Was It an Adrenocortical Adenoma or an Adrenocortical Carcinoma? Limitation of the Weiss Scoring System in Determining the Malignant Potential of Adrenocortical Tumor: Report on Two Cases

[The algorithm for morphological assessment of malignant potential of adrenocortical tumors using mathematical modeling method]

OBJECTIVE

To develop the mathematical model with high sensitivity and specificity to assess the malignant potential of adrenal cortical tumors, which can be used to diagnose adrenocortical carcinoma (ACC) in adults.

MATERIAL AND METHODS

Pathomorphological examination of surgical and consultative material of adrenocortical neoplasms was carried out. All cases were verified according to the WHO Classification of adrenal gland tumors (5th ed., 2022), the tumor's histogenesis was confirmed by immunohistochemical examination. Statistical analysis of the histological and immunohistochemical factors in terms of their value in relation to the diagnosis of ACC was carried out on Python 3.1 in the Google Colab environment. ROC analysis was used to identify critical values of predictors. The cut-off point was selected according to the Youden`s index. Logistic regression analysis using l1-regularisation was performed. To validate the model, the initial sample was divided into training and test groups in the ratio of 9:1, respectively.

RESULTS

The study included 143 patients divided into training (128 patients) and test (15 patients) samples. A prognostic algorithm was developed, which represent a diagnostically significant set of indicators of the currently used Weiss scale. The diagnosis is carried out in 3 stages. This mathematical model showed 100% accuracy (95% CI: 96-100%) on the training and test samples.

CONCLUSION

The developed algorithm could solve the problem of subjectivity and complexity in the interpretation of some of the criteria of current diagnostic algorithms. The new model is unique in that, unlike others, it allows verification of all morphological variants of ACC.

High Filamin a Expression in Adrenocortical Carcinomas Is Associated with a Favourable Tumour Behaviour: A European Multicentric Study

The insulin-like growth factor 2 (IGF2) promotes cell growth by overactivating the IGF system in an autocrine loop in adrenocortical carcinomas (ACCs). The cytoskeleton protein filamin A (FLNA) acts as a repressor of IGF2 mitogenic signalling in ACC cells. The aims of this study were to test FLNA expression by immunohistochemistry in 119 ACCs and 26 adrenocortical adenomas (ACAs) and to evaluate its relationship with clinicopathological features and outcome in ACCs. We found that 71.4% of ACCs did not express FLNA, whereas FLNA absence was a rare event in ACAs (15.4%, p < 0.001 vs. ACCs). In addition, the expression of FLNA was associated with a less aggressive tumour behaviour in ACCs. Indeed, the subgroup of ACCs with high FLNA showed a lower ENSAT stage, Weiss score, and S-GRAS score compared to ACCs with low FLNA expression (p < 0.05). Moreover, patients with high FLNA had a longer overall survival than those with low FLNA (p < 0.05). In conclusion, our data suggest that FLNA may represent a "protective" factor in ACCs, and the integration of FLNA immunohistochemical expression in ACC tissues along with other clinical and molecular markers could be helpful to improve diagnostic accuracy and prognosis prediction in ACCs.

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.

The ADRENAL score: A comprehensive scoring system for standardized evaluation of adrenal tumor

OBJECTIVES

To propose an original and standardized scoring system to quantify the functional and anatomical characteristics of adrenal tumor.

MATERIALS AND METHODS

Four groups of consecutive adrenalectomies (n = 458) with heterogeneity in tumor characteristics and surgical approaches, including 212 laparoscopic cases (Group 1) and 105 robotic cases (Group 2) from The First Affiliated Hospital of Nanchang University, 28 robotic cases from Temple University Hospital (Group 3) and 113 laparoscopic cases from The First Affiliated Hospital of Guangxi Medical University (Group 4). All patients were followed up for 4.5 to 5.5 years. Six parameters including functional status or suspicion of malignancy, tumor size, relationship to adjacent organs, intratumoral enhancement on CT, nearness of the tumor to major vessels and body mass index were assessed and scored on a 0, 1 and 2 points scale. Correlation between the sum of the 6 scores and tumor laterality (ADRENAL score) verse operative time (OT), estimated blood loss (EBL), perioperative complications, transfusion, conversion and length of hospital stay was analyzed.

RESULTS

ADRENAL score was a strong predictor of both OT and EBL in all four groups (p < 0.05 for all tests). In Group 2 and 4, higher ADRENAL score seemed to correlate with longer hospital stay. No statistically significant correlation between ADRENAL score and complication, transfusion or conversion was noted yet.

CONCLUSIONS

ADRENAL score appears to be a valid predictor of surgical outcomes. It may provide a common reference for adrenal surgery training program, preoperative risk assessment and stratified comparative analysis of adrenal surgeries via different techniques and approaches.