Assessment of tumor heterogeneity in treatment-naïve adrenocortical cancer patients using (18)F-FDG positron emission tomography

Prognostic role of quantitative [18F]FDG PET/CT parameters in adrenocortical carcinoma

PURPOSE

We aimed to evaluate the prognostic potential of baseline [18F]FDG PET/CT for overall survival (OS) in patients with adrenocortical carcinoma (ACC).

METHODS

We performed a retrospective analysis of 67 treatment-naïve ACC patients with available [18F]FDG PET/CT at time of initial diagnosis. Pretherapeutic PETs of primary tumors were manually segmented and quantitative parameters (maximum/mean/peak standardized uptake value (SUVmax/mean/peak), metabolic tumor volume (MTV) and tumor lesion glycolysis (TLG, defined as TV*SUVmean) were derived. Based on a visual read, absence (M0) or presence of metastatic disease (M1) were evaluated. Kaplan-Meier and Cox regression analyses were used to determine the prognostic value of the above mentioned markers on overall survival adjusted for established prognostic markers.

RESULTS

24/67 patients (36%) presented with M0 based on PET/CT, while the remaining 43/67 (64%) had M1-status. 32/67 patients died during follow-up and median OS was 48 months. In 12% of patients FDG-PET detected additional metastatic lesion not clearly visible by CT only. In univariable analysis, all quantitatively derived PET parameters failed to reach significance (P ≥ 0.1), and only PET/CT-based M1-status and Ki-67 were associated with increased mortality (M1: HR 13.89, 95% CI 4.15-86.32, P < 0.001; Ki-67 HR 1.29, 95% CI 1.16-1.42; P < 0.0001). Using multivariable Cox regression analyses, M1-status (HR 9.69, 95% CI 2.82-60.99) and Ki-67 index (HR 1.29, 95% CI 1.13-1.04; P < 0.05) remained significant associated with OS.

CONCLUSION

In treatment-naïve ACC patients, the quantitative PET parameter failed to predict OS, but presence of metastases detected by [18F]FDG PET/CT and Ki-67 index were independently associated with shorter OS. Therefore, a simple visual PET-based read-out is of prognostic value at initial diagnosis, while time-consuming PET-based quantification can be omitted.

Positive Correlation Between 18 F-FDG Uptake and Tumor-Proliferating Antigen Ki-67 Expression in Adrenocortical Carcinomas

PURPOSE OF THE REPORT

Adrenocortical carcinoma (ACC) is an extremely rare endocrine malignancy, which cannot always be diagnosed during conventional radiology and hormonal investigations. 18 F-FDG PET could help predict malignancy, but more data are necessary to support future guidelines.

METHODS

A cohort of 63 patients with histologically proven ACC (n = 55) or metastatic ACC with steroid oversecretion (n = 8) was assembled. All patients underwent an 18 F-FDG PET, and the SUV max and the adrenal-to-liver SUV max ratio were calculated. The 18 F-FDG PET parameters were compared with clinical, pathological, and outcome data.

RESULTS

Fifty-six of 63 patients (89%) had an ACC with an adrenal-to-liver SUV max ratio >1.45, which was a previously defined cutoff value to predict malignancy with 100% sensitivity. Seven ACCs (11%) had a lower uptake (adrenal-to-liver SUV max <1.45), most of them with a proliferation marker Ki-67 expression level <10%. A positive correlation between 18 F-FDG PET parameters (SUV max and adrenal-to-liver SUV max ratio) and tumor size, ENSAT (European Network for the Study of Adrenal Tumors) staging, total Weiss score, and the Ki-67 was found. The strong correlation between SUV max and Ki-67 ( r = 0.47, P = 0.0009) suggests a relationship between 18 F-FDG uptake levels and tumor proliferation. No statistically significant associations between outcome parameters (progression-free or overall survival) and 18 F-FDG PET parameters were found.

