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Piao Z, Meng M, Yang H, Xue T, Jia Z, Liu W. Distinguishing between aldosterone-producing adenomas and non-functional adrenocortical adenomas using the YOLOv5 network. Acta Radiol 2024:2841851241251446. [PMID: 38767055 DOI: 10.1177/02841851241251446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
BACKGROUND You Only Look Once version 5 (YOLOv5), a one-stage deep-learning (DL) algorithm for object detection and classification, offers high speed and accuracy for identifying targets. PURPOSE To investigate the feasibility of using the YOLOv5 algorithm to non-invasively distinguish between aldosterone-producing adenomas (APAs) and non-functional adrenocortical adenomas (NF-ACAs) on computed tomography (CT) images. MATERIAL AND METHODS A total of 235 patients who were diagnosed with ACAs between January 2011 and July 2022 were included in this study. Of the 215 patients, 81 (37.7%) had APAs and 134 (62.3%) had NF-ACAs' they were randomly divided into either the training set or the validation set at a ratio of 9:1. Another 20 patients, including 8 (40.0%) with APA and 12 (60.0%) with NF-ACA, were collected for the testing set. Five submodels (YOLOv5n, YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x) of YOLOv5 were trained and evaluated on the datasets. RESULTS In the testing set, the mAP_0.5 value for YOLOv5x (0.988) was higher than the values for YOLOv5n (0.969), YOLOv5s (0.965), YOLOv5m (0.974), and YOLOv5l (0.983). The mAP_0.5:0.95 value for YOLOv5x (0.711) was also higher than the values for YOLOv5n (0.587), YOLOv5s (0.674), YOLOv5m (0.671), and YOLOv5l (0.698) in the testing set. The inference speed of YOLOv5n was 2.4 ms in the testing set, which was the fastest among the five submodels. CONCLUSION The YOLOv5 algorithm can accurately and efficiently distinguish between APAs and NF-ACAs on CT images, especially YOLOv5x has the best identification performance.
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Affiliation(s)
- Zeyu Piao
- Graduate College, Dalian Medical University, Dalian, PR China
- Department of Radiology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, PR China
| | - Mingzhu Meng
- Department of Radiology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, PR China
| | - Huijie Yang
- Department of Endocrinology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, PR China
| | - Tongqing Xue
- Department of Interventional Radiology, Huaian Hospital of Huai'an City, Huai'an, PR China
| | - Zhongzhi Jia
- Department of Interventional and Vascular Surgery, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, PR China
| | - Wei Liu
- Department of Radiology, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, PR China
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Ma C, Feng B, Lin F, Lei Y, Xu K, Cui J, Liu Y, Long W, Cui E. Differentiating adrenal metastases from benign lesions with multiphase CT imaging: Deep learning could play an active role in assisting radiologists. Eur J Radiol 2023; 169:111169. [PMID: 37956572 DOI: 10.1016/j.ejrad.2023.111169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 10/05/2023] [Accepted: 10/22/2023] [Indexed: 11/15/2023]
Abstract
OBJECTIVES To develop and externally validate multiphase CT-based deep learning (DL) models for differentiating adrenal metastases from benign lesions. MATERIALS AND METHODS This retrospective two-center study included 1146 adrenal lesions from 1059 patients who underwent multiphase CT scanning between January 2008 and March 2021. The study encompassed 564 surgically confirmed adenomas, along with 135 benign lesions and 447 metastases confirmed by observation. DL models based on multiphase CT images were developed, validated and tested. The diagnostic performance of the classification models, imaging phases and radiologists with or without DL were compared using accuracy (ACC) and receiver operating characteristic (ROC) curves. Integrated discrimination improvement (IDI) analysis and the DeLong test were used to compare the area under the curve (AUC) among models. Decision curve analysis (DCA) was used to assess the clinical usefulness of the predictive models. RESULTS The DL signature based on LASSO (DLSL) had a higher AUC than that of the other classification models (IDI > 0, P < 0.05). Furthermore, the precontrast phase (PCP)-based DLSL performed best in the independent external validation (AUC = 0.881, ACC = 82.9 %) and clinical test cohorts (AUC = 0.790, ACC = 70.4 %), outperforming DLSL based on the other single-phase or three-phase images (IDI > 0, P < 0.05). DCA demonstrated that PCP-based DLSL provided a higher net benefit (0.01-0.95). The diagnostic performance led to statistically significant improvements when radiologists incorporated the DL model, with the AUC improving by 0.056-0.159 and the ACC improving by 0.069-0.178 (P < 0.05). CONCLUSION The DL model based on PCP CT images performed acceptably in differentiating adrenal metastases from benign lesions, and it may assist radiologists in accurate tumor staging for patients with a history of extra-adrenal malignancy.
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Affiliation(s)
- Changyi Ma
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen 529030, PR China
| | - Bao Feng
- School of Electronic Information and Automation, Guilin University of Aerospace Technology, 2 Jinji Road, Guilin 541000, PR China
| | - Fan Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, PR China
| | - Yan Lei
- Zunyi Medical University, 1 Xiaoyuan Road, Zunyi 563006, PR China
| | - Kuncai Xu
- School of Electronic Information and Automation, Guilin University of Aerospace Technology, 2 Jinji Road, Guilin 541000, PR China
| | - Jin Cui
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen 529030, PR China
| | - Yu Liu
- School of Electronic Information and Automation, Guilin University of Aerospace Technology, 2 Jinji Road, Guilin 541000, PR China
| | - Wansheng Long
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen 529030, PR China
| | - Enming Cui
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen 529030, PR China; Zunyi Medical University, 1 Xiaoyuan Road, Zunyi 563006, PR China; Guangdong Medical University, 2 Wenming East Road, 524023, PR China; Guangzhou Key Laboratory of Molecular and Functional Imaging for Clinical Translation, PR China.
