Literature DB >> 20175134

Assessment of therapeutic response of locally advanced breast cancer (LABC) patients undergoing neoadjuvant chemotherapy (NACT) monitored using sequential magnetic resonance spectroscopic imaging (MRSI).

Karikanni Kalathil A Danishad1, Uma Sharma, Rani G Sah, Vurthaluru Seenu, Rajinder Parshad, Naranamangalam R Jagannathan.   

Abstract

The potential of total choline (tCho) signal-to-noise ratio (SNR) (ChoSNR) and tumor volume in the assessment of tumor response in locally advanced breast cancer (LABC) patients (n = 30) undergoing neoadjuvant chemotherapy (NACT) was investigated using magnetic resonance spectroscopic imaging (MRSI) and conventional MRI at 1.5 T. Experiments were carried out sequentially at four time-points: prior to therapy and after I, II and III NACT and ChoSNR, and the tumor volume was measured. The MR response was compared with the clinical response. Sequential data of 25 patients were retrospectively analyzed by classifying them as clinical responders and non-responders. In 14 responders, the pre-therapy ChoSNR was 7.8 +/- 5.1. In 10/14 responders, no choline was observed after III NACT while in the remaining four patients the ChoSNR was reduced to 3.6 +/- 1.1 (p < 0.05). Non-responders showed no statistically significant change in ChoSNR. After III NACT, the tumor volume reduced by 84.0 +/- 14.8% in responders. Using receiver operating curve (ROC) analysis, cut-off values of 53% for ChoSNR and 47.5% for volume were obtained to differentiate responders from non-responders. The sensitivity to detect responders from non-responders using ChoSNR was 85.7% with 91% specificity while 100% sensitivity was observed for volume but with reduced specificity of 73%. Our results indicate that ChoSNR may serve as a useful parameter to predict tumor response to NACT with higher specificity compared to volume, suggesting its potential in effective treatment management. 2010 John Wiley & Sons, Ltd.

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Year:  2010        PMID: 20175134     DOI: 10.1002/nbm.1436

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  34 in total

1.  In vivo proton MR spectroscopy of pancreatic neuroendocrine tumors in a multiple endocrine neoplasia type 1 conditional knockout mouse model.

Authors:  Min-Hui Cui; Craig A Branch; Sean M Cahill; Thomas J Quinn; Asha Adem; Steven K Libutti; Ziqiang Yuan
Journal:  Magn Reson Med       Date:  2014-11-13       Impact factor: 4.668

2.  Targeting choline phospholipid metabolism: GDPD5 and GDPD6 silencing decrease breast cancer cell proliferation, migration, and invasion.

Authors:  Maria Dung Cao; Menglin Cheng; Asif Rizwan; Lu Jiang; Balaji Krishnamachary; Zaver M Bhujwalla; Tone F Bathen; Kristine Glunde
Journal:  NMR Biomed       Date:  2016-06-30       Impact factor: 4.044

3.  CEST-MRI detects metabolite levels altered by breast cancer cell aggressiveness and chemotherapy response.

Authors:  Kannie W Y Chan; Lu Jiang; Menglin Cheng; Jannie P Wijnen; Guanshu Liu; Peng Huang; Peter C M van Zijl; Michael T McMahon; Kristine Glunde
Journal:  NMR Biomed       Date:  2016-04-21       Impact factor: 4.044

4.  MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial.

Authors:  Patrick J Bolan; Eunhee Kim; Benjamin A Herman; Gillian M Newstead; Mark A Rosen; Mitchell D Schnall; Etta D Pisano; Paul T Weatherall; Elizabeth A Morris; Constance D Lehman; Michael Garwood; Michael T Nelson; Douglas Yee; Sandra M Polin; Laura J Esserman; Constantine A Gatsonis; Gregory J Metzger; David C Newitt; Savannah C Partridge; Nola M Hylton
Journal:  J Magn Reson Imaging       Date:  2016-12-16       Impact factor: 4.813

Review 5.  Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer.

Authors:  Kanchan Sonkar; Vinay Ayyappan; Caitlin M Tressler; Oluwatobi Adelaja; Ruoqing Cai; Menglin Cheng; Kristine Glunde
Journal:  NMR Biomed       Date:  2019-06-11       Impact factor: 4.044

Review 6.  Proton MR spectroscopy in the breast: Technical innovations and clinical applications.

Authors:  Reza Fardanesh; Maria Adele Marino; Daly Avendano; Doris Leithner; Katja Pinker; Sunitha B Thakur
Journal:  J Magn Reson Imaging       Date:  2019-03-07       Impact factor: 4.813

Review 7.  Metabolic tumor imaging using magnetic resonance spectroscopy.

Authors:  Kristine Glunde; Zaver M Bhujwalla
Journal:  Semin Oncol       Date:  2011-02       Impact factor: 4.929

8.  Early prediction of response to neoadjuvant chemotherapy in breast cancer patients: comparison of single-voxel (1)H-magnetic resonance spectroscopy and (18)F-fluorodeoxyglucose positron emission tomography.

Authors:  Nariya Cho; Seock-Ah Im; Keon Wook Kang; In-Ae Park; In Chan Song; Kyung-Hun Lee; Tae-Yong Kim; Hyunjong Lee; In Kook Chun; Hai-Jeon Yoon; Woo Kyung Moon
Journal:  Eur Radiol       Date:  2015-09-17       Impact factor: 5.315

Review 9.  Multiparametric MR Imaging of Breast Cancer.

Authors:  Habib Rahbar; Savannah C Partridge
Journal:  Magn Reson Imaging Clin N Am       Date:  2016-02       Impact factor: 2.266

10.  Current and emerging quantitative magnetic resonance imaging methods for assessing and predicting the response of breast cancer to neoadjuvant therapy.

Authors:  Richard G Abramson; Lori R Arlinghaus; Jared A Weis; Xia Li; Adrienne N Dula; Eduard Y Chekmenev; Seth A Smith; Michael I Miga; Vandana G Abramson; Thomas E Yankeelov
Journal:  Breast Cancer (Dove Med Press)       Date:  2012-10
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