to germline pathogenic variants in MEN1, APC, or FH, causing type 1 multiple endocrine neoplasia, familial adenomatous polyposis, or hereditary leiomyomatosis-kidney cancer syndrome, respectively. PRKAR1A germline pathogenic variants are the main alteration causing PPNAD (isolated or part of Carney complex).

Differentiate adrenal lipid-poor adenoma from nodular hyperplasia with CT quantitative parameters: a feasibility study

OBJECTIVES

To explore the potential of CT quantitative parameters in differentiating adrenal lipid-poor adenoma (LPA) from nodular hyperplasia and evaluate diagnostic performance.

MATERIALS AND METHODS

Patients with LPA or nodular hyperplasia who underwent contrast-enhanced CT before adrenalectomy were analyzed retrospectively. The study included 128 patients (83 with LPA and 45 with nodular hyperplasia). Each lesion's unenhanced attenuation, portal-venous phase attenuation (CTp), and the portal-venous phase attenuation of the abdominal aorta were evaluated. We subsequently calculated absolute enhancement [a lesion's portal-venous phase attenuation minus unenhanced attenuation (in HUs)], relative enhancement (absolute enhancement divided by unenhanced attenuation), and the relative enhancement ratio [(absolute enhancement divided by abdominal aorta's portal-venous phase attenuation) ×100%]. Lesion number and size were recorded. Volume was assessed by ITK-snap software and the ratio of lesion volume to ipsilateral adrenal volume (volume ratio) was determined. Intergroup differences were analyzed using Student's t-test and chi-squared test. Logistic regression models were developed, and receiver operating characteristic (ROC) curves were constructed to determine the area under the ROC curve (AUC), sensitivity, and specificity. The model's performance was then compared against radiologists' subjective assessments, and the inter- and intra-reader agreement values among radiologists were calculated.

RESULTS

Portal-venous phase attenuation, volume ratio, and lesion number were independent predictors of LPA. The logistic regression model incorporating CTp, volume ratio, and lesion number achieved an AUC of 0.835, with a sensitivity of 73.5% and a specificity of 80.0%. The radiologists' diagnostic specificity and accuracy appeared to be inferior to the model. The inter-reader agreement among radiologists ranged from 0.082 to 0.535, and the intra-reader agreement of two radiologists were 0.734 and 0.583.

CONCLUSION

The portal-venous phase CT demonstrated potential in distinguishing LPA from nodular hyperplasia. The diagnostic performance of the model integrating CTp, volume ratio, and lesion number outperformed radiologists in terms of variability and reproducibility.

Adrenal Volume Quantitative Visualization Tool by Multiple Parameters and an nnU-Net Deep Learning Automatic Segmentation Model

Abnormalities in adrenal gland size may be associated with various diseases. Monitoring the volume of adrenal gland can provide a quantitative imaging indicator for such conditions as adrenal hyperplasia, adrenal adenoma, and adrenal cortical adenocarcinoma. However, current adrenal gland segmentation models have notable limitations in sample selection and imaging parameters, particularly the need for more training on low-dose imaging parameters, which limits the generalization ability of the models, restricting their widespread application in routine clinical practice. We developed a fully automated adrenal gland volume quantification and visualization tool based on the no new U-Net (nnU-Net) for the automatic segmentation of deep learning models to address these issues. We established this tool by using a large dataset with multiple parameters, machine types, radiation doses, slice thicknesses, scanning modes, phases, and adrenal gland morphologies to achieve high accuracy and broad adaptability. The tool can meet clinical needs such as screening, monitoring, and preoperative visualization assistance for adrenal gland diseases. Experimental results demonstrate that our model achieves an overall dice coefficient of 0.88 on all images and 0.87 on low-dose CT scans. Compared to other deep learning models and nnU-Net model tools, our model exhibits higher accuracy and broader adaptability in adrenal gland segmentation.

Imaging features of intra-abdominal and intra-pelvic causes of hirsutism

Hirsutism is a relatively common disorder which affects approximately 5% to 15% of women. It is defined by excessive growth of terminal hair in women, which primarily affects areas dependent on androgens, such as the face, abdomen, buttocks, and thighs. Hirsutism can be caused by a variety of etiologies, which are most often not lifethreatening. However, in some cases, hirsutism can be an indicator of more serious underlying pathology, such as a neoplasm, which may require further elucidation with imaging. Within the abdomen and pelvis, adrenal and ovarian pathologies are the primary consideration. The goal of this manuscript is to review the etiologies and imaging features of various intra-abdominal and intra-pelvic causes of hirsutism.