CONCLUSIONS

This large cohort study shows that most cases of ACC demonstrate high 18 F-FDG uptake. However, the positive correlation observed between SUV max and Ki-67 expression levels seems to explain the possibility of identifying some ACC with a low or inexistent 18 F-FDG uptake. These findings have practical implications for the management of patients with an adrenal mass.

Artificial intelligence in adrenal imaging: A critical review of current applications

In the elective field of adrenal imaging, artificial intelligence (AI) can be used for adrenal lesion detection, characterization, hypersecreting syndrome management and patient follow-up. Although a perfect AI tool that includes all required steps from detection to analysis does not exist yet, multiple AI algorithms have been developed and tested with encouraging results. However, AI in this setting is still at an early stage. In this regard, most published studies about AI in adrenal gland imaging report preliminary results that do not have yet daily applications in clinical practice. In this review, recent developments and current results of AI in the field of adrenal imaging are presented. Limitations and future perspectives of AI are discussed.

Radiomics in Cross-Sectional Adrenal Imaging: A Systematic Review and Quality Assessment Study

In this study, we aimed to systematically review the current literature on radiomics applied to cross-sectional adrenal imaging and assess its methodological quality. Scopus, PubMed and Web of Science were searched to identify original research articles investigating radiomics applications on cross-sectional adrenal imaging (search end date February 2021). For qualitative synthesis, details regarding study design, aim, sample size and imaging modality were recorded as well as those regarding the radiomics pipeline (e.g., segmentation and feature extraction strategy). The methodological quality of each study was evaluated using the radiomics quality score (RQS). After duplicate removal and selection criteria application, 25 full-text articles were included and evaluated. All were retrospective studies, mostly based on CT images (17/25, 68%), with manual (19/25, 76%) and two-dimensional segmentation (13/25, 52%) being preferred. Machine learning was paired to radiomics in about half of the studies (12/25, 48%). The median total and percentage RQS scores were 2 (interquartile range, IQR = -5-8) and 6% (IQR = 0-22%), respectively. The highest and lowest scores registered were 12/36 (33%) and -5/36 (0%). The most critical issues were the absence of proper feature selection, the lack of appropriate model validation and poor data openness. The methodological quality of radiomics studies on adrenal cross-sectional imaging is heterogeneous and lower than desirable. Efforts toward building higher quality evidence are essential to facilitate the future translation into clinical practice.

European Society of Endocrinology Clinical Practice Guidelines on the management of adrenocortical carcinoma in adults, in collaboration with the European Network for the Study of Adrenal Tumors

Adrenocortical carcinoma (ACC) is a rare and in most cases steroid hormone-producing tumor with variable prognosis. The purpose of these guidelines is to provide clinicians with best possible evidence-based recommendations for clinical management of patients with ACC based on the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system. We predefined four main clinical questions, which we judged as particularly important for the management of ACC patients and performed systematic literature searches: (A) What is needed to diagnose an ACC by histopathology? (B) Which are the best prognostic markers in ACC? (C) Is adjuvant therapy able to prevent recurrent disease or reduce mortality after radical resection? (D) What is the best treatment option for macroscopically incompletely resected, recurrent or metastatic disease? Other relevant questions were discussed within the group. Selected Recommendations: (i) We recommend that all patients with suspected and proven ACC are discussed in a multidisciplinary expert team meeting. (ii) We recommend that every patient with (suspected) ACC should undergo careful clinical assessment, detailed endocrine work-up to identify autonomous hormone excess and adrenal-focused imaging. (iii) We recommend that adrenal surgery for (suspected) ACC should be performed only by surgeons experienced in adrenal and oncological surgery aiming at a complete en bloc resection (including resection of oligo-metastatic disease). (iv) We suggest that all suspected ACC should be reviewed by an expert adrenal pathologist using the Weiss score and providing Ki67 index. (v) We suggest adjuvant mitotane treatment in patients after radical surgery that have a perceived high risk of recurrence (ENSAT stage III, or R1 resection, or Ki67 >10%). (vi) For advanced ACC not amenable to complete surgical resection, local therapeutic measures (e.g. radiation therapy, radiofrequency ablation, chemoembolization) are of particular value. However, we suggest against the routine use of adrenal surgery in case of widespread metastatic disease. In these patients, we recommend either mitotane monotherapy or mitotane, etoposide, doxorubicin and cisplatin depending on prognostic parameters. In selected patients with a good response, surgery may be subsequently considered. (vii) In patients with recurrent disease and a disease-free interval of at least 12 months, in whom a complete resection/ablation seems feasible, we recommend surgery or alternatively other local therapies. Furthermore, we offer detailed recommendations about the management of mitotane treatment and other supportive therapies. Finally, we suggest directions for future research.