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Lee K, Goh J, Jang J, Hwang J, Kwak J, Kim J, Eom K. Feasibility study of computed tomography texture analysis for evaluation of canine primary adrenal gland tumors. Front Vet Sci 2023; 10:1126165. [PMID: 37711438 PMCID: PMC10499047 DOI: 10.3389/fvets.2023.1126165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Accepted: 08/01/2023] [Indexed: 09/16/2023] Open
Abstract
Objective This study aimed to investigate the feasibility of computed tomography (CT) texture analysis for distinguishing canine adrenal gland tumors and its usefulness in clinical decision-making. Materials and methods The medical records of 25 dogs with primary adrenal masses who underwent contrast CT and a histopathological examination were retrospectively reviewed, of which 12 had adenomas (AAs), 7 had adenocarcinomas (ACCs), and 6 had pheochromocytomas (PHEOs). Conventional CT evaluation of each adrenal gland tumor included the mean, maximum, and minimum attenuation values in Hounsfield units (HU), heterogeneity of the tumor parenchyma, and contrast enhancement (type, pattern, and degree), respectively, in each phase. In CT texture analysis, precontrast and delayed-phase images of 18 adrenal gland tumors, which could be applied for ComBat harmonization were used, and 93 radiomic features (18 first-order and 75 second-order statistics) were extracted. Then, ComBat harmonization was applied to compensate for the batch effect created by the different CT protocols. The area under the receiver operating characteristic curve (AUC) for each significant feature was used to evaluate the diagnostic performance of CT texture analysis. Results Among the conventional features, PHEO showed significantly higher mean and maximum precontrast HU values than ACC (p < 0.05). Eight second-order features on the precontrast images showed significant differences between the adrenal gland tumors (p < 0.05). However, none of them were significantly different between AA and PHEO, or between precontrast images and delayed-phase images. This result indicates that ACC exhibited more heterogeneous and complex textures and more variable intensities with lower gray-level values than AA and PHEO. The correlation, maximal correlation coefficient, and gray level non-uniformity normalized were significantly different between AA and ACC, and between ACC and PHEO. These features showed high AUCs in discriminating ACC and PHEO, which were comparable or higher than the precontrast mean and maximum HU (AUC = 0.865 and 0.860, respectively). Conclusion Canine primary adrenal gland tumor differentiation can be achieved with CT texture analysis on precontrast images and may have a potential role in clinical decision-making. Further prospective studies with larger populations and cross-validation are warranted.
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Affiliation(s)
- Kyungsoo Lee
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, Republic of Korea
| | - Jinhyong Goh
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, Republic of Korea
| | - Jaeyoung Jang
- Jang Jae Young Veterinary Surgery Center, Seong-nam, Gyunggi-do, Republic of Korea
| | | | - Jungmin Kwak
- Saram and Animal Medical Center, Yongin-si, Gyunggi-do, Republic of Korea
| | - Jaehwan Kim
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, Republic of Korea
| | - Kidong Eom
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul, Republic of Korea
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Stanzione A, Cuocolo R, Bombace C, Pesce I, Mainolfi CG, De Giorgi M, Delli Paoli G, La Selva P, Petrone J, Camera L, Klain M, Del Vecchio S, Cuocolo A, Maurea S. Prediction of 2-[ 18F]FDG PET-CT SUVmax for Adrenal Mass Characterization: A CT Radiomics Feasibility Study. Cancers (Basel) 2023; 15:3439. [PMID: 37444549 DOI: 10.3390/cancers15133439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/20/2023] [Accepted: 06/28/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND Indeterminate adrenal masses (AM) pose a diagnostic challenge, and 2-[18F]FDG PET-CT serves as a problem-solving tool. Aim of this study was to investigate whether CT radiomics features could be used to predict the 2-[18F]FDG SUVmax of AM. METHODS Patients with AM on 2-[18F]FDG PET-CT scan were grouped based on iodine contrast injection as CT contrast-enhanced (CE) or CT unenhanced (NCE). Two-dimensional segmentations of AM were manually obtained by multiple operators on CT images. Image resampling and discretization (bin number = 16) were performed. 919 features were calculated using PyRadiomics. After scaling, unstable, redundant, and low variance features were discarded. Using linear regression and the Uniform Manifold Approximation and Projection technique, a CT radiomics synthetic value (RadSV) was obtained. The correlation between CT RadSV and 2-[18F]FDG SUVmax was assessed with Pearson test. RESULTS A total of 725 patients underwent PET-CT from April 2020 to April 2021. In 150 (21%) patients, a total of 179 AM (29 bilateral) were detected. Group CE consisted of 84 patients with 108 AM (size = 18.1 ± 4.9 mm) and Group NCE of 66 patients with 71 AM (size = 18.5 ± 3.8 mm). In both groups, 39 features were selected. No statisticallyf significant correlation between CT RadSV and 2-[18F]FDG SUVmax was found (Group CE, r = 0.18 and p = 0.058; Group NCE, r = 0.13 and p = 0.27). CONCLUSIONS It might not be feasible to predict 2-[18F]FDG SUVmax of AM using CT RadSV. Its role as a problem-solving tool for indeterminate AM remains fundamental.