Three-dimensional CT cinematic rendering of adrenal masses: Role in tumor analysis and management

The adrenal gland is home to an array of complex physiological and neoplastic disease processes. While dedicated adrenal computed tomography (CT) is the gold standard imaging modality for adrenal lesions, there exists significant overlap among imaging features of adrenal pathology. This can often make radiological diagnosis and subsequent determination of the optimal surgical approach challenging. Cinematic rendering (CR) is a novel CT post-processing technique that utilizes advanced light modeling to generate highly photorealistic anatomic visualization. This generates unique prospects in the evaluation of adrenal masses. As one of the first large tertiary care centers to incorporate CR into routine diagnostic workup, our preliminary experience with using CR has been positive, and we have found CR to be a valuable adjunct during surgical planning. Herein, we highlight the unique utility of CR techniques in the workup of adrenal lesions and provide commentary on the opportunities and obstacles associated with the application of this novel display method in this setting.

Case report: Coexistence of Jacobs syndrome, congenital adrenal hyperplasia, and ambiguous genitalia in a male infant

Key Clinical Message

Jacobs syndrome and congenital adrenal hyperplasia are separate entities but share common clinical features such as ambiguous genitalia. Further studies are needed to conclude the relationship between Jacobs syndrome and congenital adrenal hyperplasia.

Abstract

A 5-month-old male infant was evaluated for ambiguous genitalia. Examination revealed cryptorchidism, inguinal hernia, long phallus, and Grade 3 scrotal hypospadias. Serum 17-OH progesterone was high and chromosomal analysis showed 47XYY/45XO. A diagnosis of Jacobs and CAH was made. The parents were counseled about the patient's condition. He was given hydrocortisone and referred to the pediatric surgeon for further management.

Bone age assessment from articular surface and epiphysis using deep neural networks

Bone age assessment is of great significance to genetic diagnosis and endocrine diseases. Traditional bone age diagnosis mainly relies on experienced radiologists to examine the regions of interest in hand radiography, but it is time-consuming and may even lead to a vast error between the diagnosis result and the reference. The existing computer-aided methods predict bone age based on general regions of interest but do not explore specific regions of interest in hand radiography. This paper aims to solve such problems by performing bone age prediction on the articular surface and epiphysis from hand radiography using deep convolutional neural networks. The articular surface and epiphysis datasets are established from the Radiological Society of North America (RSNA) pediatric bone age challenge, where the specific feature regions of the articular surface and epiphysis are manually segmented from hand radiography. Five convolutional neural networks, i.e., ResNet50, SENet, DenseNet-121, EfficientNet-b4, and CSPNet, are employed to improve the accuracy and efficiency of bone age diagnosis in clinical applications. Experiments show that the best-performing model can yield a mean absolute error (MAE) of 7.34 months on the proposed articular surface and epiphysis datasets, which is more accurate and fast than the radiologists. The project is available at https://github.com/YameiDeng/BAANet/, and the annotated dataset is also published at https://doi.org/10.5281/zenodo.7947923.

Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation

OBJECTIVE

This study aims to evaluate the morphometrics of normal adrenal glands in adult patients semiautomatically using a deep learning-based segmentation model.

MATERIALS AND METHODS

A total of 520 abdominal CT image series with normal findings, from January 1, 2016, to March 14, 2019, were retrospectively collected for the training of the adrenal segmentation model. Then, 1043 portal venous phase image series of inpatient contrast-enhanced abdominal CT examinations with normal adrenal glands were included for analysis and grouped by every 10-year gap. A 3D U-Net-based segmentation model was used to predict bilateral adrenal labels followed by manual modification of labels as appropriate. Quantitative parameters (volume, CT value, and diameters) of the bilateral adrenal glands were then analyzed.

RESULTS

In the study cohort aged 18-77 years old (554 males and 489 females), the left adrenal gland was significantly larger than the right adrenal gland [all patients, 2867.79 (2317.11-3499.89) mm³ vs. 2452.84 (1983.50-2935.18) mm³, P < 0.001]. Male patients showed a greater volume of bilateral adrenal glands than females in all age groups (all patients, left: 3237.83 ± 930.21 mm³ vs. 2646.49 ± 766.42 mm³, P < 0.001; right: 2731.69 ± 789.19 mm³ vs. 2266.18 ± 632.97 mm³, P = 0.001). Bilateral adrenal volume in male patients showed an increasing then decreasing trend as age increased that peaked at 38-47 years old (left: 3416.01 ± 886.21 mm³, right: 2855.04 ± 774.57 mm³).

