Left-versus-right-adrenal-volume ratio as a screening index before adrenal venous sampling to identify unilateral primary aldosteronism patients

Asymmetric Adrenals: Sexual Dimorphism of Adrenal Tumors

CONTEXT

Sexual dimorphism has direct consequences on the incidence and survival of cancer. Early and accurate diagnosis is crucial to improve prognosis.

OBJECTIVE

This work aimed to characterized the influence of sex and adrenal asymmetry on the emergence of adrenal tumors.

METHODS

We conducted a multicenter, observational study involving 8037 patients with adrenal tumors, including adrenocortical carcinoma (ACC), aldosterone-producing adenoma (APA), cortisol-secreting adrenocortical adenomas (CSAs), non-aldosterone-producing adrenal cortical adenoma (NAPACA), pheochromocytoma (PCC), and neuroblastoma (NB), and investigated tumor lateralization according to sex. Human adrenal tissues (n = 20) were analyzed with a multiomics approach that allows determination of gene expression, catecholamine, and steroid contents in a single sample. In addition, we performed a literature review of computed tomography and magnetic resonance imaging-based studies examining adrenal gland size.

RESULTS

ACC (n = 1858); CSA (n = 68), NAPACA (n = 2174), and PCC (n = 1824) were more common in females than in males (female-to-male ratio: 1.1:1-3.8:1), whereas NBs (n = 2320) and APAs (n = 228) were less prevalent in females (0.8:1). ACC, APA, CSA, NAPACA, and NB occurred more frequently in the left than in the right adrenal (left-to-right ratio: 1.1:1-1.8:1), whereas PCC arose more often in the right than in the left adrenal (0.8:1). In both sexes, the left adrenal was larger than the right adrenal; females have smaller adrenals than males.

CONCLUSION

Adrenal asymmetry in both sexes may be related to the pathogenesis of adrenal tumors and should be considered during the diagnosis of these tumors.

Predicting Bilateral Subtypes of Primary Aldosteronism Without Adrenal Vein Sampling: A Systematic Review and Meta-analysis

CONTEXT

Primary aldosteronism (PA) is the most common endocrine cause of hypertension. The final diagnostic step involves subtyping, using adrenal vein sampling (AVS), to determine if PA is unilateral or bilateral. The complete PA diagnostic process is time and resource intensive, which can impact rates of diagnosis and treatment. Previous studies have developed tools to predict bilateral PA before AVS.

OBJECTIVE

Evaluate the sensitivity and specificity of published tools that aim to identify bilateral subtypes of PA.

METHODS

Medline and Embase databases were searched to identify published models that sought to subtype PA, and algorithms to predict bilateral PA are reported. Meta-analysis and meta-regression were then performed.

RESULTS

There were 35 studies included, evaluating 55 unique algorithms to predict bilateral PA. The algorithms were grouped into 6 categories: those combining biochemical, radiological, and demographic characteristics (A); confirmatory testing alone or combined with biochemical, radiological, and demographic characteristics (B); biochemistry results alone (C); adrenocorticotropic hormone stimulation testing (D); anatomical imaging (E); and functional imaging (F). Across the identified algorithms, sensitivity and specificity ranged from 5% to 100% and 36% to 100%, respectively. Meta-analysis of 30 unique predictive tools from 32 studies showed that the group A algorithms had the highest specificity for predicting bilateral PA, while group F had the highest sensitivity.

CONCLUSIONS

Despite the variability in published predictive algorithms, they are likely important for decision-making regarding the value of AVS. Prospective validation may enable medical treatment upfront for people with a high likelihood of bilateral PA without the need for an invasive and resource-intensive test.

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.

The performance of left/right adrenal volume ratio and volume difference in predicting unilateral primary aldosteronism

PURPOSE

The role of computed tomography (CT) in the diagnosis of primary aldosteronism (PA) warrants attention, since the success application of adrenal venous sampling (AVS) remains limited. We aimed to investigate the value of CT-based volumetric indicators, including left-versus-right-adrenal-volume ratio (L/Rv) and left-subtract-right-adrenal-volume difference (L - Rv), in the diagnosis of unilateral primary aldosteronism (UPA).

METHODS

A retrospective case-control study included 153 patients with PA and 1272 controls. AVS was used to classify patients into bilateral disease, left-sided disease, and right-sided disease groups.

RESULTS

Adrenal gland volume on both sides of PA patients was significantly larger than controls. The optimal cutoff values of L/Rv and L - Rv were 1.417 [area under the curve (AUC) 0.864] and 1.185 (AUC 0.827), respectively, for the diagnosis of left-sided PA, and 1.030 (AUC 0.767) and 0.220 (AUC 0.769), respectively, for the diagnosis of right-sided PA. The mean AUC for subsequent cross-validation ranged from 0.77 ± 0.03 to 0.86 ± 0.02. Based on the optimal cutoff values, the combination of L/Rv and L - Rv detected 69.6% of patients with left-sided PA and 74.3% of patients with right-sided PA, with a specificity of 93.5% and 89.0%, respectively. For a better clinical application, we reported the sub-optimal cutoffs corresponding to a specificity of 95%. A L/Rv higher than 1.431 and a L - Rv higher than 3.185 as sub-optimal cutoff values was detected in 26.1% of patients with left-sided PA (specificity: 97.2%). A L/Rv smaller than 0.892 and a L - Rv smaller than -0.640 could detect 48.6% of patients with right-sided PA (specificity: 97.5%).