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Affiliation(s)
- Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Renato Cuocolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84084 Baronissi, Italy
| | - Claudia Bombace
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Ilaria Pesce
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Ciro Gabriele Mainolfi
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Marco De Giorgi
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Gregorio Delli Paoli
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Pasquale La Selva
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Jessica Petrone
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Luigi Camera
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Michele Klain
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Silvana Del Vecchio
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Alberto Cuocolo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Simone Maurea
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
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Ceccato F, Correa R, Livhits M, Falhammar H. Editorial: Predictive tools in pheochromocytoma and paraganglioma. Front Endocrinol (Lausanne) 2023; 14:1227543. [PMID: 37383393 PMCID: PMC10298152 DOI: 10.3389/fendo.2023.1227543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 06/02/2023] [Indexed: 06/30/2023] Open
Affiliation(s)
- Filippo Ceccato
- Department of Medicine DIMED, University of Padua, Padua, Italy
- Endocrine Disease Unit, University-Hospital of Padua, Padua, Italy
| | - Ricardo Correa
- Endocrinology, Diabetes and Metabolism, The University of Arizona College of Medicine Phoenix, Phoenix, AZ, United States
| | - Masha Livhits
- Department of General Surgery, UCLA David Geffen School of Medicine, Los Angeles, CA, United States
| | - Henrik Falhammar
- Department of Endocrinology, Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
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Okroj D, Rzepecka A, Kłosowski P, Babińska A, Sworczak K. Review of Diagnostic Modalities for Adrenal Incidentaloma. J Clin Med 2023; 12:jcm12113739. [PMID: 37297933 DOI: 10.3390/jcm12113739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/18/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023] Open
Abstract
Adrenal incidentalomas are common findings in clinical practice, with a prevalence of up to 4.2% in radiological studies. Due to the large number of focal lesions in the adrenal glands, it can be challenging to make a definitive diagnosis and determine the appropriate management. The purpose of this review is to present current diagnostic modalities used to preoperatively distinguish between adrenocortical adenoma (ACA) and adrenocortical cancer (ACC). Proper management and diagnosis are crucial in avoiding unnecessary adrenalectomies, which occur in over 40% of cases. A literature analysis was conducted to compare ACA and ACC using imaging studies, hormonal evaluation, pathological workup, and liquid biopsy. Before deciding on surgical treatment, the nature of the tumor can be accurately determined using noncontrast CT imaging combined with tumor size and metabolomics. This approach helps to narrow down the group of patients with adrenal tumors who require surgical treatment due to the suspected malignant nature of the lesion.
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Affiliation(s)
- Dominika Okroj
- Department of Endocrinology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, ul. Dębinki 7, 80-211 Gdańsk, Poland
| | - Agata Rzepecka
- Department of Endocrinology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, ul. Dębinki 7, 80-211 Gdańsk, Poland
| | - Przemysław Kłosowski
- Department of Endocrinology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, ul. Dębinki 7, 80-211 Gdańsk, Poland
| | - Anna Babińska
- Department of Endocrinology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, ul. Dębinki 7, 80-211 Gdańsk, Poland
| | - Krzysztof Sworczak
- Department of Endocrinology and Internal Medicine, Faculty of Medicine, Medical University of Gdańsk, ul. Dębinki 7, 80-211 Gdańsk, Poland
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Crimì F, Agostini E, Toniolo A, Torresan F, Iacobone M, Tizianel I, Scaroni C, Quaia E, Campi C, Ceccato F. CT Texture Analysis of Adrenal Pheochromocytomas: A Pilot Study. Curr Oncol 2023; 30:2169-2177. [PMID: 36826128 PMCID: PMC9955696 DOI: 10.3390/curroncol30020167] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/02/2023] [Accepted: 02/07/2023] [Indexed: 02/12/2023] Open
Abstract
Radiomics is a promising research field that combines big data analysis (from tissue texture analysis) with clinical questions. We studied the application of CT texture analysis in adrenal pheochromocytomas (PCCs) to define the correlation between the extracted features and the secretory pattern, the histopathological data, and the natural history of the disease. A total of 17 patients affected by surgically removed PCCs were retrospectively enrolled. Before surgery, all patients underwent contrast-enhanced CT and complete endocrine evaluation (catecholamine secretion and genetic evaluation). The pheochromocytoma adrenal gland scaled score (PASS) was determined upon histopathological examination. After a resampling of all CT images, the PCCs were delineated using LifeX software in all three phases (unenhanced, arterial, and venous), and 58 texture parameters were extracted for each volume of interest. Using the Mann-Whitney test, the correlations between the hormonal hypersecretion, the malignancy score of the lesion (PASS > 4), and texture parameters were studied. The parameters DISCRETIZED_HUpeak and GLZLM_GLNU in the unenhanced phase and GLZLM_SZE, CONVENTIONAL_HUmean, CONVENTIONAL_HUQ3, DISCRETIZED_HUmean, DISCRETIZED_AUC_CSH, GLRLM_HGRE, and GLZLM_SZHGE in the venous phase were able to differentiate secreting PCCs (p < 0.01), and the parameters GLZLM_GLNU in the unenhanced phase and GLRLM_GLNU and GLRLM_RLNU in the venous differentiated tumors with low and high PASS. CT texture analysis of adrenal PCCs can be a useful tool for the early identification of secreting or malignant tumors.
