Lin Cheng1, Jianping Zhang2,3,4, Yujie Wang5,6, Xiaoli Xu7, Yongping Zhang2,3,4, Yingjian Zhang8,3,4, Guangyu Liu5,6, Jingyi Cheng9,10,11. 1. Department of Nuclear Medicine, Shanghai Proton and Heavy Ion Center, Shanghai, 201321, China. lin.cheng@sphic.org.cn. 2. Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai, 200032, China. 3. Center for Biomedical Imaging, Fudan University, Shanghai, 200032, China. 4. Shanghai Engineering Research Center for Molecular Imaging Probes, Shanghai, 200032, China. 5. Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, 200032, China. 6. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China. 7. Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China. 8. Department of Nuclear Medicine, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, 4365 Kangxin Road, Shanghai, 201321, China. 9. Department of Nuclear Medicine, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, 4365 Kangxin Road, Shanghai, 201321, China. jingyi.cheng@sphic.org.cn. 10. Center for Biomedical Imaging, Fudan University, Shanghai, 200032, China. jingyi.cheng@sphic.org.cn. 11. Shanghai Engineering Research Center for Molecular Imaging Probes, Shanghai, 200032, China. jingyi.cheng@sphic.org.cn.
Abstract
OBJECTIVE: This study was designed to evaluate the utility of textural features for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). METHODS: Sixty-one consecutive patients with locally advanced breast cancer underwent 18F-FDG PET/CT scanning at baseline and after the second course of NAC. Changes to imaging parameters [maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG)] and textural features (entropy, coarseness, skewness) between the 2 scans were measured by two independent radiologists. Pathological responses were reviewed by one pathologist, and the significance of the predictive value of each parameter was analyzed using a Chi-squared test. Receiver operating characteristic curve analysis was used to compare the area under the curve (AUC) for each parameter. RESULTS: pCR was observed more often in patients with HER2-positive tumors (22 patients) than in patients with HER2-negative tumors (5 patients) (71.0 vs. 16.7%, p < 0.001). ∆ %SUVmax, ∆ %entropy and ∆ %coarseness were significantly useful for differentiating pCR from non-pCR in the HER2-negative group, and the AUCs for these parameters were 0.928, 0.808 and 0.800, respectively (p = 0.003, 0.032 and 0.037). In the HER2-positive group, ∆ %SUVmax and ∆ %skewness were moderately useful for predicting pCR, and the respective AUCs were 0.747 and 0.758 (p = 0.033 and 0.026). Although there was no significant difference in the AUCs between groups for these parameters, an additional 3/22 patients in the HER2-positive group with pCR were identified when ∆ %skewness and ∆ %SUVmax were considered together (p = 0.031). The absolute values for each parameter before NAC and after 2 cycles cannot predict pCR in our patients. Neither ∆ %MTV nor ∆ %TLG was efficiently predictive of pCR in any group. CONCLUSIONS: The early changes in the textural features of 18F-FDG PET images after two cycles of NAC are predictive of pCR in both HER2-negative and HER2-positive patients; this evidence warrants confirmation by further research.
OBJECTIVE: This study was designed to evaluate the utility of textural features for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). METHODS: Sixty-one consecutive patients with locally advanced breast cancer underwent 18F-FDG PET/CT scanning at baseline and after the second course of NAC. Changes to imaging parameters [maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG)] and textural features (entropy, coarseness, skewness) between the 2 scans were measured by two independent radiologists. Pathological responses were reviewed by one pathologist, and the significance of the predictive value of each parameter was analyzed using a Chi-squared test. Receiver operating characteristic curve analysis was used to compare the area under the curve (AUC) for each parameter. RESULTS: pCR was observed more often in patients with HER2-positive tumors (22 patients) than in patients with HER2-negative tumors (5 patients) (71.0 vs. 16.7%, p < 0.001). ∆ %SUVmax, ∆ %entropy and ∆ %coarseness were significantly useful for differentiating pCR from non-pCR in the HER2-negative group, and the AUCs for these parameters were 0.928, 0.808 and 0.800, respectively (p = 0.003, 0.032 and 0.037). In the HER2-positive group, ∆ %SUVmax and ∆ %skewness were moderately useful for predicting pCR, and the respective AUCs were 0.747 and 0.758 (p = 0.033 and 0.026). Although there was no significant difference in the AUCs between groups for these parameters, an additional 3/22 patients in the HER2-positive group with pCR were identified when ∆ %skewness and ∆ %SUVmax were considered together (p = 0.031). The absolute values for each parameter before NAC and after 2 cycles cannot predict pCR in our patients. Neither ∆ %MTV nor ∆ %TLG was efficiently predictive of pCR in any group. CONCLUSIONS: The early changes in the textural features of 18F-FDG PET images after two cycles of NAC are predictive of pCR in both HER2-negative and HER2-positive patients; this evidence warrants confirmation by further research.
Entities:
Keywords:
18F-FDG PET; Breast cancer; Neoadjuvant chemotherapy; Textural feature
Authors: E J van Helden; Y J L Vacher; W N van Wieringen; F H P van Velden; H M W Verheul; O S Hoekstra; R Boellaard; C W Menke-van der Houven van Oordt Journal: Eur J Nucl Med Mol Imaging Date: 2018-08-09 Impact factor: 9.236
Authors: Lale Umutlu; Julian Kirchner; Nils-Martin Bruckmann; Janna Morawitz; Gerald Antoch; Saskia Ting; Ann-Kathrin Bittner; Oliver Hoffmann; Lena Häberle; Eugen Ruckhäberle; Onofrio Antonio Catalano; Michal Chodyla; Johannes Grueneisen; Harald H Quick; Wolfgang P Fendler; Christoph Rischpler; Ken Herrmann; Peter Gibbs; Katja Pinker Journal: Cancers (Basel) Date: 2022-03-29 Impact factor: 6.575