Literature DB >> 29352378

Can histogram analysis of MR images predict aggressiveness in pancreatic neuroendocrine tumors?

Riccardo De Robertis1, Bogdan Maris2, Nicolò Cardobi3, Paolo Tinazzi Martini3, Stefano Gobbo4, Paola Capelli5, Silvia Ortolani6, Sara Cingarlini7, Salvatore Paiella8, Luca Landoni8, Giovanni Butturini9, Paolo Regi9, Aldo Scarpa5, Giampaolo Tortora7, Mirko D'Onofrio10.   

Abstract

OBJECTIVES: To evaluate MRI derived whole-tumour histogram analysis parameters in predicting pancreatic neuroendocrine neoplasm (panNEN) grade and aggressiveness.
METHODS: Pre-operative MR of 42 consecutive patients with panNEN >1 cm were retrospectively analysed. T1-/T2-weighted images and ADC maps were analysed. Histogram-derived parameters were compared to histopathological features using the Mann-Whitney U test. Diagnostic accuracy was assessed by ROC-AUC analysis; sensitivity and specificity were assessed for each histogram parameter.
RESULTS: ADCentropy was significantly higher in G2-3 tumours with ROC-AUC 0.757; sensitivity and specificity were 83.3 % (95 % CI: 61.2-94.5) and 61.1 % (95 % CI: 36.1-81.7). ADCkurtosis was higher in panNENs with vascular involvement, nodal and hepatic metastases (p= .008, .021 and .008; ROC-AUC= 0.820, 0.709 and 0.820); sensitivity and specificity were: 85.7/74.3 % (95 % CI: 42-99.2 /56.4-86.9), 36.8/96.5 % (95 % CI: 17.2-61.4 /76-99.8) and 100/62.8 % (95 % CI: 56.1-100/44.9-78.1). No significant differences between groups were found for other histogram-derived parameters (p >.05).
CONCLUSIONS: Whole-tumour histogram analysis of ADC maps may be helpful in predicting tumour grade, vascular involvement, nodal and liver metastases in panNENs. ADCentropy and ADCkurtosis are the most accurate parameters for identification of panNENs with malignant behaviour. KEY POINTS: • Whole-tumour ADC histogram analysis can predict aggressiveness in pancreatic neuroendocrine neoplasms. • ADC entropy and kurtosis are higher in aggressive tumours. • ADC histogram analysis can quantify tumour diffusion heterogeneity. • Non-invasive quantification of tumour heterogeneity can provide adjunctive information for prognostication.

Entities:  

Keywords:  Magnetic resonance imaging; Neuroendocrine neoplasm; Neuroendocrine tumour; Pancreas; Pancreatic neoplasms

Mesh:

Year:  2018        PMID: 29352378     DOI: 10.1007/s00330-017-5236-7

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  35 in total

1.  Pancreatic neuroendocrine tumour grading on endoscopic ultrasound-guided fine needle aspiration: high reproducibility and inter-observer agreement of the Ki-67 labelling index.

Authors:  B Weynand; I Borbath; V Bernard; C Sempoux; J-F Gigot; C Hubert; V Lannoy; P H Deprez; A Jouret-Mourin
Journal:  Cytopathology       Date:  2013-11-15       Impact factor: 2.073

2.  Is the combination of MR and CT findings useful in determining the tumor grade of pancreatic neuroendocrine tumors?

Authors:  Fumihito Toshima; Dai Inoue; Takahiro Komori; Kotaro Yoshida; Norihide Yoneda; Tetsuya Minami; Osamu Matsui; Hiroko Ikeda; Toshifumi Gabata
Journal:  Jpn J Radiol       Date:  2017-03-03       Impact factor: 2.374

3.  Non-invasive quantification of tumour heterogeneity in water diffusivity to differentiate malignant from benign tissues of urinary bladder: a phase I study.

Authors:  Huyen T Nguyen; Zarine K Shah; Amir Mortazavi; Kamal S Pohar; Lai Wei; Guang Jia; Debra L Zynger; Michael V Knopp
Journal:  Eur Radiol       Date:  2016-08-23       Impact factor: 5.315

4.  Evaluation of Ki-67 index in EUS-FNA specimens for the assessment of malignancy risk in pancreatic neuroendocrine tumors.

Authors:  Toshiyuki Hasegawa; Kenji Yamao; Susumu Hijioka; Vikram Bhatia; Nobumasa Mizuno; Kazuo Hara; Hiroshi Imaoka; Yasumasa Niwa; Masahiro Tajika; Shinya Kondo; Tutomu Tanaka; Yasuhiro Shimizu; Taira Kinoshita; Takuhiro Kohsaki; Isao Nishimori; Shinji Iwasaki; Toshiji Saibara; Waki Hosoda; Yasushi Yatabe
Journal:  Endoscopy       Date:  2013-11-11       Impact factor: 10.093

5.  ADC histogram analysis for adrenal tumor histogram analysis of apparent diffusion coefficient in differentiating adrenal adenoma from pheochromocytoma.

Authors:  Tomokazu Umanodan; Yoshihiko Fukukura; Yuichi Kumagae; Toshikazu Shindo; Masatoyo Nakajo; Koji Takumi; Masanori Nakajo; Hiroto Hakamada; Aya Umanodan; Takashi Yoshiura
Journal:  J Magn Reson Imaging       Date:  2016-08-29       Impact factor: 4.813

6.  Utility of histogram analysis of ADC maps for differentiating orbital tumors.

Authors:  Xiao-Quan Xu; Hao Hu; Guo-Yi Su; Hu Liu; Xun-Ning Hong; Hai-Bin Shi; Fei-Yun Wu
Journal:  Diagn Interv Radiol       Date:  2016 Mar-Apr       Impact factor: 2.630

Review 7.  Improving tumour heterogeneity MRI assessment with histograms.