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Affiliation(s)
- Filippo Crimì
- Department of Medicine (DIMED), University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Institute of Radiology, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
| | - Elena Agostini
- Department of Medicine (DIMED), University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Institute of Radiology, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
| | - Alessandro Toniolo
- Department of Medicine (DIMED), University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Institute of Radiology, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
| | - Francesca Torresan
- Department of Surgical, Oncological and Gastroenterological Sciences, University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Endocrine Surgery Unit, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
| | - Maurizio Iacobone
- Department of Surgical, Oncological and Gastroenterological Sciences, University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Endocrine Surgery Unit, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
| | - Irene Tizianel
- Department of Medicine (DIMED), University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Endocrinology Unit, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
| | - Carla Scaroni
- Department of Medicine (DIMED), University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Endocrinology Unit, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
| | - Emilio Quaia
- Department of Medicine (DIMED), University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Institute of Radiology, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
| | - Cristina Campi
- Department of Mathematics (DIMA), University of Genova, Via Dodecaneso 33, 16146 Genova, Italy
| | - Filippo Ceccato
- Department of Medicine (DIMED), University of Padova, Via Giustiniani 2, 35128 Padova, Italy
- Endocrinology Unit, Padova University Hospital, Via Giustiniani 2, 35128 Padova, Italy
- Correspondence:
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Zhu H, Wu M, Wei P, Tian M, Zhang T, Hu C, Han Z. A modified method for CT radiomics region-of-interest segmentation in adrenal lipid-poor adenomas: a two-institution comparative study. Front Oncol 2023; 13:1086039. [PMID: 37152026 PMCID: PMC10154461 DOI: 10.3389/fonc.2023.1086039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 04/05/2023] [Indexed: 05/09/2023] Open
Abstract
Objective This study aimed to investigate the application of modified region-of-interest (ROI) segmentation method in unenhanced computed tomography in the radiomics model of adrenal lipid-poor adenoma, and to evaluate the diagnostic performance using an external medical institution data set and select the best ROI segmentation method. Methods The imaging data of 135 lipid-poor adenomas and 102 non-adenomas in medical institution A and 30 lipid-poor adenomas and 43 non-adenomas in medical institution B were retrospectively analyzed, and all cases were pathologically or clinically confirmed. The data of Institution A builds the model, and the data of Institution B verifies the diagnostic performance of the model. Semi-automated ROI segmentation of tumors was performed using uAI software, using maximum area single-slice method (MAX) and full-volume method (ALL), as well as modified single-slice method (MAX_E) and full-volume method (ALL_E) to segment tumors, respectively. The inter-rater correlation coefficients (ICC) was performed to assess the stability of the radiomics features of the four ROI segmentation methods. The area under the curve (AUC) and at least 95% specificity pAUC (Partial AUC) were used as measures of the diagnostic performance of the model. Results A total of 104 unfiltered radiomics features were extracted using each of the four segmentation methods. In the ROC analysis of the radiomics model, the AUC value of the model constructed by MAX was 0.925, 0.919, and 0.898 on the training set, the internal validation set, and the external validation set, respectively, and the AUC value of MAX_E was 0.937, 0.931, and 0.906, respectively. The AUC value of ALL was 0.929, 0.929, and 0.918, and the AUC value of ALL_E was 0.942, 0.926, and 0.927, respectively. In all samples, the pAUCs of MAX, MAX_E, ALL, and ALL_E were 0.021, 0.025, 0.018, and 0.028, respectively. Conclusion The diagnostic performance of the radiomics model constructed based on the full-volume method was better than that of the model based on the single-slice method. The model constructed using the ALL_E method had a stronger generalization ability and the highest AUC and pAUC value.
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Affiliation(s)
- Hanlin Zhu
- Department of Radiology, Hangzhou Ninth People’s Hospital, Hangzhou, China
| | - Mengwei Wu
- Department of Radiology, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China
| | - Peiying Wei
- Department of Radiology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Min Tian
- Department of Radiology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tong Zhang
- Department of Radiology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chunfeng Hu
- Department of Radiology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhijiang Han
- Department of Radiology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Zhijiang Han,
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Bertherat J, Bourdeau I, Bouys L, Chasseloup F, Kamenicky P, Lacroix A. Clinical, pathophysiologic, genetic and therapeutic progress in Primary Bilateral Macronodular Adrenal Hyperplasia. Endocr Rev 2022:6957368. [PMID: 36548967 DOI: 10.1210/endrev/bnac034] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 10/07/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022]
Abstract
Patients with primary bilateral macronodular adrenal hyperplasia (PBMAH) usually present bilateral benign adrenocortical macronodules at imaging and variable levels of cortisol excess. PBMAH is a rare cause of primary overt Cushing's syndrome, but may represent up to one third of bilateral adrenal incidentalomas with evidence of cortisol excess. The increased steroidogenesis in PBMAH is often regulated by various G-protein coupled receptors aberrantly expressed in PBMAH tissues; some receptor ligands are ectopically produced in PBMAH tissues creating aberrant autocrine/paracrine regulation of steroidogenesis. The bilateral nature of PBMAH and familial aggregation, led to the identification of germline heterozygous inactivating mutations of the ARMC5 gene, in 20-25% of the apparent sporadic cases and more frequently in familial cases; ARMC5 mutations/pathogenic variants can be associated with meningiomas. More recently, combined germline mutations/pathogenic variants and somatic events inactivating the KDM1A gene were specifically identified in patients affected by GIP-dependent PBMAH. Functional studies demonstrated that inactivation of KDM1A leads to GIP-receptor (GIPR) overexpression and over or down-regulation of other GPCRs. Genetic analysis is now available for early detection of family members of index cases with PBMAH carrying identified germline pathogenic variants. Detailed biochemical, imaging, and co-morbidities assessment of the nature and severity of PBMAH is essential for its management. Treatment is reserved for patients with overt or mild cortisol/aldosterone or other steroid excesses taking in account co-morbidities. It previously relied on bilateral adrenalectomy; however recent studies tend to favor unilateral adrenalectomy, or less frequently, medical treatment with cortisol synthesis inhibitors or specific blockers of aberrant GPCR.
