Literature DB >> 33799913

Semi-Automated Segmentation of Bone Metastases from Whole-Body MRI: Reproducibility of Apparent Diffusion Coefficient Measurements.

Alberto Colombo1, Giulia Saia1, Alcide A Azzena2, Alice Rossi3, Fabio Zugni1, Paola Pricolo1, Paul E Summers1, Giulia Marvaso4,5, Robert Grimm6, Massimo Bellomi1,5, Barbara A Jereczek-Fossa4,5, Anwar R Padhani7, Giuseppe Petralia5,8.   

Abstract

Using semi-automated software simplifies quantitative analysis of the visible burden of disease on whole-body MRI diffusion-weighted images. To establish the intra- and inter-observer reproducibility of apparent diffusion coefficient (ADC) measures, we retrospectively analyzed data from 20 patients with bone metastases from breast (BCa; n = 10; aged 62.3 ± 14.8) or prostate cancer (PCa; n = 10; aged 67.4 ± 9.0) who had undergone examinations at two timepoints, before and after hormone-therapy. Four independent observers processed all images twice, first segmenting the entire skeleton on diffusion-weighted images, and then isolating bone metastases via ADC histogram thresholding (ADC: 650-1400 µm2/s). Dice Similarity, Bland-Altman method, and Intraclass Correlation Coefficient were used to assess reproducibility. Inter-observer Dice similarity was moderate (0.71) for women with BCa and poor (0.40) for men with PCa. Nonetheless, the limits of agreement of the mean ADC were just ±6% for women with BCa and ±10% for men with PCa (mean ADCs: 941 and 999 µm2/s, respectively). Inter-observer Intraclass Correlation Coefficients of the ADC histogram parameters were consistently greater in women with BCa than in men with PCa. While scope remains for improving consistency of the volume segmented, the observer-dependent variability measured in this study was appropriate to distinguish the clinically meaningful changes of ADC observed in patients responding to therapy, as changes of at least 25% are of interest.

Entities:  

Keywords:  ADC; DWI; WB-MRI; bone metastases; quantitative analysis; reproducibility

Year:  2021        PMID: 33799913      PMCID: PMC7998160          DOI: 10.3390/diagnostics11030499

Source DB:  PubMed          Journal:  Diagnostics (Basel)        ISSN: 2075-4418


  39 in total

1.  Diffusion-weighted Imaging as a Treatment Response Biomarker for Evaluating Bone Metastases in Prostate Cancer: A Pilot Study.

Authors:  Raquel Perez-Lopez; Joaquin Mateo; Helen Mossop; Matthew D Blackledge; David J Collins; Mihaela Rata; Veronica A Morgan; Alison Macdonald; Shahneen Sandhu; David Lorente; Pasquale Rescigno; Zafeiris Zafeiriou; Diletta Bianchini; Nuria Porta; Emma Hall; Martin O Leach; Johann S de Bono; Dow-Mu Koh; Nina Tunariu
Journal:  Radiology       Date:  2016-11-22       Impact factor: 11.105

2.  High Signal in Bone Marrow on Diffusion-Weighted Imaging of Female Pelvis: Correlation With Anemia and Fibroid-Associated Symptoms.

Authors:  Ying-Yuan Chen; Ching-Lan Wu; Shu-Huei Shen
Journal:  J Magn Reson Imaging       Date:  2018-03-05       Impact factor: 4.813

3.  Extracranial Soft-Tissue Tumors: Repeatability of Apparent Diffusion Coefficient Estimates from Diffusion-weighted MR Imaging.

Authors:  Jessica M Winfield; Nina Tunariu; Mihaela Rata; Keiko Miyazaki; Neil P Jerome; Michael Germuska; Matthew D Blackledge; David J Collins; Johann S de Bono; Timothy A Yap; Nandita M deSouza; Simon J Doran; Dow-Mu Koh; Martin O Leach; Christina Messiou; Matthew R Orton
Journal:  Radiology       Date:  2017-03-16       Impact factor: 11.105

4.  Computed diffusion-weighted MR imaging may improve tumor detection.

Authors:  Matthew D Blackledge; Martin O Leach; David J Collins; Dow-Mu Koh
Journal:  Radiology       Date:  2011-08-18       Impact factor: 11.105

5.  Assessment of treatment response by total tumor volume and global apparent diffusion coefficient using diffusion-weighted MRI in patients with metastatic bone disease: a feasibility study.