Authors:  N Just
Journal:  Br J Cancer       Date:  2014-09-30       Impact factor: 7.640

8.  Pancreatic neuroendocrine neoplasms: Magnetic resonance imaging features according to grade and stage.

Authors:  Riccardo De Robertis; Sara Cingarlini; Paolo Tinazzi Martini; Silvia Ortolani; Giovanni Butturini; Luca Landoni; Paolo Regi; Roberto Girelli; Paola Capelli; Stefano Gobbo; Giampaolo Tortora; Aldo Scarpa; Paolo Pederzoli; Mirko D'Onofrio
Journal:  World J Gastroenterol       Date:  2017-01-14       Impact factor: 5.742

9.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105

10.  "Textural analysis of multiparametric MRI detects transition zone prostate cancer".

Authors:  Harbir S Sidhu; Salvatore Benigno; Balaji Ganeshan; Nikos Dikaios; Edward W Johnston; Clare Allen; Alex Kirkham; Ashley M Groves; Hashim U Ahmed; Mark Emberton; Stuart A Taylor; Steve Halligan; Shonit Punwani
Journal:  Eur Radiol       Date:  2016-09-12       Impact factor: 5.315

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  19 in total

1.  Deep learning for World Health Organization grades of pancreatic neuroendocrine tumors on contrast-enhanced magnetic resonance images: a preliminary study.

Authors:  Xuan Gao; Xiaolin Wang
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-09-26       Impact factor: 2.924

2.  Apparent Diffusion Coefficient Histogram Analysis for Assessing Tumor Staging and Detection of Lymph Node Metastasis in Epithelial Ovarian Cancer: Correlation with p53 and Ki-67 Expression.

Authors:  Feng Wang; Yuxiang Wang; Yan Zhou; Congrong Liu; Dong Liang; Lizhi Xie; Zhihang Yao; Jianyu Liu
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

Review 3.  CT and MRI of pancreatic tumors: an update in the era of radiomics.

Authors:  Marion Bartoli; Maxime Barat; Anthony Dohan; Sébastien Gaujoux; Romain Coriat; Christine Hoeffel; Christophe Cassinotto; Guillaume Chassagnon; Philippe Soyer
Journal:  Jpn J Radiol       Date:  2020-10-21       Impact factor: 2.374

4.  Magnetic resonance imaging radiomic analysis can preoperatively predict G1 and G2/3 grades in patients with NF-pNETs.

Authors:  Yun Bian; Jing Li; Kai Cao; Xu Fang; Hui Jiang; Chao Ma; Gang Jin; Jianping Lu; Li Wang
Journal:  Abdom Radiol (NY)       Date:  2020-08-17

5.  Volumetric Histogram Analysis of Apparent Diffusion Coefficient as a Biomarker to Predict Survival of Esophageal Cancer Patients.

Authors:  Atsushi Hirata; Koichi Hayano; Gaku Ohira; Shunsuke Imanishi; Toshiharu Hanaoka; Takeshi Toyozumi; Kentaro Murakami; Tomoyoshi Aoyagi; Kiyohiko Shuto; Hisahiro Matsubara
Journal:  Ann Surg Oncol       Date:  2020-02-25       Impact factor: 5.344

Review 6.  Quantitative pancreatic MRI: a pathology-based review.

Authors:  Manil D Chouhan; Louisa Firmin; Samantha Read; Zahir Amin; Stuart A Taylor
Journal:  Br J Radiol       Date:  2019-06-14       Impact factor: 3.039

7.  Volumetric apparent diffusion coefficient histogram analysis of the testes in nonobstructive azoospermia: a noninvasive fingerprint of impaired spermatogenesis?

Authors:  Athina C Tsili; Loukas G Astrakas; Anna C Goussia; Nikolaos Sofikitis; Maria I Argyropoulou
Journal:  Eur Radiol       Date:  2022-04-29       Impact factor: 5.315

Review 8.  GEP-NET radiomics: a systematic review and radiomics quality score assessment.

Authors:  Femke C R Staal; Else A Aalbersberg; Daphne van der Velden; Erica A Wilthagen; Margot E T Tesselaar; Regina G H Beets-Tan; Monique Maas
Journal:  Eur Radiol       Date:  2022-07-26       Impact factor: 7.034

9.  Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer.

Authors:  Mayra Evelia Jiménez de Los Santos; Juan Armando Reyes-Pérez; Victor Domínguez Osorio; Yolanda Villaseñor-Navarro; Liliana Moreno-Astudillo; Itzel Vela-Sarmiento; Isabel Sollozo-Dupont
Journal:  World J Gastroenterol       Date:  2022-06-21       Impact factor: 5.374

Review 10.  New frontiers in imaging including radiomics updates for pancreatic neuroendocrine neoplasms.

Authors:  Mohammed Saleh; Priya R Bhosale; Motoyo Yano; Malak Itani; Ahmed K Elsayes; Daniel Halperin; Emily K Bergsland; Ajaykumar C Morani
Journal:  Abdom Radiol (NY)       Date:  2020-10-23
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