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Affiliation(s)
- Jerôme Bertherat
- Department of Endocrinology and National Reference Center for Rare Adrenal Disorders, Cochin Hospital, Assistance Publique Hôpitaux de Paris, 24 rue du Fg St Jacques, Paris 75014, France
| | - Isabelle Bourdeau
- Division of Endocrinology, Department of Medicine and Research Center, Centre hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada
| | - Lucas Bouys
- Department of Endocrinology and National Reference Center for Rare Adrenal Disorders, Cochin Hospital, Assistance Publique Hôpitaux de Paris, 24 rue du Fg St Jacques, Paris 75014, France
| | - Fanny Chasseloup
- Université Paris-Saclay, Inserm, Physiologie et Physiopathologie Endocriniennes, Service d'Endocrinologie et des Maladies de la Reproduction, 94276 Le Kremlin-Bicêtre, France
| | - Peter Kamenicky
- Université Paris-Saclay, Inserm, Physiologie et Physiopathologie Endocriniennes, Service d'Endocrinologie et des Maladies de la Reproduction, 94276 Le Kremlin-Bicêtre, France
| | - André Lacroix
- Division of Endocrinology, Department of Medicine and Research Center, Centre hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada
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10
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Liu X, Elbanan MG, Luna A, Haider MA, Smith AD, Sabottke CF, Spieler BM, Turkbey B, Fuentes D, Moawad A, Kamel S, Horvat N, Elsayes KM. Radiomics in Abdominopelvic Solid-Organ Oncologic Imaging: Current Status. AJR Am J Roentgenol 2022; 219:985-995. [PMID: 35766531 PMCID: PMC10616929 DOI: 10.2214/ajr.22.27695] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Radiomics is the process of extraction of high-throughput quantitative imaging features from medical images. These features represent noninvasive quantitative biomarkers that go beyond the traditional imaging features visible to the human eye. This article first reviews the steps of the radiomics pipeline, including image acquisition, ROI selection and image segmentation, image preprocessing, feature extraction, feature selection, and model development and application. Current evidence for the application of radiomics in abdominopelvic solid-organ cancers is then reviewed. Applications including diagnosis, subtype determination, treatment response assessment, and outcome prediction are explored within the context of hepatobiliary and pancreatic cancer, renal cell carcinoma, prostate cancer, gynecologic cancer, and adrenal masses. This literature review focuses on the strongest available evidence, including systematic reviews, meta-analyses, and large multicenter studies. Limitations of the available literature are highlighted, including marked heterogeneity in radiomics methodology, frequent use of small sample sizes with high risk of overfitting, and lack of prospective design, external validation, and standardized radiomics workflow. Thus, although studies have laid a foundation that supports continued investigation into radiomics models, stronger evidence is needed before clinical adoption.
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Affiliation(s)
- Xiaoyang Liu
- Joint Department of Medical Imaging, Division of Abdominal Imaging, University Health Network, University of Toronto, ON, Canada
| | - Mohamed G Elbanan
- Department of Radiology, Yale New Haven Health, Bridgeport Hospital, Bridgeport, CT
| | | | - Masoom A Haider
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
- Joint Department of Medical Imaging, University Health Network, Sinai Health System and University of Toronto, Toronto, ON, Canada
| | - Andrew D Smith
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL
| | - Carl F Sabottke
- Department of Medical Imaging, University of Arizona College of Medicine, Tucson, AZ
| | - Bradley M Spieler
- Department of Radiology, University Medical Center, Louisiana State University Health Sciences Center, New Orleans, LA
| | - Baris Turkbey
- Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD
| | - David Fuentes
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX
| | - Ahmed Moawad
- Department of Diagnostic and Interventional Radiology, Mercy Catholic Medical Center, Darby, PA
| | - Serageldin Kamel
- Department of Lymphoma, University of Texas MD Anderson Cancer Center, Houston, TX
| | - Natally Horvat
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Khaled M Elsayes
- Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX 77030
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11
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Imaging or Adrenal Vein Sampling Approach in Primary Aldosteronism? A Patient-Based Approach. Tomography 2022; 8:2735-2748. [PMID: 36412687 PMCID: PMC9680373 DOI: 10.3390/tomography8060228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 11/05/2022] [Accepted: 11/08/2022] [Indexed: 11/11/2022] Open
Abstract
Primary aldosteronism (PA) is the most frequent cause of secondary hypertension, associated with an increased risk of cardiovascular and cerebral disease, compared to essential hypertension. Therefore, it is mandatory to promptly recognize the disease and offer to the patient the correct diagnostic-therapeutic process in order to reduce new-onset cardiovascular events. It is fundamental to define subtype classification (unilateral or bilateral disease), in order to provide the best treatment (surgery for unilateral and medical treatment for bilateral disease). Here, we report five clinical cases of different subtypes of PA (patients with monolateral or bilateral PA, nondiagnostic AVS, allergy to iodinated contrast, and patients not suitable for surgery), with particular attention to the diagnostic-therapeutic process and the different approaches tailored to a single case. Since PA is a spectrum of various diseases, it needs a personalized diagnostic-therapeutic process, customized for the individual patient, depending on previous medical history, suitability for the surgery and patient's preferences.
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12
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Li C, Fu Y, Yi X, Guan X, Liu L, Chen BT. Application of radiomics in adrenal incidentaloma: a literature review. Discov Oncol 2022; 13:112. [PMID: 36305962 PMCID: PMC9616972 DOI: 10.1007/s12672-022-00577-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 10/13/2022] [Indexed: 11/05/2022] Open
Abstract
Assessment of adrenal incidentaloma relies on imaging analysis and evaluation of adrenal function. Radiomics as a tool for quantitative image analysis is useful for evaluation of adrenal incidentaloma. In this review, we examined radiomic literature on adrenal incidentaloma including both adrenal functional assessment and structural differentiation of benign versus malignant adrenal tumors. In this review, we summarized the status of radiomic application on adrenal incidentaloma and suggested potential direction for future research.