CONCLUSIONS

The semiautomated measurement revealed that the adrenal volume differs as age increases. Male patients aged 38-47 years old have a peaked adrenal volume.

Imaging of pregnant and lactating patients with suspected adrenal disorders

A high level of clinical suspicion is essential in the diagnosis and management of a suspected adrenal mass during pregnancy and the peripartum period. Timely recognition is important in order to improve fetal and maternal outcomes. Imaging is often performed to confirm a suspected adrenal lesion; however, increasing usage of diagnostic imaging during pregnancy and lactation has also increased awareness, concerns and confusion regarding the safety risks regarding fetal and maternal exposure to radiation and imaging intravenous contrast agents. This may lead to anxiety and avoidance of imaging examinations which can delay diagnosis and appropriate treatment. This article briefly reviews evidence-based recommended imaging modalities during pregnancy and the lactation period for the assessment of a suspected adrenal mass while recognizing that no examination should be withheld when the exam is necessary to confirm an important clinical suspicion. The imaging characteristics of the more common adrenal pathologies that may affect pregnant women are also discussed.

Histopathologic Features of Adrenal Cortical Carcinoma

Adrenal cortical carcinoma (ACC) is a rare and aggressive malignancy that poses challenging issues regarding the diagnostic workup. Indeed, no presurgical technique or clinical parameters can reliably distinguish between adrenal cortical adenomas, which are more frequent and have a favorable outcome, and ACC, and the final diagnosis largely relies on histopathologic analysis of the surgical specimen. However, even the pathologic assessment of malignancy in an adrenal cortical lesion is not straightforward and requires a combined evaluation of multiple histopathologic features. Starting from the Weiss score, which was developed in 1984, several histopathologic scoring systems have been designed to tackle the difficulties of ACC diagnosis. Dealing with specific histopathologic variants (eg, Liss-Weiss-Bisceglia scoring system for oncocytic ACC) or patient characteristics (eg, Wieneke index in the pediatric setting), these scores remarkably improved the diagnostic workup of ACC and its subtypes. Nevertheless, cases with misleading features or discordant correlations between pathologic findings and clinical behavior still occur. Owing to multicentric collaborative studies integrating morphologic features with ancillary immunohistochemical markers and molecular analysis, ACC has eventually emerged as a multifaceted, heterogenous malignancy, and, while innovative and promising approaches are currently being tested, the future clinical management of patients with ACC will mainly rely on personalized medicine and target-therapy protocols. At the dawn of the new Fifth World Health Organization classification of endocrine tumors, this review will tackle ACC from the pathologist's perspective, thus focusing on the main available diagnostic, prognostic, and predictive tissue-tethered features and biomarkers and providing relevant clinical and molecular correlates.

Fully automatic volume measurement of the adrenal gland on CT using deep learning to classify adrenal hyperplasia

OBJECTIVES

To develop a fully automated deep learning model for adrenal segmentation and to evaluate its performance in classifying adrenal hyperplasia.

METHODS

This retrospective study evaluated automated adrenal segmentation in 308 abdominal CT scans from 48 patients with adrenal hyperplasia and 260 patients with normal glands from 2010 to 2021 (mean age, 42 years; 156 women). The dataset was split into training, validation, and test sets at a ratio of 6:2:2. Contrast-enhanced CT images and manually drawn adrenal gland masks were used to develop a U-Net-based segmentation model. Predicted adrenal volumes were obtained by fivefold splitting of the dataset without overlapping the test set. Adrenal volumes and anthropometric parameters (height, weight, and sex) were utilized to develop an algorithm to classify adrenal hyperplasia, using multilayer perceptron, support vector classification, a random forest classifier, and a decision tree classifier. To measure the performance of the developed model, the dice coefficient and intraclass correlation coefficient (ICC) were used for segmentation, and area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were used for classification.

