An Illustrated Review of the Recent 2019 World Health Organization Classification of Neuroendocrine Neoplasms: A Radiologic and Pathologic Correlation.
Journal
Journal of computer assisted tomography
ISSN: 1532-3145
Titre abrégé: J Comput Assist Tomogr
Pays: United States
ID NLM: 7703942
Informations de publication
Date de publication:
27 02 2024
27 02 2024
Historique:
medline:
5
3
2024
pubmed:
5
3
2024
entrez:
4
3
2024
Statut:
aheadofprint
Résumé
Recent advances in molecular pathology and an improved understanding of the etiology of neuroendocrine neoplasms (NENs) have given rise to an updated World Health Organization classification. Since gastroenteropancreatic NENs (GEP-NENs) are the most common forms of NENs and their incidence has been increasing constantly, they will be the focus of our attention. Here, we review the findings at the foundation of the new classification system, discuss how it impacts imaging research and radiological practice, and illustrate typical and atypical imaging and pathological findings. Gastroenteropancreatic NENs have a highly variable clinical course, which existing classification schemes based on proliferation rate were unable to fully capture. While well- and poorly differentiated NENs both express neuroendocrine markers, they are fundamentally different diseases, which may show similar proliferation rates. Genetic alterations specific to well-differentiated neuroendocrine tumors graded 1 to 3 and poorly differentiated neuroendocrine cancers of small cell and large-cell subtype have been identified. The new tumor classification places new demands and creates opportunities for radiologists to continue providing the clinically most relevant report and on researchers to design projects, which continue to be clinically applicable.
Identifiants
pubmed: 38438338
doi: 10.1097/RCT.0000000000001593
pii: 00004728-990000000-00293
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
Références
Assarzadegan N, Montgomery E. What is new in the 2019 World Health Organization (WHO) classification of tumors of the digestive system: review of selected updates on neuroendocrine neoplasms, appendiceal tumors, and molecular testing. Arch Pathol Lab Med. 2021;145:664–677.
Kaltsas GA, Besser GM, Grossman AB. The diagnosis and medical management of advanced neuroendocrine tumors. Endocr Rev. 2004;25:458–511.
Dasari A, Shen C, Halperin D, et al. Trends in the incidence, prevalence, and survival outcomes in patients with neuroendocrine tumors in the United States. JAMA Oncol. 2017;3:1335–1342.
White BE, Rous B, Chandrakumaran K, et al. Incidence and survival of neuroendocrine neoplasia in England 1995–2018: a retrospective, population-based study. Lancet Reg Health Eur. 2022;23:100510.
Nagtegaal ID, Odze RD, Klimstra D, et al. The 2019 WHO classification of tumours of the digestive system. Histopathology. 2020;76:182–188.
Bosman FT, Carneiro F, Hruban RH, et al. WHO Classification of Tumours of the Digestive System. IARC Press; 2010. [Google Scholar].
Lloyd RV, Osamura RY, Klöppel G, et al. WHO Classification of Tumours of Endocrine Organs. International Agency for Research on Cancer; 2017. [Google Scholar].
Pavel M, Öberg K, Falconi M, et al. Gastroenteropancreatic neuroendocrine neoplasms: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2020;31:844–860.
Lithgow K, Venkataraman H, Hughes S, et al. Well-differentiated gastroenteropancreatic G3 NET: findings from a large single centre cohort. Sci Rep. 2021;11:17947.
Tang LH, Untch BR, Reidy DL, et al. Well-differentiated neuroendocrine tumors with a morphologically apparent high-grade component: a pathway distinct from poorly differentiated neuroendocrine carcinomas. Clin Cancer Res. 2016;22:1011–1017.
Rindi G, Luinetti O, Cornaggia M, et al. Three subtypes of gastric argyrophil carcinoid and the gastric neuroendocrine carcinoma: a clinicopathologic study. Gastroenterology. 1993;104:994–1006.
Jiao Y, Shi C, Edil BH, et al. DAXX/ATRX, MEN1, and mTOR pathway genes are frequently altered in pancreatic neuroendocrine tumors. Science. 2011;331:1199–1203.
Scarpa A, Chang DK, Nones K, et al. Whole-genome landscape of pancreatic neuroendocrine tumours. Nature. 2017;543:65–71.
Konukiewitz B, Schlitter AM, Jesinghaus M, et al. Somatostatin receptor expression related to TP53 and RB1 alterations in pancreatic and extrapancreatic neuroendocrine neoplasms with a Ki67-index above 20. Mod Pathol. 2017;30:587–598.
