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Kedra A, Dohan A, Gaujoux S, Sibony M, Jouinot A, Assié G, Groussin Rouiller L, Libé R, Bertherat J, Soyer P, Barat M. Preoperative Detection of Liver Involvement by Right-Sided Adrenocortical Carcinoma Using CT and MRI. Cancers (Basel) 2021; 13:1603. [PMID: 33807178 PMCID: PMC8036813 DOI: 10.3390/cancers13071603] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 03/21/2021] [Accepted: 03/26/2021] [Indexed: 11/16/2022] Open
Abstract
The major prognosis factor of adrenocortical carcinoma (ACC) is the completeness of surgery. The aim of our study was to identify preoperative imaging features associated with direct liver involvement (DLI) by right-sided ACC. Two radiologists, blinded to the outcome, independently reviewed preoperative CT and MRI examinations for eight signs of DLI, in patients operated for right-sided ACC and retrospectively included from November 2007 to January 2020. DLI was confirmed using surgical and histopathological findings. Kappa values were calculated. Univariable and multivariable analyses were performed by using a logistic regression model. Receiver operating characteristic (ROC) curves were built for CT and MRI. Twenty-nine patients were included. Seven patients had DLI requiring en bloc resection. At multivariable analysis, focal ACC bulge was the single independent sign associated with DLI on CT (OR: 60.00; 95% CI: 4.60-782.40; p < 0.001), and ACC contour disruption was the single independent sign associated with DLI on MRI (OR: 126.00; 95% CI: 6.82-2328.21; p < 0.001). Both signs were highly reproducible, with respective kappa values of 0.85 and 0.91. The areas under ROC curves of MRI and CT models were not different (p = 0.838). Focal ACC bulge on CT and ACC contour disruption on MRI are independent and highly reproducible signs, strongly associated with DLI by right-sided ACC on preoperative imaging. MRI does not improve the preoperative assessment of DLI by comparison with CT.
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Affiliation(s)
- Alice Kedra
- Department of Diagnostic and Interventional Imaging, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France; (A.D.); (P.S.); (M.B.)
| | - Anthony Dohan
- Department of Diagnostic and Interventional Imaging, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France; (A.D.); (P.S.); (M.B.)
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
| | - Sébastien Gaujoux
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
- Department of Surgery, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France
| | - Mathilde Sibony
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
- Department of Pathology, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France
| | - Anne Jouinot
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
- Department of Oncology, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France
| | - Guillaume Assié
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
- Department of Endocrinology, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France;
| | - Lionel Groussin Rouiller
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
- Department of Endocrinology, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France;
| | - Rossella Libé
- Department of Endocrinology, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France;
| | - Jérôme Bertherat
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
- Department of Endocrinology, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France;
| | - Philippe Soyer
- Department of Diagnostic and Interventional Imaging, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France; (A.D.); (P.S.); (M.B.)
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
| | - Maxime Barat
- Department of Diagnostic and Interventional Imaging, Hôpital Cochin, Assistance Publique—Hôpitaux de Paris, 75014 Paris, France; (A.D.); (P.S.); (M.B.)
- Faculté de Médecine, Université de Paris, 75006 Paris, France; (S.G.); (M.S.); (A.J.); (G.A.); (L.G.R.); (J.B.)
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Guadagno E, D'Avella E, Cappabianca P, Colao A, Del Basso De Caro M. Ki67 in endocrine neoplasms: to count or not to count, this is the question! A systematic review from the English language literature. J Endocrinol Invest 2020; 43:1429-1445. [PMID: 32415572 DOI: 10.1007/s40618-020-01275-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 04/23/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Endocrine neoplasms are generally slow-growing tumors that can show hormonal activity and give metastases. In most cases they are benign and clearly malignant forms are easy to diagnose. However, borderline forms may occur and be, for the pathologists, very difficult to classify. In these cases, there is a strong need to identify factors that may aid. Official classification systems for endocrine neoplasms are based on the evaluation of proliferation and, in most cases, they rely on mitotic count. In support, the study of Ki67 is carried out which, however, has not yet been included in any official classification system, except for neuroendocrine neoplasms of the gastro-entero-pancreatic tract. PURPOSE The aim of the present study was to investigate the proven or unproven role of Ki67 in endocrine neoplasms, in different districts, in order to bring to light the substantial differences, in terms of proliferation, existing between neoplasms so similar, but at the same time, so different. METHODS A thorough search of English language literature was performed, looking for articles concerning Ki67 in five endocrine neoplasms (pituitary adenomas, thyroid neoplasms, adrenocortical neoplasms, pheochromocytomas and paragangliomas). RESULTS From 2170, 236 articles were selected and it was seen that the endocrine neoplasm in which Ki67 was most studied was the pituitary, where it still shows a controversial role. In other neoplasms different roles were identified. CONCLUSION The pathologist should be aware of the contribution that this proliferative marker can give to the diagnosis and, sometimes, to the therapy selection, for the clinician.