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Affiliation(s)
- Cheng Li
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Yan Fu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, 410008, Hunan, People's Republic of China
| | - Xiaoping Yi
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, 410008, Hunan, People's Republic of China.
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha , 410008, Hunan, People's Republic of China.
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
| | - Xiao Guan
- Department of Urological Surgery, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
| | - Longfei Liu
- Department of Urological Surgery, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
| | - Bihong T Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, USA
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13
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De Leo A, Vara G, Paccapelo A, Balacchi C, Vicennati V, Tucci L, Pagotto U, Selva S, Ricci C, Alberici L, Minni F, Nanni C, Ambrosi F, Santini D, Golfieri R, Di Dalmazi G, Mosconi C. Computerized tomography texture analysis of pheochromocytoma: relationship with hormonal and histopathological data. J Endocrinol Invest 2022; 45:1935-1944. [PMID: 35680695 PMCID: PMC9463266 DOI: 10.1007/s40618-022-01826-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 05/17/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVES Pheochromocytomas are rare tumors which can present with heterogeneous secretion profiles, clinical manifestations, and radiologic appearance. Under a histopathological point of view, they can be characterized as more or less aggressive with the Pheochromocytoma of the Adrenal gland Scaled Score (PASS) and the Grading system for Adrenal Pheochromocytoma and Paraganglioma (GAPP) score. The aim of this study is to analyze the texture analysis characteristics of pheochromocytoma and identify whether the texture analysis can yield information aiding in the diagnosis and the characterization of those tumors. METHODS Radiological, biochemical, and histopathological data regarding 30 consecutive patients with histologically confirmed pheochromocytoma were analyzed. Images obtained in the unenhanced, late arterial, venous, and delayed phases were used for the texture analysis. RESULTS Urinary epinephrine and metanephrine levels showed a significant correlation (R2 = 0.946; R2 = 699) in the multivariate linear model with texture features, as well as Ki-67 (R2 = 0.397), PASS score (R2 = 0.182), GAPP score (R2 = 0.705), and cellularity showed a significant correlation (R2 = 0.389). The cluster analysis based on radiomic features resulted in 2 clusters, with significative differences in terms of systolic and diastolic blood pressure values at the time of diagnosis (p = 0.025), GAPP score (4 vs 6, p = 0.05), histological pattern (1-2, p = 0.039), and comedonecrosis (0% vs 50%, p = 0.013). CONCLUSION In conclusion, our study provides the proof of concept for the use of texture analysis on contrast-enhanced CT images as a noninvasive, quantitative tool for helping in the characterization of the clinical, biochemical, and histopathological features of pheochromocytoma.
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Affiliation(s)
- A De Leo
- Pathology Unit, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum-University of Bologna, Bologna, Italy
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
| | - G Vara
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy.
| | - A Paccapelo
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
| | - C Balacchi
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
| | - V Vicennati
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Unit of Endocrinology and Diabetes Prevention and Care, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - L Tucci
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Unit of Endocrinology and Diabetes Prevention and Care, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - U Pagotto
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Unit of Endocrinology and Diabetes Prevention and Care, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - S Selva
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Division of Pancreatic Surgery, Department of Internal Medicine and Surgery (DIMEC), Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - C Ricci
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Division of Pancreatic Surgery, Department of Internal Medicine and Surgery (DIMEC), Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - L Alberici
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Division of Pancreatic Surgery, Department of Internal Medicine and Surgery (DIMEC), Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - F Minni
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Division of Pancreatic Surgery, Department of Internal Medicine and Surgery (DIMEC), Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - C Nanni
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Nuclear Medicine Unit, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - F Ambrosi
- Pathology Unit, Maggiore Hospital, Bologna, Italy
| | - D Santini
- Pathology Unit, Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum-University of Bologna, Bologna, Italy
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
| | - R Golfieri
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
| | - G Di Dalmazi
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
- Unit of Endocrinology and Diabetes Prevention and Care, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - C Mosconi
- Diagnostic and Interventional Radiology Unit, Department of Diagnostic and Preventive Medicine, Via Albertoni 15, 40136, Bologna, Italy
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14
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Mínguez Ojeda C, Gómez Dos Santos V, Álvaro Lorca J, Ruz-Caracuel I, Pian H, Sanjuanbenito Dehesa A, Burgos Revilla FJ, Araujo-Castro M. Tumour size in adrenal tumours: its importance in the indication of adrenalectomy and in surgical outcomes-a single-centre experience. J Endocrinol Invest 2022; 45:1999-2006. [PMID: 35748977 DOI: 10.1007/s40618-022-01836-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 06/04/2022] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate the relevance of tumour size in adrenal tumours in the estimation of malignancy risk and in the outcomes of adrenalectomy. METHODS We evaluate the histological results and surgical outcomes (intraoperative and postsurgical complications) in a retrospective single-centre cohort of patients without history of active extraadrenal malignancy with adrenal tumours consecutively operated in our centre during January 2010 and December 2020. We compared these results in lesions smaller and larger than 40, 50, and 60 mm. RESULTS Of 131 patients with adrenal tumours who underwent adrenalectomy, 76 (58.0%) had adrenal masses measuring ≥ 40 mm; 47 were > 50 mm and 28 > 60 mm. The final diagnosis was adrenocortical carcinoma (ACC) in 7 patients, pheochromocytoma in 35, and benign lesions in the remaining. All patients with ACC had adrenal masses > 50 mm, with Hounsfield units > 40 and low lipidic content in the CT. The risk of ACC and pheochromocytoma increased as tumour size did. The diagnostic accuracy of tumour size was quite good for the prediction of ACC (AUC-ROC 0.883). Nevertheless, when only adrenal tumours with HU < 40 were considered, the risk of ACC was 0% independent of tumour size. For pheochromocytomas, the risk was of 8.6% independent of tumour size for lesions with < 20HU. The risk of intraoperative and postoperative complications was independent of tumour size. CONCLUSION Risk of malignancy and of pheochromocytoma increased as tumour size increased, but, in the presurgical estimation of malignancy risk and of pheochromocytoma, not only tumour size, also lipidic content and other radiological features, should be considered. The risk of complications was independent of tumour size, but hospital stay was longer in patients with complication or open approach.