Yachida S, Vakiani E, White CM, et al. Small cell and large cell neuroendocrine carcinomas of the pancreas are genetically similar and distinct from well-differentiated pancreatic neuroendocrine tumors. Am J Surg Pathol. 2012;36:173–184.
Karpathakis A, Dibra H, Pipinikas C, et al. Prognostic impact of novel molecular subtypes of small intestinal neuroendocrine tumor. Clin Cancer Res. 2016;22:250–258.
Rekhtman N. Lung neuroendocrine neoplasms: recent progress and persistent challenges. Mod Pathol. 2022;35:36–50.
Borczuk AC, Chan JKC, Cooper WA, et al. Thoracic Tumours. International Agency for Pesearch on Cancer (lABC); 2021. [Google Scholar].
Hermans BCM, Derks JL, Moonen L, et al. Pulmonary neuroendocrine neoplasms with well differentiated morphology and high proliferative activity: illustrated by a case series and review of the literature. Lung Cancer. 2020;150:152–158.
Fernandez-Cuesta L, Peifer M, Lu X, et al. Frequent mutations in chromatin-remodelling genes in pulmonary carcinoids. Nat Commun. 2014;5:3518.
Rekhtman N, Pietanza MC, Hellmann MD, et al. Next-generation sequencing of pulmonary large cell neuroendocrine carcinoma reveals small cell carcinoma-like and non-small cell carcinoma-like subsets. Clin Cancer Res. 2016;22:3618–3629.
Alcala N, Leblay N, Gabriel AAG, et al. Integrative and comparative genomic analyses identify clinically relevant pulmonary carcinoid groups and unveil the supra-carcinoids. Nat Commun. 2019;10:3407.
Yu HA, Arcila ME, Rekhtman N, et al. Analysis of tumor specimens at the time of acquired resistance to EGFR-TKI therapy in 155 patients with EGFR-mutant lung cancers. Clin Cancer Res. 2013;19:2240–2247.
Quintanal-Villalonga Á, Chan JM, Yu HA, et al. Lineage plasticity in cancer: a shared pathway of therapeutic resistance. Nat Rev Clin Oncol. 2020;17:360–371.
George J, Walter V, Peifer M, et al. Integrative genomic profiling of large-cell neuroendocrine carcinomas reveals distinct subtypes of high-grade neuroendocrine lung tumors. Nat Commun. 2018;9:1048.
Rossi G, Cavazza A, Spagnolo P, et al. Diffuse idiopathic pulmonary neuroendocrine cell hyperplasia syndrome. Eur Respir J. 2016;47:1829–1841.
Hayes AR, Luong TV, Banks J, et al. Diffuse idiopathic pulmonary neuroendocrine cell hyperplasia (DIPNECH): Prevalence, clinicopathological characteristics and survival outcome in a cohort of 311 patients with well-differentiated lung neuroendocrine tumours. J Neuroendocrinol. 2022;34:e13184.
Koo CW, Baliff JP, Torigian DA, et al. Spectrum of pulmonary neuroendocrine cell proliferation: diffuse idiopathic pulmonary neuroendocrine cell hyperplasia, tumorlet, and carcinoids. AJR Am J Roentgenol. 2010;195:661–668.
Shehabeldin AN, Ro JY. Neuroendocrine tumors of genitourinary tract: recent advances. Ann Diagn Pathol. 2019;42:48–58.
Shah MH, Goldner WS, Benson AB, et al. Neuroendocrine and adrenal tumors, version 2.2021, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2021;19:839–867.
Baloch ZW, LiVolsi VA. Neuroendocrine tumors of the thyroid gland. Am J Clin Pathol. 2001;115(Suppl):S56–S67.
Priya SR, Dravid CS, Digumarti R, et al. Targeted therapy for medullary thyroid cancer: a review. Front Oncol. 2017;7:238.
Machado NN, Wilhelm SM. Parathyroid cancer: a review. Cancers (Basel). 2019;11:1676.
Trouillas J, Jaffrain-Rea ML, Vasiljevic A, et al. How to classify the pituitary neuroendocrine tumors (PitNET)s in 2020. Cancers (Basel). 2020;12:514.
Asa SL, Mete O, Cusimano MD, et al. Pituitary neuroendocrine tumors: a model for neuroendocrine tumor classification. Mod Pathol. 2021;34:1634–1650.
Becker JC, Stang A, Decaprio JA, et al. Merkel cell carcinoma. Nat Rev Dis Primers. 2017;3:17077.
Tsang JY, Tse GM. Breast cancer with neuroendocrine differentiation: an update based on the latest WHO classification. Mod Pathol. 2021;34:1062–1073.
Khanna L, Prasad SR, Sunnapwar A, et al. Pancreatic neuroendocrine neoplasms: 2020 update on pathologic and imaging findings and classification. Radiographics. 2020;40:1240–1262.