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Affiliation(s)
- E Guadagno
- Pathology Section, Department of Advanced Biomedical Sciences, "Federico II" University of Naples, Via Pansini 5, 80131, Naples, Italy.
| | - E D'Avella
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, "Federico II" University of Naples, Via Pansini 5, 80131, Naples, Italy
| | - P Cappabianca
- Division of Neurosurgery, Department of Neurosciences, Reproductive and Odontostomatological Sciences, "Federico II" University of Naples, Via Pansini 5, 80131, Naples, Italy
| | - A Colao
- Endocrinology Section, Department of Clinic Medicine and Surgery, "Federico II" University of Naples, Via Pansini 5, 80131, Naples, Italy
| | - M Del Basso De Caro
- Pathology Section, Department of Advanced Biomedical Sciences, "Federico II" University of Naples, Via Pansini 5, 80131, Naples, Italy
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Leong D, Nyantoro M, Shedzad H, Robins P, Henley D, Ryan S, Nguyen H, Lisewski D. Management of adrenocortical carcinoma in Western Australia: a perspective over 14 years. ANZ J Surg 2020; 91:62-67. [PMID: 32627365 DOI: 10.1111/ans.16111] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 05/24/2020] [Accepted: 06/07/2020] [Indexed: 12/17/2022]
Abstract
BACKGROUND Adrenocortical carcinoma is a rare but aggressive form of endocrine neoplasm that confers a poor prognosis. To date, the only Australian data published is from New South Wales. This paper describes our experience in Western Australia with a focus on surgical approach and outcomes. METHODS A retrospective study of patients treated for adrenocortical carcinoma in Western Australia over 14 years was performed. RESULTS Over the 14-year period, a total of 33 patients underwent surgery for adrenocortical carcinoma. Resection outcomes were superior in an open en bloc approach with an 85% R0 margin (P = 0.007). Local recurrence rates were lowest in an open en bloc approach (11%) compared to laparoscopic (75%). Multivariate analysis showed that an en bloc resection is highly correlated with an R0 resection (P < 0.05) and significantly associated with lower (odds ratio = 0.06) local recurrence (P = 0.009). Higher volume surgeons (>5 cases) had lower operative times and blood loss. Compliance with mitotane was significantly improved with close monitoring of levels. The European Network for the Study of Adrenal Tumours (ENSAT) stage at presentation was most predictive of long-term survival with 100% of stage I patients alive compared to 53% of stage II, 25% of stage III and 17% of stage IV patients at the end of the follow-up period. CONCLUSION An open en bloc approach with a low threshold for multi-visceral resection performed by high volume surgeons have improved outcomes in local recurrence, operative times and blood loss.
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Affiliation(s)
- David Leong
- Department of Endocrine Surgery, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - Munyaradzi Nyantoro
- Department of General Surgery, Fiona Stanley Hospital, Perth, Western Australia, Australia
| | - Hira Shedzad
- Department of Endocrine Surgery, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - Peter Robins
- Department of Nuclear Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - David Henley
- Department of Endocrine Surgery, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia.,Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.,School of Medicine and Pharmacology, University of Western Australia, Crawley, Western Australia, Australia
| | - Simon Ryan
- Department of Endocrine Surgery, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - Hieu Nguyen
- Department of Endocrine Surgery, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - Dean Lisewski
- School of Medicine and Pharmacology, University of Western Australia, Crawley, Western Australia, Australia.,Department of Endocrine Surgery, Fiona Stanley Hospital, Perth, Western Australia, Australia
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Xie L, Wang Q, Nan F, Ge L, Dang Y, Sun X, Li N, Dong H, Han Y, Zhang G, Zhu W, Guo X. OSacc: Gene Expression-Based Survival Analysis Web Tool For Adrenocortical Carcinoma. Cancer Manag Res 2019; 11:9145-9152. [PMID: 31749633 PMCID: PMC6817837 DOI: 10.2147/cmar.s215586] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 10/02/2019] [Indexed: 12/30/2022] Open
Abstract
Gene expression profiling data with long-term clinical follow-up information are great resources to screen, develop, evaluate and validate prognostic biomarkers in translational cancer research. However, an easy-to-use interactive online tool is needed to analyze these profiling and clinical data. In the current work, we developed OSacc (Online consensus Survival analysis of ACC), a web tool that provides rapid and user-friendly survival analysis based on seven independent transcriptomic profiles with long-term clinical follow-up information of 259 ACC patients gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. OSacc allows researchers and clinicians to evaluate the prognostic value of genes of interest by Kaplan–Meier (KM) survival plot with hazard ratio (HR) and log-rank test in ACC. OSacc is freely available at http://bioinfo.henu.edu.cn/ACC/ACCList.jsp.
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Affiliation(s)
- Longxiang Xie
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Qiang Wang
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Fangmei Nan
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Linna Ge
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Yifang Dang
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Xiaoxiao Sun
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Ning Li
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Huan Dong
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Yali Han
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Guosen Zhang
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
| | - Wan Zhu
- Department of Anesthesia, Stanford University, Stanford, CA, USA
| | - Xiangqian Guo
- Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China
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