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Affiliation(s)
- C Mínguez Ojeda
- Urology Department, Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - V Gómez Dos Santos
- Urology Department, Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - J Álvaro Lorca
- Urology Department, Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - I Ruz-Caracuel
- Pathology Department, Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - H Pian
- Pathology Department, Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | | | - F J Burgos Revilla
- Urology Department, Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - M Araujo-Castro
- Endocrinology and Nutrition Department, Hospital Universitario Ramón y Cajal, IRYCIS, Colmenar Viejo Street, km. 9, 100, 28034, Madrid, Spain.
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15
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Bracci B, De Santis D, Del Gaudio A, Faugno MC, Romano A, Tarallo M, Zerunian M, Guido G, Polici M, Polidori T, Pucciarelli F, Matarazzo I, Laghi A, Caruso D. Adrenal Lesions: A Review of Imaging. Diagnostics (Basel) 2022; 12:diagnostics12092171. [PMID: 36140572 PMCID: PMC9498052 DOI: 10.3390/diagnostics12092171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/04/2022] [Accepted: 09/05/2022] [Indexed: 11/16/2022] Open
Abstract
Adrenal lesions are frequently incidentally diagnosed during investigations for other clinical conditions. Despite being usually benign, nonfunctioning, and silent, they can occasionally cause discomfort or be responsible for various clinical conditions due to hormonal dysregulation; therefore, their characterization is of paramount importance for establishing the best therapeutic strategy. Imaging techniques such as ultrasound, computed tomography, magnetic resonance, and PET-TC, providing anatomical and functional information, play a central role in the diagnostic workup, allowing clinicians and surgeons to choose the optimal lesion management. This review aims at providing an overview of the most encountered adrenal lesions, both benign and malignant, including describing their imaging characteristics.
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Affiliation(s)
- Benedetta Bracci
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Domenico De Santis
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Antonella Del Gaudio
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Maria Carla Faugno
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Allegra Romano
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Mariarita Tarallo
- Department of Surgery “Pietro Valdoni”, Sapienza University of Rome, 00185 Rome, Italy
| | - Marta Zerunian
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Gisella Guido
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Michela Polici
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Tiziano Polidori
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Francesco Pucciarelli
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Iolanda Matarazzo
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Andrea Laghi
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
| | - Damiano Caruso
- Department of Medical Surgical Sciences and Translational Medicine, Sapienza—University of Rome, Radiology Unit—Sant’Andrea University Hospital, 00189 Rome, Italy
- Correspondence:
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16
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Zhang H, Lei H, Pang J. Diagnostic performance of radiomics in adrenal masses: A systematic review and meta-analysis. Front Oncol 2022; 12:975183. [PMID: 36119492 PMCID: PMC9478189 DOI: 10.3389/fonc.2022.975183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 08/17/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives(1) To assess the methodological quality and risk of bias of radiomics studies investigating the diagnostic performance in adrenal masses and (2) to determine the potential diagnostic value of radiomics in adrenal tumors by quantitative analysis.MethodsPubMed, Embase, Web of Science, and Cochrane Library databases were searched for eligible literature. Methodological quality and risk of bias in the included studies were assessed by the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) and Radiomics Quality Score (RQS). The diagnostic performance was evaluated by pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC). Spearman’s correlation coefficient and subgroup analysis were used to investigate the cause of heterogeneity. Publication bias was examined using the Deeks’ funnel plot.ResultsTwenty-eight studies investigating the diagnostic performance of radiomics in adrenal tumors were identified, with a total of 3579 samples. The average RQS was 5.11 (14.2% of total) with an acceptable inter-rater agreement (ICC 0.94, 95% CI 0.93–0.95). The risk of bias was moderate according to the result of QUADAS-2. Nine studies investigating the use of CT-based radiomics in differentiating malignant from benign adrenal tumors were included in the quantitative analysis. The pooled sensitivity, specificity, DOR and AUC with 95% confidence intervals were 0.80 (0.68-0.88), 0.83 (0.73-0.90), 19.06 (7.87-46.19) and 0.88 (0.85–0.91), respectively. There was significant heterogeneity among the included studies but no threshold effect in the meta-analysis. The result of subgroup analysis demonstrated that radiomics based on unenhanced and contrast-enhanced CT possessed higher diagnostic performance, and second-order or higher-order features could enhance the diagnostic sensitivity but also increase the false positive rate. No significant difference in diagnostic ability was observed between studies with machine learning and those without.ConclusionsThe methodological quality and risk of bias of studies investigating the diagnostic performance of radiomics in adrenal tumors should be further improved in the future. CT-based radiomics has the potential benefits in differentiating malignant from benign adrenal tumors. The heterogeneity between the included studies was a major limitation to obtaining more accurate conclusions.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/ CRD 42022331999 .
