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Automatic Prediction and Assessment of Treatment Response in Patients with Hodgkin’s Lymphoma Using a Whole-Body DW-MRI Based Approach

The lack of validation and standardization represents the main drawback for a clear role of whole-body diffusion weighted imaging (WB-DWI) for prediction and assessment of treatment response in Hodgkin’s lymphoma (HL). We explored the reliability of an automatic approach based on the WB-DWI techniqu...

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Autores principales: Brancato, Valentina, Aiello, Marco, Della Pepa, Roberta, Basso, Luca, Garbino, Nunzia, Nicolai, Emanuele, Picardi, Marco, Salvatore, Marco, Cavaliere, Carlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555579/
https://www.ncbi.nlm.nih.gov/pubmed/32948043
http://dx.doi.org/10.3390/diagnostics10090702
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author Brancato, Valentina
Aiello, Marco
Della Pepa, Roberta
Basso, Luca
Garbino, Nunzia
Nicolai, Emanuele
Picardi, Marco
Salvatore, Marco
Cavaliere, Carlo
author_facet Brancato, Valentina
Aiello, Marco
Della Pepa, Roberta
Basso, Luca
Garbino, Nunzia
Nicolai, Emanuele
Picardi, Marco
Salvatore, Marco
Cavaliere, Carlo
author_sort Brancato, Valentina
collection PubMed
description The lack of validation and standardization represents the main drawback for a clear role of whole-body diffusion weighted imaging (WB-DWI) for prediction and assessment of treatment response in Hodgkin’s lymphoma (HL). We explored the reliability of an automatic approach based on the WB-DWI technique for prediction and assessment of response to treatment in patients with HL. The study included 20 HL patients, who had whole-body positron emission tomography (PET)/ magnetic resonance Imaging (MRI) performed before, during and after chemotherapy. Using the syngo.via MR Total Tumor Load tool, we automatically extracted values of diffusion volume (DV) and its associated histogram features by WB-DWI images, and evaluated their utility in predicting and assessing interim and end-of-treatment (EOT) response. The Mann–Whitney test followed by receiver operator characteristic (ROC) analysis was performed between features and their inter-time point percentage differences for patients having a complete or partial treatment response, revealing that several WB-DWI associated features allowed for prediction of interim response and both prediction and assessment of EOT response. Our proposed method offers huge advantages in terms of saving time and work, enabling clinicians to draw conclusions relating to HL treatment response in a fully automatic way, and encloses, also, all DWI advantages compared to PET/ computed tomography (CT).
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spelling pubmed-75555792020-10-19 Automatic Prediction and Assessment of Treatment Response in Patients with Hodgkin’s Lymphoma Using a Whole-Body DW-MRI Based Approach Brancato, Valentina Aiello, Marco Della Pepa, Roberta Basso, Luca Garbino, Nunzia Nicolai, Emanuele Picardi, Marco Salvatore, Marco Cavaliere, Carlo Diagnostics (Basel) Article The lack of validation and standardization represents the main drawback for a clear role of whole-body diffusion weighted imaging (WB-DWI) for prediction and assessment of treatment response in Hodgkin’s lymphoma (HL). We explored the reliability of an automatic approach based on the WB-DWI technique for prediction and assessment of response to treatment in patients with HL. The study included 20 HL patients, who had whole-body positron emission tomography (PET)/ magnetic resonance Imaging (MRI) performed before, during and after chemotherapy. Using the syngo.via MR Total Tumor Load tool, we automatically extracted values of diffusion volume (DV) and its associated histogram features by WB-DWI images, and evaluated their utility in predicting and assessing interim and end-of-treatment (EOT) response. The Mann–Whitney test followed by receiver operator characteristic (ROC) analysis was performed between features and their inter-time point percentage differences for patients having a complete or partial treatment response, revealing that several WB-DWI associated features allowed for prediction of interim response and both prediction and assessment of EOT response. Our proposed method offers huge advantages in terms of saving time and work, enabling clinicians to draw conclusions relating to HL treatment response in a fully automatic way, and encloses, also, all DWI advantages compared to PET/ computed tomography (CT). MDPI 2020-09-16 /pmc/articles/PMC7555579/ /pubmed/32948043 http://dx.doi.org/10.3390/diagnostics10090702 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Brancato, Valentina
Aiello, Marco
Della Pepa, Roberta
Basso, Luca
Garbino, Nunzia
Nicolai, Emanuele
Picardi, Marco
Salvatore, Marco
Cavaliere, Carlo
Automatic Prediction and Assessment of Treatment Response in Patients with Hodgkin’s Lymphoma Using a Whole-Body DW-MRI Based Approach
title Automatic Prediction and Assessment of Treatment Response in Patients with Hodgkin’s Lymphoma Using a Whole-Body DW-MRI Based Approach
title_full Automatic Prediction and Assessment of Treatment Response in Patients with Hodgkin’s Lymphoma Using a Whole-Body DW-MRI Based Approach
title_fullStr Automatic Prediction and Assessment of Treatment Response in Patients with Hodgkin’s Lymphoma Using a Whole-Body DW-MRI Based Approach
title_full_unstemmed Automatic Prediction and Assessment of Treatment Response in Patients with Hodgkin’s Lymphoma Using a Whole-Body DW-MRI Based Approach
title_short Automatic Prediction and Assessment of Treatment Response in Patients with Hodgkin’s Lymphoma Using a Whole-Body DW-MRI Based Approach
title_sort automatic prediction and assessment of treatment response in patients with hodgkin’s lymphoma using a whole-body dw-mri based approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555579/
https://www.ncbi.nlm.nih.gov/pubmed/32948043
http://dx.doi.org/10.3390/diagnostics10090702
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