Authors:  Matthew D Blackledge; David J Collins; Nina Tunariu; Matthew R Orton; Anwar R Padhani; Martin O Leach; Dow-Mu Koh
Journal:  PLoS One       Date:  2014-04-07       Impact factor: 3.240

6.  Differentiation of multiple myeloma and metastases: Use of axial diffusion-weighted MR imaging in addition to standard MR imaging at 3T.

Authors:  Ga Eun Park; Won-Hee Jee; So-Yeon Lee; Jin-Kyeong Sung; Joon-Yong Jung; Robert Grimm; Yohan Son; Mun Young Paek; Chang-Kee Min; Kee-Yong Ha
Journal:  PLoS One       Date:  2018-12-17       Impact factor: 3.240

7.  Guidelines for Acquisition, Interpretation, and Reporting of Whole-Body MRI in Myeloma: Myeloma Response Assessment and Diagnosis System (MY-RADS).

Authors:  Christina Messiou; Jens Hillengass; Stefan Delorme; Frédéric E Lecouvet; Lia A Moulopoulos; David J Collins; Matthew D Blackledge; Niels Abildgaard; Brian Østergaard; Heinz-Peter Schlemmer; Ola Landgren; Jon Thor Asmussen; Martin F Kaiser; Anwar Padhani
Journal:  Radiology       Date:  2019-02-26       Impact factor: 11.105

8.  Volume of Bone Metastasis Assessed with Whole-Body Diffusion-weighted Imaging Is Associated with Overall Survival in Metastatic Castration-resistant Prostate Cancer.

Authors:  Raquel Perez-Lopez; David Lorente; Matthew D Blackledge; David J Collins; Joaquin Mateo; Diletta Bianchini; Aurelius Omlin; Andrea Zivi; Martin O Leach; Johann S de Bono; Dow-Mu Koh; Nina Tunariu
Journal:  Radiology       Date:  2016-01-25       Impact factor: 11.105

9.  Inter- and Intra-Observer Repeatability of Quantitative Whole-Body, Diffusion-Weighted Imaging (WBDWI) in Metastatic Bone Disease.

Authors:  Matthew D Blackledge; Nina Tunariu; Matthew R Orton; Anwar R Padhani; David J Collins; Martin O Leach; Dow-Mu Koh
Journal:  PLoS One       Date:  2016-04-28       Impact factor: 3.240

10.  Whole-body magnetic resonance imaging (WB-MRI) reporting with the METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P): inter-observer agreement between readers of different expertise levels.

Authors:  Paola Pricolo; Eleonora Ancona; Paul Summers; Jorge Abreu-Gomez; Sarah Alessi; Barbara Alicja Jereczek-Fossa; Ottavio De Cobelli; Franco Nolè; Giuseppe Renne; Massimo Bellomi; Anwar Roshanali Padhani; Giuseppe Petralia
Journal:  Cancer Imaging       Date:  2020-10-27       Impact factor: 3.909

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  3 in total

1.  Detection and Segmentation of Pelvic Bones Metastases in MRI Images for Patients With Prostate Cancer Based on Deep Learning.

Authors:  Xiang Liu; Chao Han; Yingpu Cui; Tingting Xie; Xiaodong Zhang; Xiaoying Wang
Journal:  Front Oncol       Date:  2021-11-29       Impact factor: 6.244

2.  Effects of Sex and Age on Fat Fraction, Diffusion-Weighted Image Signal Intensity and Apparent Diffusion Coefficient in the Bone Marrow of Asymptomatic Individuals: A Cross-Sectional Whole-Body MRI Study.

Authors:  Alberto Colombo; Luca Bombelli; Paul E Summers; Giulia Saia; Fabio Zugni; Giulia Marvaso; Robert Grimm; Barbara A Jereczek-Fossa; Anwar R Padhani; Giuseppe Petralia
Journal:  Diagnostics (Basel)       Date:  2021-05-20

Review 3.  Whole-Body Magnetic Resonance Imaging: Current Role in Patients with Lymphoma.

Authors:  Domenico Albano; Giuseppe Micci; Caterina Patti; Federico Midiri; Silvia Albano; Giuseppe Lo Re; Emanuele Grassedonio; Ludovico La Grutta; Roberto Lagalla; Massimo Galia
Journal:  Diagnostics (Basel)       Date:  2021-05-31
  3 in total

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