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Higgs JA, Quinn AP, Seely KD, Richards Z, Mortensen SP, Crandall CS, Brooks AE. Pathophysiological Link between Insulin Resistance and Adrenal Incidentalomas. Int J Mol Sci 2022; 23:ijms23084340. [PMID: 35457158 PMCID: PMC9032410 DOI: 10.3390/ijms23084340] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/05/2022] [Accepted: 04/12/2022] [Indexed: 12/22/2022] Open
Abstract
Adrenal incidentalomas are incidentally discovered adrenal masses greater than one centimeter in diameter. An association between insulin resistance and adrenal incidentalomas has been established. However, the pathophysiological link between these two conditions remains incompletely characterized. This review examines the literature on the interrelationship between insulin resistance and adrenal masses, their subtypes, and related pathophysiology. Some studies show that functional and non-functional adrenal masses elicit systemic insulin resistance, whereas others conclude the inverse. Insulin resistance, hyperinsulinemia, and the anabolic effects on adrenal gland tissue, which have insulin and insulin-like growth factor-1 receptors, offer possible pathophysiological links. Conversely, autonomous adrenal cortisol secretion generates visceral fat accumulation and insulin resistance. Further investigation into the mechanisms and timing of these two pathologies as they relate to one another is needed and could be valuable in the prevention, detection, and treatment of both conditions.
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Affiliation(s)
- Jordan A. Higgs
- College of Osteopathic Medicine, Rocky Vista University, Ivins, UT 84738, USA; (J.A.H.); (A.P.Q.); (Z.R.); (S.P.M.); (C.S.C.)
| | - Alyssa P. Quinn
- College of Osteopathic Medicine, Rocky Vista University, Ivins, UT 84738, USA; (J.A.H.); (A.P.Q.); (Z.R.); (S.P.M.); (C.S.C.)
| | - Kevin D. Seely
- College of Osteopathic Medicine, Rocky Vista University, Ivins, UT 84738, USA; (J.A.H.); (A.P.Q.); (Z.R.); (S.P.M.); (C.S.C.)
- Correspondence:
| | - Zeke Richards
- College of Osteopathic Medicine, Rocky Vista University, Ivins, UT 84738, USA; (J.A.H.); (A.P.Q.); (Z.R.); (S.P.M.); (C.S.C.)
| | - Shad P. Mortensen
- College of Osteopathic Medicine, Rocky Vista University, Ivins, UT 84738, USA; (J.A.H.); (A.P.Q.); (Z.R.); (S.P.M.); (C.S.C.)
| | - Cody S. Crandall
- College of Osteopathic Medicine, Rocky Vista University, Ivins, UT 84738, USA; (J.A.H.); (A.P.Q.); (Z.R.); (S.P.M.); (C.S.C.)
| | - Amanda E. Brooks
- Department of Research and Scholarly Activity, Rocky Vista University, Ivins, UT 84738, USA;
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Maggio R, Messina F, D’Arrigo B, Maccagno G, Lardo P, Palmisano C, Poggi M, Monti S, Matarazzo I, Laghi A, Pugliese G, Stigliano A. Machine Learning-Based Texture Analysis in the Characterization of Cortisol Secreting vs. Non-Secreting Adrenocortical Incidentalomas in CT Scan. Front Endocrinol (Lausanne) 2022; 13:873189. [PMID: 35784576 PMCID: PMC9248203 DOI: 10.3389/fendo.2022.873189] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 04/22/2022] [Indexed: 11/13/2022] Open
Abstract
New radioimaging techniques, exploiting the quantitative variables of imaging, permit to identify an hypothetical pathological tissue. We have applied this potential in a series of 72 adrenal incidentalomas (AIs) followed at our center, subdivided in functioning and non-functioning using laboratory findings. Each AI was studied in the preliminary non-contrast phase with a specific software (Mazda), surrounding a region of interest within each lesion. A total of 314 features were extrapolated. Mean and standard deviations of features were obtained and the difference in means between the two groups was statistically analyzed. Receiver Operating Characteristic (ROC) curves were used to identify an optimal cutoff for each variable and a prediction model was constructed via multivariate logistic regression with backward and stepwise selection. A 11-variable prediction model was constructed, and a ROC curve was used to differentiate patients with high probability of functioning AI. Using a threshold value of >-275.147, we obtained a sensitivity of 93.75% and a specificity of 100% in diagnosing functioning AI. On the basis of these results, computed tomography (CT) texture analysis appears a promising tool in the diagnostic definition of AIs.
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Affiliation(s)
- Roberta Maggio
- Endocrinology, Department of Clinical and Molecular Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Filippo Messina
- Department of Surgical and Medical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Benedetta D’Arrigo
- Department of Surgical and Medical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Giacomo Maccagno
- Department of Surgical and Medical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Pina Lardo
- Endocrinology, Department of Clinical and Molecular Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Claudia Palmisano
- Department of Surgical and Medical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Maurizio Poggi
- Endocrinology, Department of Clinical and Molecular Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Salvatore Monti
- Endocrinology, Department of Clinical and Molecular Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Iolanda Matarazzo
- Department of Surgical and Medical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Andrea Laghi
- Department of Surgical and Medical Sciences and Translational Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Giuseppe Pugliese
- Endocrinology, Department of Clinical and Molecular Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
| | - Antonio Stigliano
- Endocrinology, Department of Clinical and Molecular Medicine, Sant’Andrea University Hospital, Sapienza University of Rome, Rome, Italy
- *Correspondence: Antonio Stigliano,
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