@article {KAIRA6481, author = {KYOICHI KAIRA and TETSUYA HIGUCHI and NORIAKI SUNAGA and YUKIKO ARISAKA and TAKESHI HISADA and HIDEYUKI TOMINAGA and NOBORU ORIUCHI and TAKAYUKI ASAO and YOSHIHITO TSUSHIMA and MASANOBU YAMADA}, title = {Usefulness of 18F-α-Methyltyrosine PET for Therapeutic Monitoring of Patients with Advanced Lung Cancer}, volume = {36}, number = {12}, pages = {6481--6490}, year = {2016}, publisher = {International Institute of Anticancer Research}, abstract = {Background/Aim: L-[3-18F]-α-methyl tyrosine (18F-FAMT) positron emission tomography (PET) has a high specificity for detecting malignant lesions. However, the usefulness of therapeutic monitoring of 18F-FAMT PET against advanced human neoplasms remains unclear. Here, we evaluated 18F-FAMT PET clinical significance regarding therapy response and outcome after systemic chemotherapy in patients with advanced lung cancer, compared to 18F-FDG PET. Patients and Methods: All patients with untreated advanced lung cancer received 18F-FAMT PET and 18F-FDG PET before and 4 weeks after one cycle of chemotherapy. Metabolic response (MR) was defined according to the PERCIST guideline. Results: Ninety-five patients were eligible for analysis on both PET scans. The histological type included 87 non-small cell lung cancers and 8 small-cell lung cancers. Post-treatment maximal standardized uptake values (SUVmax) and MR on 18F-FAMT PET were correlated with tumor response. In all patients, post-treatment SUVmax of 18F-FDG and 18F-FAMT PET and MR of 18F-FAMT PET were statistically significant prognostic markers for predicting poor outcome by univariate analysis. Multivariate analysis confirmed that MR on 18F-FAMT PET was a significant independent prognostic factor. Conclusion: MR on 18F-FAMT PET may be a potential parameter to predict the prognosis after first-line chemotherapy in patients with advanced lung cancer.}, issn = {0250-7005}, URL = {https://ar.iiarjournals.org/content/36/12/6481}, eprint = {https://ar.iiarjournals.org/content/36/12/6481.full.pdf}, journal = {Anticancer Research} }