Tamm EP, Bhosale P, Lee JH, et al. State-of-the-art imaging of pancreatic neuroendocrine tumors. Surg Oncol Clin N Am. 2016;25:375–400.
Keck KJ, Maxwell JE, Menda Y, et al. Identification of primary tumors in patients presenting with metastatic gastroenteropancreatic neuroendocrine tumors. Surgery. 2017;161:272–279.
Sundin A, Arnold R, Baudin E, et al. ENETS consensus guidelines for the standards of care in neuroendocrine tumors: radiological, nuclear medicine & hybrid imaging. Neuroendocrinology. 2017;105:212–244.
Dromain C, de Baere T, Lumbroso J, et al. Detection of liver metastases from endocrine tumors: a prospective comparison of somatostatin receptor scintigraphy, computed tomography, and magnetic resonance imaging. J Clin Oncol. 2005;23:70–78.
Tirumani SH, Jagannathan JP, Braschi-Amirfarzan M, et al. Value of hepatocellular phase imaging after intravenous gadoxetate disodium for assessing hepatic metastases from gastroenteropancreatic neuroendocrine tumors: comparison with other MRI pulse sequences and with extracellular agent. Abdom Radiol (NY). 2018;43:2329–2339.
d'Assignies G, Fina P, Bruno O, et al. High sensitivity of diffusion-weighted MR imaging for the detection of liver metastases from neuroendocrine tumors: comparison with T2-weighted and dynamic gadolinium-enhanced MR imaging. Radiology. 2013;268:390–399.
Hwang EJ, Lee JM, Yoon JH, et al. Intravoxel incoherent motion diffusion-weighted imaging of pancreatic neuroendocrine tumors: prediction of the histologic grade using pure diffusion coefficient and tumor size. Invest Radiol. 2014;49:396–402.
Mebis W, Snoeckx A, Corthouts B, et al. Correlation between apparent diffusion coefficient value on MRI and histopathologic WHO grades of neuroendocrine tumors. J Belg Soc Radiol. 2020;104:7.
Zong RL, Geng L, Wang X, et al. Diagnostic performance of apparent diffusion coefficient for prediction of grading of pancreatic neuroendocrine tumors: a systematic review and meta-analysis. Pancreas. 2019;48:151–160.
Azoulay A, Cros J, Vullierme MP, et al. Morphological imaging and CT histogram analysis to differentiate pancreatic neuroendocrine tumor grade 3 from neuroendocrine carcinoma. Diagn Interv Imaging. 2020;101:821–830.
Lucio Cascini G, Cuccurullo V, Tamburrini O, et al. Peptide imaging with somatostatin analogues: more than cancer probes. Curr Radiopharm. 2013;6:36–40.
Ilhan H, Lindner S, Todica A, et al. Biodistribution and first clinical results of 18F-SiFAlin-TATE PET: a novel 18F-labeled somatostatin analog for imaging of neuroendocrine tumors. Eur J Nucl Med Mol Imaging. 2020;47:870–880.
Hicks RJ, Jackson P, Kong G, et al. 64Cu-SARTATE PET imaging of patients with neuroendocrine tumors demonstrates high tumor uptake and retention, potentially allowing prospective dosimetry for peptide receptor radionuclide therapy. J Nucl Med. 2019;60:777–785.
Pauwels E, Cleeren F, Bormans G, et al. Somatostatin receptor PET ligands - the next generation for clinical practice. Am J Nucl Med Mol Imaging. 2018;8:311.
Adams LC, Bressem KK, Brangsch J, et al. Quantitative 3D assessment of 68Ga-DOTATOC PET/MRI with diffusion-weighted imaging to assess imaging markers for gastroenteropancreatic neuroendocrine tumors: preliminary results. J Nucl Med. 2020;61:1021–1027.
Carideo L, Prosperi D, Panzuto F, et al. Role of Combined [68Ga]Ga-DOTA-SST analogues and [18F]FDG PET/CT in the management of GEP-NENs: a systematic review. J Clin Med. 2019;8:1032.
Sansovini M, Severi S, Ianniello A, et al. Long-term follow-up and role of FDG PET in advanced pancreatic neuroendocrine patients treated with 177Lu-D OTATATE. Eur J Nucl Med Mol Imaging. 2017;44:490–499.
Alevroudis E, Spei M-E, Chatziioannou SN, et al. Clinical utility of 18F-FDG PET in neuroendocrine tumors prior to peptide receptor radionuclide therapy: a systematic review and meta-analysis. Cancers (Basel). 2021;13:1813.