CONCLUSIONS

CT-based L/Rv and L - Rv performed well in predicting UPA. The combination of L/Rv and L - Rv may serve as a potential indicator for guiding surgical decision making in centers without AVS programs.

Morphologically Normal-Appearing Adrenal Glands as a Prevalent Source of Aldosterone Production in Primary Aldosteronism

BACKGROUND

Normal-appearing adrenal glands on cross-sectional imaging may still be the source of aldosterone production in primary aldosteronism (PA).

METHODS

We evaluated the prevalence of aldosterone production among morphologically normal-appearing adrenal glands and the impact of this phenomenon on interpretations of localization studies and treatment decisions. We performed a retrospective cohort study of PA patients with at least 1 normal adrenal gland and reanalyzed contemporary studies to assess interpretations of imaging and adrenal venous sampling (AVS) at the individual patient and adrenal levels.

RESULTS

Among 243 patients, 43 (18%) had bilateral normal-appearing adrenals and 200 (82%) had a unilateral normal-appearing adrenal, for a total of 286 normal-appearing adrenal glands. 38% of these normal-appearing adrenal glands were a source of aldosteronism on AVS, resulting in discordance between imaging and AVS findings in 31% of patients. Most patients with lateralizing PA underwent curative unilateral treatment (80%); however, curative treatment was pursued in 92% of patients who had concordant imaging-AVS results but in only 38% who had discordant results (P < 0.05). In young patients, imaging-AVS discordance was detected in 32% of those under 45 years and 21% of those under 35 years. Among 20 contemporary studies (including 4,904 patients and 6,934 normal-appearing adrenal glands), up to 64% of normal-appearing adrenals were a source of aldosteronism resulting in 31% of patients having discordant results.

CONCLUSIONS

Morphologically normal-appearing adrenal glands are commonly the source of aldosterone production in PA, even among young patients. The lack of awareness of this issue may result in inappropriate treatment recommendations.

An optimized two-stage cascaded deep neural network for adrenal segmentation on CT images

Segmentation of adrenal glands from CT images is a crucial step in the AI-assisted diagnosis of adrenal gland-related disease. However, highly intrasubject variability in shape and adhesive boundaries with surrounding tissues make accurate segmentation of the adrenal gland a challenging task. In the current study, we proposed a novel two-stage deep neural network for adrenal gland segmentation in an end-to-end fashion. In the first stage, a localization network that aims to determine the candidate volume of the target organ was used in the preprocessing step to reduce class imbalance and computational burden. Then, in the second stage, a Small-organNet model trained with a novel boundary attention focal loss was designed to refine the boundary of the organ within the screened volume. The experimental results show that our proposed cascaded framework outperforms the state-of-the-art deep learning method in segmenting the adrenal gland with respect to accuracy; it requires fewer trainable parameters and imposes a smaller demand on computational resources.

The Value of Different Single or Combined Indexes of the Captopril Challenge Test in the Diagnosis of Primary Aldosteronism

OBJECTIVE

The result interpretation of the captopril challenge test (CCT) for the diagnosis of primary aldosteronism (PA) is not standardized. Superiorities of different indexes in the CCT have not been fully investigated. We aimed to comprehensively evaluate the value and influence factors of different CCT-associated indexes in the diagnosis of PA.

METHODS

We enrolled 312, 85, 179 and 97 patients in the groups of PA, essential hypertension (EH), unilateral PA (UPA) and bilateral PA (BPA), respectively. For each single index investigated, we computed diagnostic estimates including the area under the receiver operating characteristic curve (AUC). We performed pre-specified subgroup analyses to explore influence factors. We assessed the diagnostic value of combined indexes in binary logistic regression models.

RESULTS

Post-CCT aldosterone to renin ratio (ARR) (AUC = 0.8771) and plasma aldosterone concentration (PAC) (AUC = 0.8769) showed high value in distinguishing PA from EH, and their combination (AUC = 0.937) was even superior to either alone. The diagnostic efficacy was moderately high for post-CCT aldosterone to angiotensin II ratio (AA2R) (AUC = 0.834) or plasma renin activity (PRA) (AUC = 0.795) but low for the suppression percentage of PAC (AUC = 0.679). Post-CCT PAC had a significantly higher AUC in the UPA than BPA subgroup (AUC = 0.914 vs 0.827, P<0.05).

CONCLUSION

We can take post-CCT ARR and PAC altogether into account to distinguish PA from EH, while caution should be taken to interpret CCT results with the suppression percentage of PAC. Post-CCT PAC may perform better to identify the unilateral than bilateral form of PA.