Survival prediction in patients undergoing radionuclide therapy based on intratumoral somatostatin-receptor heterogeneity

The NETTER-1 trial demonstrated significantly improved progression-free survival (PFS) for peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET) emphasizing the high demand for response prediction in appropriate candidates. In this multicenter study, we aimed to elucidate the prognostic value of tumor heterogeneity as assessed by somatostatin receptor (SSTR)-PET/CT. 141 patients with SSTR-expressing tumors were analyzed obtaining SSTR-PET/CT before PRRT (1-6 cycles, ¹⁷⁷Lu somatostatin analog). Using the Interview Fusion Workstation (Mediso), a total of 872 metastases were manually segmented. Conventional PET parameters as well as textural features representing intratumoral heterogeneity were computed. The prognostic ability for PFS and overall survival (OS) were examined. After performing Cox regression, independent parameters were determined by ROC analysis to obtain cut-off values to be used for Kaplan-Meier analysis. Within follow-up (median, 43.1 months), 75 patients showed disease progression (median, 22.2 m) and 54 patients died (median, 27.6 m). Cox analysis identified 8 statistically independent heterogeneity parameters for time-to-progression and time-to-death. Among them, the textural feature Entropy predicted both PFS and OS. Conventional PET parameters failed in response prediction. Imaging-based heterogeneity assessment provides prognostic information in PRRT candidates and outperformed conventional PET parameters. Its implementation in clinical practice can pave the way for individualized patient management.

Texture analysis of FDG PET/CT for differentiating between FDG-avid benign and metastatic adrenal tumors: efficacy of combining SUV and texture parameters

PURPOSE

To retrospectively investigate the SUV-related and texture parameters individually and in combination for differentiating between F-18-fluorodeoxyglucose (FDG)-avid benign and metastatic adrenal tumors with PET/CT.

METHODS

Thirteen benign adrenal tumors (BATs) and 22 metastatic adrenal tumors (MATs) with a metabolic tumor volume (MTV) > 10.0 cm³ and SUV ≥ 2.5 were included. SUVmax, MTV, total lesion glycolysis, and four textural parameters [entropy, homogeneity, intensity variability (IV), and size-zone variability] were obtained. These parameters were compared between BATs and MATs using Mann-Whitney U test, and the diagnostic performance was evaluated by the area under the curve (AUC) values derived from the receiver operating characteristic analysis. The diagnostic value of combining SUV and texture parameters was examined using a scoring system.

RESULTS

MATs showed significantly higher SUV_max (p = 0.004), entropy (p = 0.013), IV (p = 0.006), and lower homogeneity (p = 0.019) than BATs. The accuracies for diagnosing MATs were 82.9, 82.9, 85.7, and 71.4% for SUV_max, entropy, IV, and homogeneity, respectively. No significant differences in AUC were found among these parameters (p > 0.05 each). When each parameter was scored as 0 (negative for malignancy) and 1 (positive for malignancy) according to each threshold criterion and the four parameter summed scores 0, 1, and 2 were defined as benignity and 3 and 4 as malignancy, the sensitivity and specificity and accuracy to predict MATs were 100% (22/22), 84.6% (11/13), and 94.3% (33/35), respectively, with 0.97 of the AUC.

CONCLUSION

The combined use of SUV_max and texture parameters has a potential to significantly increase the diagnostic performance to differentiate between large FDG-avid BATs and MATs.