Cargando…

Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients?

The potential of total choline (tCho), apparent diffusion coefficient (ADC) and tumor volume, both individually and in combination of all these three parameters (multi-parametric approach), was evaluated in predicting both pathological and clinical responses in 42 patients with locally advanced brea...

Descripción completa

Detalles Bibliográficos
Autores principales: Sharma, Uma, Agarwal, Khushbu, Sah, Rani G., Parshad, Rajinder, Seenu, Vurthaluru, Mathur, Sandeep, Gupta, Siddhartha D., Jagannathan, Naranamangalam R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104482/
https://www.ncbi.nlm.nih.gov/pubmed/30159254
http://dx.doi.org/10.3389/fonc.2018.00319
_version_ 1783349497007439872
author Sharma, Uma
Agarwal, Khushbu
Sah, Rani G.
Parshad, Rajinder
Seenu, Vurthaluru
Mathur, Sandeep
Gupta, Siddhartha D.
Jagannathan, Naranamangalam R.
author_facet Sharma, Uma
Agarwal, Khushbu
Sah, Rani G.
Parshad, Rajinder
Seenu, Vurthaluru
Mathur, Sandeep
Gupta, Siddhartha D.
Jagannathan, Naranamangalam R.
author_sort Sharma, Uma
collection PubMed
description The potential of total choline (tCho), apparent diffusion coefficient (ADC) and tumor volume, both individually and in combination of all these three parameters (multi-parametric approach), was evaluated in predicting both pathological and clinical responses in 42 patients with locally advanced breast cancer (LABC) enrolled for neoadjuvant chemotherapy (NACT). Patients were sequentially examined by conventional MRI; diffusion weighted imaging and in vivo proton MR spectroscopy at 4 time points (pre-therapy, after I, II, and III NACT) at 1.5 T. Miller Payne grading system was used for pathological assessment of response. Of the 42 patients, 24 were pathological responders (pR) while 18 were pathological non-responders (pNR). Clinical response determination classified 26 patients as responders (cR) while 16 as non-responders (cNR). tCho and ADC showed significant changes after I NACT, however, MR measured tumor volume showed reduction only after II NACT both in pR and cR. After III NACT, the sensitivity to detect responders was highest for MR volume (83.3% for pR and 96.2% for cR) while the specificity was highest for ADC (76.5% for pR and 100% for cR). Combination of all three parameters exhibited lower sensitivity (66.7%) than MR volume for pR prediction, however, a moderate improvement was seen in specificity (58.8%). For the prediction of clinical response, multi-parametric approach showed 84.6% sensitivity with 100% specificity compared to MR volume (sensitivity 96.2%; specificity 80%). Kappa statistics demonstrated substantial agreement of clinical response with MR volume (k = 0.78) and with multi-parametric approach (k = 0.80) while moderate agreement was seen for tCho (k = 0.48) and ADC (k = 0.46). The values of k for tCho, MR volume and ADC were 0.31, 0.38, and 0.18 indicating fair, moderate, and slight agreement, respectively with pathological response. Moderate agreement (k = 0.44) was observed between clinical and pathological responses. Our study demonstrated that both tCho and ADC are strong predictors of assessment of early pathological and clinical responses. Multi-parametric approach yielded 100% specificity in predicting clinical response. Following III NACT, MR volume emerged as highly suitable predictor for both clinical and pathological assessments. PCA demonstrated separate clusters of pR vs. pNR and cR vs. cNR at post-therapy while with some overlap at pre-therapy.
format Online
Article
Text
id pubmed-6104482
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-61044822018-08-29 Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients? Sharma, Uma Agarwal, Khushbu Sah, Rani G. Parshad, Rajinder Seenu, Vurthaluru Mathur, Sandeep Gupta, Siddhartha D. Jagannathan, Naranamangalam R. Front Oncol Oncology The potential of total choline (tCho), apparent diffusion coefficient (ADC) and tumor volume, both individually and in combination of all these three parameters (multi-parametric approach), was evaluated in predicting both pathological and clinical responses in 42 patients with locally advanced breast cancer (LABC) enrolled for neoadjuvant chemotherapy (NACT). Patients were sequentially examined by