RESULTS

The model for segmenting adrenal glands achieved a Dice coefficient of 0.7009 for 308 cases and an ICC of 0.91 (95% CI, 0.90-0.93) for adrenal volume. The models for classifying hyperplasia had the following results: AUC, 0.98-0.99; accuracy, 0.948-0.961; sensitivity, 0.750-0.813; and specificity, 0.973-1.000.

CONCLUSION

The proposed segmentation algorithm can accurately segment the adrenal glands on CT scans and may help clinicians identify possible cases of adrenal hyperplasia.

KEY POINTS

• A deep learning segmentation method can accurately segment the adrenal gland, which is a small organ, on CT scans. • The machine learning algorithm to classify adrenal hyperplasia using adrenal volume and anthropometric parameters (height, weight, and sex) showed good performance. • The proposed segmentation algorithm may help clinicians identify possible cases of adrenal hyperplasia.

Approach of Heterogeneous Spectrum Involving 3beta-Hydroxysteroid Dehydrogenase 2 Deficiency

We aim to review data on 3beta-hydroxysteroid dehydrogenase type II (3βHSD2) deficiency. We identified 30 studies within the last decade on PubMed: 1 longitudinal study (N = 14), 2 cross-sectional studies, 1 retrospective study (N = 16), and 26 case reports (total: 98 individuals). Regarding geographic area: Algeria (N = 14), Turkey (N = 31), China (2 case reports), Morocco (2 sisters), Anatolia (6 cases), and Italy (N = 1). Patients’ age varied from first days of life to puberty; the oldest was of 34 y. Majority forms displayed were salt-wasting (SW); some associated disorders of sexual development (DSD) were attendant also—mostly 46,XY males and mild virilisation in some 46,XX females. SW pushed forward an early diagnosis due to severity of SW crisis. The clinical spectrum goes to: premature puberty (80%); 9 with testicular adrenal rest tumours (TARTs); one female with ovarian adrenal rest tumours (OARTs), and some cases with adrenal hyperplasia; cardio-metabolic complications, including iatrogenic Cushing’ syndrome. More incidental (unusual) associations include: 1 subject with Barter syndrome, 1 Addison’s disease, 2 subjects of Klinefelter syndrome (47,XXY/46,XX, respective 47,XXY). Neonatal screening for 21OHD was the scenario of detection in some cases; 17OHP might be elevated due to peripheral production (pitfall for misdiagnosis of 21OHD). An ACTH stimulation test was used in 2 studies. Liquid chromatography tandem–mass spectrometry unequivocally sustains the diagnostic by expressing high baseline 17OH-pregnenolone to cortisol ratio as well as 11-oxyandrogen levels. HSD3B2 gene sequencing was provided in 26 articles; around 20 mutations were described as “novel pathogenic mutation” (frameshift, missense or nonsense); many subjects had a consanguineous background. The current COVID-19 pandemic showed that CAH-associated chronic adrenal insufficiency is at higher risk. Non-adherence to hormonal replacement contributed to TARTs growth, thus making them surgery candidates. To our knowledge, this is the largest study on published cases strictly concerning 3βHSD2 deficiency according to our methodology. Adequate case management underlines the recent shift from evidence-based medicine to individualized (patient-oriented) medicine, this approach being particularly applicable in this exceptional and challenging disorder.

Salt-Wasting Form of Congenital Adrenal Hyperplasia: A Case Report

Congenital adrenal hyperplasia (CAH) is a set of autosomal recessive disorders characterized by enzyme abnormalities in the adrenal steroidogenesis pathway, which cause impaired cortisol biosynthesis. Glucocorticoid, mineralocorticoid, and sex steroid production can all be altered in individuals, necessitating hormone replacement therapy. The symptoms might range from prenatal salt loss and abnormal genitalia to adult hirsutism and irregular menses. We present the case of a girl who presented with a seizure initially at the age of three months. Laboratory results revealed hypoglycemia, hyponatremia, and hyperkalemia with increased renin activity, increased adrenocorticotropic hormone (ACTH), low aldosterone, low cortisol, high dehydroepiandrosterone sulfate (DHEAS), and high 17 hydroxyprogesterone levels. Imaging findings were normal. The patient was managed with hydrocortisone and fludrocortisone. She is currently on regular follow-up and is doing well with dexamethasone therapy.

Adrenal Mass Characterization in the Era of Quantitative Imaging: State of the Art

Simple Summary

Non-invasive characterization of adrenal lesions requires a rigorous approach. Although CT is the cornerstone of adrenal lesion characterization, a multimodality multiparametric imaging approach helps improve confidence in adrenal lesion characterization.

