title: Prediction model of chemotherapy response in osteosarcoma by 18F-FDG PET and MRI.
abstract: Response to neoadjuvant chemotherapy is a significant prognostic factor for osteosarcoma; however, this information can be determined only after surgical resection. If we could predict histologic response before surgery, it might be helpful for the planning of surgeries and tailoring of treatment. We evaluated the usefulness of (18)F-FDG PET for this purpose.
  
  
  METHODS
  A total of 70 consecutive patients with a high-grade osteosarcoma treated at our institute were prospectively enrolled. All patients underwent (18)F-FDG PET and MRI before and after neoadjuvant chemotherapy. We analyzed the predictive values of 5 parameters, namely, maximum standardized uptake values (SUVs), before and after (SUV2) chemotherapy, SUV change ratio, tumor volume change ratio, and metabolic volume change ratio (MVCR) in terms of their abilities to discriminate responders from nonresponders.
  
  
  RESULTS
  Patients with an SUV2 of less than or equal to 2 showed a good histologic response, and patients with an SUV2 of greater than 5 showed a poor histologic response. The histologic response of a patient with an intermediate SUV2 (2 < SUV2 </= 5) was found to be predictable using MVCR. A patient with an MVCR of less than 0.65 is likely to be a good responder, whereas a patient with an MVCR of greater than or equal to 0.65 is likely to be a poor responder. According to our model, the predictive values for good responders and poor responders were 97% (31/32) and 95% (36/38), respectively.
  
  
  CONCLUSIONS
  We found that combined information on (18)F-FDG PET and MRI scans, acquired before and after chemotherapy, could be used to predict histologic response to neoadjuvant chemotherapy in osteosarcoma.
authors.affiliation: Department of Nuclear Medicine, Korea Cancer Center Hospital, Seoul, Korea.
authors.forename: Gi Jeong
authors.initials: GJ
authors.lastname: Cheon
authors.forename: Min Suk
authors.initials: MS
authors.lastname: Kim
authors.forename: Jun Ah
authors.initials: JA
authors.lastname: Lee
authors.forename: Soo-Yong
authors.initials: SY
authors.lastname: Lee
authors.forename: Wan Hyeong
authors.initials: WH
authors.lastname: Cho
authors.forename: Won Seok
authors.initials: WS
authors.lastname: Song
authors.forename: Jae-Soo
authors.initials: JS
authors.lastname: Koh
authors.forename: Ji Young
authors.initials: JY
authors.lastname: Yoo
authors.forename: Dong Hyun
authors.initials: DH
authors.lastname: Oh
authors.forename: Duk Seop
authors.initials: DS
authors.lastname: Shin
authors.forename: Dae-Geun
authors.initials: DG
authors.lastname: Jeon
mesh_terms: D000971:Antineoplastic Combined Chemotherapy Protocols / Q000008:administration & dosage*; D001859:Bone Neoplasms / Q000175:diagnosis* / Q000188:drug therapy*; D017024:Chemotherapy, Adjuvant; D003198:Computer Simulation; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D012516:Osteosarcoma / Q000175:diagnosis* / Q000188:drug therapy*; D017063:Outcome Assessment, Health Care / Q000379:methods; D049268:Positron-Emission Tomography / Q000379:methods*; D011379:Prognosis; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D016896:Treatment Outcome
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18