title: Predicting pathologic response to neoadjuvant chemotherapy in breast cancer by using MR imaging and quantitative 1H MR spectroscopy.
abstract: OBJECTIVE
  To compare changes in the concentration of choline-containing compounds (tCho) and in tumor size at follow-up after neoadjuvant chemotherapy (NAC) between patients who achieved pathologic complete response (pCR) and those who did not (non-pCR).
  
  
  METHODS
  This study was approved by the institutional review board and was compliant with HIPAA; each patient gave informed consent. Thirty-five patients (mean age, 48 years +/- 11 [standard deviation]; range, 29-75 years) with breast cancer were included. Treatment included doxorubicin and cyclophosphamide followed by a taxane-based regimen. Changes in tCho and tumor size in pCR versus non-pCR groups were compared by using the two-way Mann-Whitney nonparametric test. Receiver operating characteristic (ROC) analysis was performed to differentiate between them and the area under the ROC curve (AUC) was compared.
  
  
  RESULTS
  In the pCR group, the tCho level change was greater compared with change in tumor size (P = .003 at first follow-up, P = .01 at second follow-up), but they were not significantly different in the non-pCR group. Changes in tumor size and tCho level at the first follow-up study were not significantly different between the pCR and non-pCR groups but reached significance at the second follow-up. In ROC analysis, the magnetic resonance (MR) imaging and MR spectroscopic parameters had AUCs of 0.65-0.68 at first follow-up; at second follow-up, AUC for change in tumor size was 0.9, AUC for change in tCho was 0.73.
  
  
  CONCLUSIONS
  Patients who show greater reduction in tCho compared with changes in tumor size are more likely to achieve pCR. The change in tumor size halfway through therapy was the most accurate predictor of pCR.
authors.affiliation: Tu & Yuen Center for Functional Onco-Imaging, University of California, Irvine Hall 164, Irvine, CA 92697-5020, USA.
authors.forename: Hyeon-Man
authors.initials: HM
authors.lastname: Baek
authors.forename: Jeon-Hor
authors.initials: JH
authors.lastname: Chen
authors.forename: Ke
authors.initials: K
authors.lastname: Nie
authors.forename: Hon J
authors.initials: HJ
authors.lastname: Yu
authors.forename: Shadfar
authors.initials: S
authors.lastname: Bahri
authors.forename: Rita S
authors.initials: RS
authors.lastname: Mehta
authors.forename: Orhan
authors.initials: O
authors.lastname: Nalcioglu
authors.forename: Min-Ying
authors.initials: MY
authors.lastname: Su
mesh_terms: D000328:Adult; D000368:Aged; D000911:Antibodies, Monoclonal / Q000008:administration & dosage; D061067:Antibodies, Monoclonal, Humanized; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use*; D000068258:Bevacizumab; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000378:metabolism / Q000473:pathology*; D016190:Carboplatin / Q000008:administration & dosage; D017024:Chemotherapy, Adjuvant; D002794:Choline / Q000378:metabolism; D003287:Contrast Media; D003520:Cyclophosphamide / Q000008:administration & dosage; D004317:Doxorubicin / Q000008:administration & dosage; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D009682:Magnetic Resonance Spectroscopy; D008875:Middle Aged; D020360:Neoadjuvant Therapy; D017239:Paclitaxel / Q000008:administration & dosage; D012372:ROC Curve; D018709:Statistics, Nonparametric; D000068878:Trastuzumab; D016896:Treatment Outcome
chemical_list: D000911:Antibodies, Monoclonal; D061067:Antibodies, Monoclonal, Humanized; D003287:Contrast Media; D000068258:Bevacizumab; D004317:Doxorubicin; D003520:Cyclophosphamide; D016190:Carboplatin; D002794:Choline; D000068878:Trastuzumab; D017239:Paclitaxel