Chan DL, Pavlakis N, Schembri GP, et al. Dual somatostatin receptor/FDG PET/CT imaging in metastatic neuroendocrine tumours: proposal for a novel grading scheme with prognostic significance. Theranostics. 2017;7:1149–1158.
Chan DL, Hayes AR, Karfis I, et al. Dual [68Ga]DOTATATE and [18F]FDG PET/CT in patients with metastatic gastroenteropancreatic neuroendocrine neoplasms: a multicentre validation of the NETPET score. Br J Cancer. 2023;128:549–555.
Chen L, Liu M, Bao J, et al. The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis. PLoS One. 2013;8:e79008.
Tacher V, Le Deley MC, Hollebecque A, et al. Factors associated with success of image-guided tumour biopsies: results from a prospective molecular triage study (MOSCATO-01). Eur J Cancer. 2016;59:79–89.
Wu M-H, Xiao L-F, Liu H-W, et al. PET/CT-guided versus CT-guided percutaneous core biopsies in the diagnosis of bone tumors and tumor-like lesions: which is the better choice? Cancer Imaging. 2019;19:69.
Gilson P, Merlin JL, Harlé A. Deciphering tumour heterogeneity: from tissue to liquid biopsy. Cancers (Basel). 2022;14:1384.
Drost FH, Osses DF, Nieboer D, et al. Prostate MRI, with or without MRI-targeted biopsy, and systematic biopsy for detecting prostate cancer. Cochrane Database Syst Rev. 2019;4:CD012663.
Wang R, Liu H, Liang P, et al. Radiomics analysis of CT imaging for differentiating gastric neuroendocrine carcinomas from gastric adenocarcinomas. Eur J Radiol. 2021;138:109662.
Staal FC, Taghavi M, Hong EK, et al. CT-based radiomics to distinguish progressive from stable neuroendocrine liver metastases treated with somatostatin analogues: an explorative study. Acta Radiol. 2023;64:1062–1070.
Ye J-Y, Fang P, Peng Z-P, et al. A radiomics-based interpretable model to predict the pathological grade of pancreatic neuroendocrine tumors. Eur Radiol. Epub ahead of print September 2. 2023.
Javed AA, Zhu Z, Kinny-Köster B, et al. Accurate non-invasive grading of nonfunctional pancreatic neuroendocrine tumors with a CT derived radiomics signature. Diagn Interv Imaging. 2024;105:33–39.
Zhu H-B, Zhu H-T, Jiang L, et al. Radiomics analysis from magnetic resonance imaging in predicting the grade of nonfunctioning pancreatic neuroendocrine tumors: a multicenter study. Eur Radiol. 2024;34:90–102.
Staal FCR, Aalbersberg EA, van der Velden D, et al. GEP-NET radiomics: a systematic review and radiomics quality score assessment. Eur Radiol. 2022;32:7278–7294.
Caruso D, Polici M, Rinzivillo M, et al. CT-based radiomics for prediction of therapeutic response to Everolimus in metastatic neuroendocrine tumors. Radiol Med. 2022;127:691–701.
Bezzi C, Mapelli P, Presotto L, et al. Radiomics in pancreatic neuroendocrine tumors: methodological issues and clinical significance. Eur J Nucl Med Mol Imaging. 2021;48:4002–4015.
Gu W, Chen Y, Zhu H, et al. Development and validation of CT-based radiomics deep learning signatures to predict lymph node metastasis in non-functional pancreatic neuroendocrine tumors: a multicohort study. EClinicalMedicine. 2023;65:102269.
Cozzi D, Bicci E, Cavigli E, et al. Radiomics in pulmonary neuroendocrine tumours (NETs). Radiol Med. 2022;127:609–615.
Bian Y, Jiang H, Ma C, et al. CT-based radiomics score for distinguishing between grade 1 and grade 2 nonfunctioning pancreatic neuroendocrine tumors. Am J Roentgenol. 2020;215:852–863.
Bian Y, Zhao Z, Jiang H, et al. Noncontrast radiomics approach for predicting grades of nonfunctional pancreatic neuroendocrine tumors. J Magn Reson Imaging. 2020;52:1124–1136.
Song T, Zhang Q-W, Duan S-F, et al. MRI-based radiomics approach for differentiation of hypovascular non-functional pancreatic neuroendocrine tumors and solid pseudopapillary neoplasms of the pancreas. BMC Med Imaging. 2021;21:36.
Mapelli P, Bezzi C, Palumbo D, et al. 68Ga-DOTATOC PET/MR imaging and radiomic parameters in predicting histopathological prognostic factors in patients with pancreatic neuroendocrine well-differentiated tumours. Eur J Nucl Med Mol Imaging. 2022;49:2352–2363.