conventional MRI; diffusion weighted imaging and in vivo proton MR spectroscopy at 4 time points (pre-therapy, after I, II, and III NACT) at 1.5 T. Miller Payne grading system was used for pathological assessment of response. Of the 42 patients, 24 were pathological responders (pR) while 18 were pathological non-responders (pNR). Clinical response determination classified 26 patients as responders (cR) while 16 as non-responders (cNR). tCho and ADC showed significant changes after I NACT, however, MR measured tumor volume showed reduction only after II NACT both in pR and cR. After III NACT, the sensitivity to detect responders was highest for MR volume (83.3% for pR and 96.2% for cR) while the specificity was highest for ADC (76.5% for pR and 100% for cR). Combination of all three parameters exhibited lower sensitivity (66.7%) than MR volume for pR prediction, however, a moderate improvement was seen in specificity (58.8%). For the prediction of clinical response, multi-parametric approach showed 84.6% sensitivity with 100% specificity compared to MR volume (sensitivity 96.2%; specificity 80%). Kappa statistics demonstrated substantial agreement of clinical response with MR volume (k = 0.78) and with multi-parametric approach (k = 0.80) while moderate agreement was seen for tCho (k = 0.48) and ADC (k = 0.46). The values of k for tCho, MR volume and ADC were 0.31, 0.38, and 0.18 indicating fair, moderate, and slight agreement, respectively with pathological response. Moderate agreement (k = 0.44) was observed between clinical and pathological responses. Our study demonstrated that both tCho and ADC are strong predictors of assessment of early pathological and clinical responses. Multi-parametric approach yielded 100% specificity in predicting clinical response. Following III NACT, MR volume emerged as highly suitable predictor for both clinical and pathological assessments. PCA demonstrated separate clusters of pR vs. pNR and cR vs. cNR at post-therapy while with some overlap at pre-therapy. Frontiers Media S.A. 2018-08-15 /pmc/articles/PMC6104482/ /pubmed/30159254 http://dx.doi.org/10.3389/fonc.2018.00319 Text en Copyright © 2018 Sharma, Agarwal, Sah, Parshad, Seenu, Mathur, Gupta and Jagannathan. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Sharma, Uma
Agarwal, Khushbu
Sah, Rani G.
Parshad, Rajinder
Seenu, Vurthaluru
Mathur, Sandeep
Gupta, Siddhartha D.
Jagannathan, Naranamangalam R.
Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients?
title Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients?
title_full Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients?
title_fullStr Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients?
title_full_unstemmed Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients?
title_short Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients?
title_sort can multi-parametric mr based approach improve the predictive value of pathological and clinical therapeutic response in breast cancer patients?
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104482/
https://www.ncbi.nlm.nih.gov/pubmed/30159254
http://dx.doi.org/10.3389/fonc.2018.00319
work_keys_str_mv AT sharmauma canmultiparametricmrbasedapproachimprovethepredictivevalueofpathologicalandclinicaltherapeuticresponseinbreastcancerpatients
AT agarwalkhushbu canmultiparametricmrbasedapproachimprovethepredictivevalueofpathologicalandclinicaltherapeuticresponseinbreastcancerpatients
AT sahranig canmultiparametricmrbasedapproachimprovethepredictivevalueofpathologicalandclinicaltherapeuticresponseinbreastcancerpatients
AT parshadrajinder canmultiparametricmrbasedapproachimprovethepredictivevalueofpathologicalandclinicaltherapeuticresponseinbreastcancerpatients
AT seenuvurthaluru canmultiparametricmrbasedapproachimprovethepredictivevalueofpathologicalandclinicaltherapeuticresponseinbreastcancerpatients
AT mathursandeep canmultiparametricmrbasedapproachimprovethepredictivevalueofpathologicalandclinicaltherapeuticresponseinbreastcancerpatients
AT guptasiddharthad canmultiparametricmrbasedapproachimprovethepredictivevalueofpathologicalandclinicaltherapeuticresponseinbreastcancerpatients
AT jagannathannaranamangalamr canmultiparametricmrbasedapproachimprovethepredictivevalueofpathologicalandclinicaltherapeuticresponseinbreastcancerpatients