Abstract

Detection and characterization of adrenal lesions have evolved during the past two decades. Although the role of imaging in adrenal lesions associated with hormonal secretion is usually straightforward, characterization of non-functioning adrenal lesions may be challenging to confidently identify those that need to be resected. Although many adrenal lesions can be readily diagnosed when they display typical imaging features, the diagnosis may be challenging for atypical lesions. Computed tomography (CT) remains the cornerstone of adrenal imaging, but other morphological or functional modalities can be used in combination to reach a diagnosis and avoid useless biopsy or surgery. Early- and delayed-phase contrast-enhanced CT images are essential for diagnosing lipid-poor adenoma. Ongoing studies are evaluating the capabilities of dual-energy CT to provide valid virtual non-contrast attenuation and iodine density measurements from contrast-enhanced examinations. Adrenal lesions with attenuation values between 10 and 30 Hounsfield units (HU) on unenhanced CT can be characterized by MRI when iodinated contrast material injection cannot be performed. ¹⁸F-FDG PET/CT helps differentiate between atypical benign and malignant adrenal lesions, with the adrenal-to-liver maximum standardized uptake value ratio being the most discriminative variable. Recent studies evaluating the capabilities of radiomics and artificial intelligence have shown encouraging results.

Spontaneously reversible adrenal nodules in primary diffuse large B-cell testicular lymphoma mimicking an extranodal involvement: A case report

In the staging of cancer patients, transient and spontaneously reversible bilateral adrenal hypertrophy may mimic a secondary localization of the disease. We discuss the case of an 82-year-old male patient with suspected testicular neoplasia in which abdominal CT examination reveals the onset of a bilateral macronodular adrenal enlargement, suggesting the diagnostic hypothesis of primary testicular neoplasia with secondary adrenal localization. The subsequent ¹⁸FDG-PET/CT study showed hyper-metabolism of the testicular mass, while the adrenal glands, surprisingly, did not show increased uptake of the radiotracer. After right orchifunicolectomy, primary testicular diffuse large B-cell lymphoma was diagnosed. The subsequent staging PET/CT study with iodine contrast medium, three months after the first CT examination, showed spontaneous complete regression of the adrenal hypertrophy without any use of drug therapy. The differential diagnosis of this finding considered the lack of hypermetabolism and the densitometric characteristics of the adrenal glands, the absence of possible pharmacological interactions throughout the time of the diagnostic procedures, and the available clinical-laboratory data. By excluding the main causes of adrenal hypertrophy, the most likely diagnostic hypothesis was transient adrenal hypertrophy due to stress induced by testicular lymphoma, meaning by stress a disturbance not only emotional but also an alteration of organic homeostasis. Our case suggests that the analysis of adrenal lesions appeared in cancer patients should take into account non-metastatic conditions that must be studied with a multimodal approach and with serial investigations.

Imaging of Adrenal-Related Endocrine Disorders

Endocrine disorders associated with adrenal pathologies can be caused by insufficient adrenal gland function or excess hormone secretion. Excess hormone secretion may result from adrenal hyperplasia or hormone-secreting (ie, functioning) adrenal masses. Based on the hormone type, functioning adrenal masses can be classified as cortisol-producing tumors, aldosterone producing tumors, and androgen-producing tumors, which originate in the adrenal cortex, as well as catecholamine-producing pheochromocytomas, which originate in the medulla. Nonfunctioning lesions can cause adrenal gland enlargement without causing hormonal imbalance. Evaluation of adrenal-related endocrine disorders requires clinical and biochemical workup associated with imaging evaluation to reach a diagnosis and guide management.

Imaging features of adrenal gland masses in the pediatric population

The spectrum of adrenal masses in the pediatric population markedly differs from that in the adult population. Imaging plays a crucial role in detecting adrenal masses, differentiating malignant from benign lesions, recognizing extra-adrenal lesions in the suprarenal fossa, and directing further management. Ultrasound is the primary imaging modality of choice for the evaluation of adrenal masses in the neonatal period, whereas MRI or CT is used as a problem-solving tool. In older children, computed tomography or magnetic resonance imaging is often required after initial sonographic evaluation for further characterization of a lesion. Herein, we discuss the salient imaging features along with pathophysiology and clinical features of pediatric adrenal masses.