Literature DB >> 18374468

Vascularity change and tumor response to neoadjuvant chemotherapy for advanced breast cancer.

Wen-Hung Kuo1, Chiung-Nien Chen, Fon-Jou Hsieh, Ming-Kwang Shyu, Li-Yun Chang, Po-Huang Lee, Li-Yu D Liu, Chia-Hsien Cheng, Jane Wang, King-Jen Chang.   

Abstract

For advanced breast cancer with severe local disease (ABC) (stage III/IV), neoadjuvant chemotherapy improves local control and surgical outcome. However, about approximately 20 to 30% of advanced cancers show either no or poor response to chemotherapy. To prevent unnecessary treatment, a capability of predicting clinical response to neoadjuvant chemotherapy of ABC is highly desirable. Vascularity index (VI) of breast cancers was derived from the quantification results in 30 ABC patients by using power Doppler sonography. Power Doppler sonography evaluation was performed every one to two weeks during chemotherapy. The overall response rate for 30 advanced patients tested was 70%, when 50% or more reduction in tumor size was the objective clinical response. Chemotherapy response was unrelated to the original tumor size (p = 0.563) or chemotherapy agents used (p = 0.657). The median VI for all 30 patients was 4.99%. The response rates for hypervascular tumors vs. hypovascular tumors, based on initial median value, were 86.7% and 53.3%, respectively (p = 0.109). The average VIs in responders and nonresponders were 7.67 +/- 4.77% and 4.01 +/- 3.82% (p = 0.052). There was a tendency for responders who have a relatively high initial vascularity. The VI change in responder group shows a pattern of initial increasing in vascularity followed by decreasing in vascularity. All patients (17/17) with a VI increment of >5% during chemotherapy had good chemotherapy response, whereas in patients with a VI increment of <5%, the response rate was 30.8% (4/13) (p < 0.001). For patients with a peak VI of >10% during chemotherapy, the response rate was 94.1% (16/17). However, in patients with a peak VI of <10%, the response rate was 38.5% (5/13) (p = 0.001). This prediction was made mostly within one month (25.47 +/- 12.96 d for VI increments >5% and 25.44 +/- 12.41 d for VI increased to >10%). In the meantime, the differences in size reduction shown in B-mode sonography were insignificant between responders and nonresponders (patient group with VI increment >5%, p = 0.308; patient group with peak VI >10%, p = 0.396). In conclusion, we propose that VI as determined by using power Doppler sonography is a good and inexpensive clinical tool for monitoring vascularity changes during neoadjuvant chemotherapy in ABC patients. Two parameters--VI increment >5% and peak VI >10%--are potential early predictors for good responses to neoadjuvant chemotherapy within one month in patients with ABC.

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Year:  2008        PMID: 18374468     DOI: 10.1016/j.ultrasmedbio.2007.11.011

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  7 in total

1.  A computer-aided diagnosis (CAD) scheme for pretreatment prediction of pathological response to neoadjuvant therapy using dynamic contrast-enhanced MRI texture features.

Authors:  Valentina Giannini; Simone Mazzetti; Agnese Marmo; Filippo Montemurro; Daniele Regge; Laura Martincich
Journal:  Br J Radiol       Date:  2017-07-14       Impact factor: 3.039

2.  Dynamic Diffuse Optical Tomography for Monitoring Neoadjuvant Chemotherapy in Patients with Breast Cancer.

Authors:  Jacqueline E Gunther; Emerson A Lim; Hyun K Kim; Molly Flexman; Mirella Altoé; Jessica A Campbell; Hanina Hibshoosh; Katherine D Crew; Kevin Kalinsky; Dawn L Hershman; Andreas H Hielscher
Journal:  Radiology       Date:  2018-02-12       Impact factor: 11.105

3.  Monitoring Neoadjuvant Chemotherapy for Breast Cancer by Using Three-dimensional Subharmonic Aided Pressure Estimation and Imaging with US Contrast Agents: Preliminary Experience.

Authors:  Kibo Nam; John R Eisenbrey; Maria Stanczak; Anush Sridharan; Adam C Berger; Tiffany Avery; Juan P Palazzo; Flemming Forsberg
Journal:  Radiology       Date:  2017-05-03       Impact factor: 11.105

4.  Breast cancer: assessing response to neoadjuvant chemotherapy by using US-guided near-infrared tomography.

Authors:  Quing Zhu; Patricia A DeFusco; Andrew Ricci; Edward B Cronin; Poornima U Hegde; Mark Kane; Behnoosh Tavakoli; Yan Xu; Jesse Hart; Susan H Tannenbaum
Journal:  Radiology       Date:  2012-12-21       Impact factor: 11.105

5.  Higher underestimation of tumour size post-neoadjuvant chemotherapy with breast magnetic resonance imaging (MRI)-A concordance comparison cohort analysis.

Authors:  Wen-Pei Wu; Hwa-Koon Wu; Chih-Jung Chen; Chih-Wie Lee; Shou-Tung Chen; Dar-Ren Chen; Chen-Te Chou; Chi Wei Mok; Hung-Wen Lai
Journal:  PLoS One       Date:  2019-10-10       Impact factor: 3.240

6.  Machine Learning Models and Multiparametric Magnetic Resonance Imaging for the Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer.

Authors:  Carmen Herrero Vicent; Xavier Tudela; Paula Moreno Ruiz; Víctor Pedralva; Ana Jiménez Pastor; Daniel Ahicart; Silvia Rubio Novella; Isabel Meneu; Ángela Montes Albuixech; Miguel Ángel Santamaria; María Fonfria; Almudena Fuster-Matanzo; Santiago Olmos Antón; Eduardo Martínez de Dueñas
Journal:  Cancers (Basel)       Date:  2022-07-19       Impact factor: 6.575

7.  Diffusion weighted imaging evaluated the early therapy effect of tamoxifen in an MNU-induced mammary cancer rat model.

Authors:  Guihua Zhai; Clinton J Grubbs; Cecil R Stockard; Heidi R Umphrey; T Mark Beasley; Hyunki Kim
Journal:  PLoS One       Date:  2013-05-21       Impact factor: 3.240

  7 in total

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