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PO-0889: FLT PET kinetic analysis biomarkers of resistance to radiotherapy for nasal tumours in canines
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realistic VMs can help to optimize clinical imaging protocols and image analysis tools. PO-0888 Response monitoring by 18FDG-PET in locally advanced NSCLC treated with concurrent chemoradiotherapy J.N.A. Van Diessen1, M. La Fontaine2, M. Van den Heuvel3, W. Vogel4, J.S.A. Belderbos1, J.J. Sonke2 1 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Radiation Oncology, Amsterdam, The Netherlands 2 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Academic Physics, Amsterdam, The Netherlands 3 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Pulmonology, Amsterdam, The Netherlands 4 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Nuclear Medicine, Amsterdam, The Netherlands Purpose or Objective The randomized phase 2 Raditux-trial (NTR2230) in locally advanced non-small cell lung cancer (NSCLC), investigating the additional benefit of Cetuximab to concurrent chemoradiotherapy (CCRT) did not show improved survival but revealed a remarkable 5-year overall survival (OS) of 37.3% [1]. Patients were staged with 18FDG-PET-scans before and 4 weeks after CCRT. The purpose of this study was to investigate whether PET metrics have prognostic value in relation to local, regional, and distant failure. Material and Methods In the Raditux-trial, 102 stage IIIA-B NSCLC patients were included. CCRT consisted of 66 Gy in 24 fractions (using IMRT) combined with daily low dose Cisplatin. A subgroup of the patients had a repeat 18FDG-PET-scan for response evaluation of the primary tumor and lymph nodes after a median of 4.2 weeks (range, 1.6-10.1). Twenty patients underwent additional surgery and were excluded. Ten patients were excluded due to technical reasons. The preand post-treatment 18FDG-PET-scans from the remaining 42 patients were anatomically registered with the planning CT-scan. The following pre-and post-treatment PET metrics were calculated of the primary tumor (PT) as well as the combined lymph nodes (LNs): SUVmax, total lesion glycolysis (TLG) and metabolic tumor volume (MTV). The response ratio between the pre- and post-treatment values was also calculated. These parameters were tested as prognostic factors using the Kaplan-Meier method and Cox regression analysis for univariate and multivariate analyses. Results Forty-two patients were evaluated for the prognostic value of the PET metrics. The median follow-up and OS was 32 and 33 months, respectively. Median GTV of the PT and the LNs was 80 cc (range, 2-439) and 27 cc (range, 2195). The SUVmax of both PT and LNs decreased significantly as well as TLG of the PT and MTV of the LNs (p≤0.001). The post-treatment and the response ratio of the SUVmax of the LNs was correlated significantly with regional failure (p=0.009; p=0.009) (Table 1). The response ratio of the SUVmax of the LNs was also significantly correlated with OS (p=0.014). No parameters corresponded with local and distant failure. Table 1 The P-values and HR of the PET metrics of the primary tumor (PT) related to local failure and combined lymph nodes (LNs) related to regional failure of the pre- and post-treatment 18FDG-PET-scan as well as the response ratio.
Conclusion The post-treatment and response SUVmax of the LNs were found to be significant prognostic factors for regional failure and OS in patients with locally advanced NSCLC treated with hypofractionated CCRT. These parameters might be useful in the selection of patients for additional therapy. PO-0889 FLT PET kinetic analysis biomarkers of resistance to radiotherapy for nasal tumours in canines U. Simoncic1, T.J. Bradshaw2, L. Kubicek3, L.J. Forrest4, R. Jeraj5 1 Jozef Stefan Institute, F-8, Ljubljana, Slovenia 2 University of Wisconsin, Department of Radiology, Madison, USA 3 Angell Animal Medical Center, Angell Animal Medical Center, Boston, USA 4 University of Wisconsin, Department of Surgical Sciences- School of Veterinary Medicine, Madison, USA 5 University of Wisconsin, Department of Medical Physics, Madison, USA Purpose or Objective Imaging biomarkers of resistance to radiotherapy are prerequisite for precise treatment. Multiple imaging biomarkers are typically provided by a separate multitracer or multimodal imaging. This study assessed kinetic analysis as a means to create multiple imaging biomarkers of resistance to radiotherapy from a dynamic 3’(18F)fluoro-3’-deoxy-L-thymidine (FLT) positron emission tomography (PET) scan. Material and Methods Sixteen canine cancer patients with spontaneous nasal tumours were imaged dynamically with FLT PET before and during the radiotherapy. Images were analysed for kinetics on a voxel basis using a two tissue, four rateconstant compartmental model. Overall parameter values (mean and median over the region of intrests (ROI)) and heterogeneity measures (coefficient of variation (COV), ratio of interquartile range to median (IQR/median)) were evaluated over the tumour gross target volume for the transport (Ki=K1k3/(k2+k3)), perfusion/permeability (K1) and vascular fraction (Vb) parametric images. Response biomarkers were evaluated as a ratio of mid-therapy to pre-therapy regional values, (i.e. mean, median, COV, IQR/median). Alternative, spatial responses were evaluated as a mean, median, COV or IQR/median taken on a ratio of mid-therapy to pre-therapy prametric images. The time to progression after radiotherapy (TTP) was estimated by assessing the therapy response according to the RECIST. Kaplan-Meier analysis and univariate Cox proportional hazards (PH) regression were used to assess the impact of each imaging biomarker on the TTP. Results Pre- or mid-therapy overall Ki parameters were significant predictors of TTP after the radiotherapy. However, many imaging biomarkers based on K1 and Vb parameters had higher predictive power for the radiation therapy response. Table shows results of univariate Cox proportional hazard regression for imaging biomarkers derived from FLT PET parametric images. Hazard is significantly increased for higher pre- or mid-therapy overall Ki parameter values, higher or increasing pre- or mid-therapy overall K1 parameter value, lower or
S489 ESTRO 36 _______________________________________________________________________________________________
decreasing pre- or mid-therapy K1 spatial heterogeneity, higher but decreasing pre- or mid-therapy overall Vb parameter value, and lower pre-therapy Vb spatial heterogeneity.
Figure shows selected results of Kaplan-Meier analyses that illustrates prognostic power of some imaging biomarkers based on FLT PET parametric images.
Conclusion Worse outcome after radiotherapy was significantly associated with higher pre- or mid-therapy overall Ki. Additionally, we found that various imaging biomarkers derived from vascular parameters or their change through the therapy, contains even stronger prognostic information than the FLT transport parameter, which justify use of kinetic analysis. PO-0890 PET-based radiobiological modeling of changes in tumor hypoxia during chemoradiotherapy M. Crispin Ortuzar1, M. Grkovski1, B.J. Beattie1, N.Y. Lee2, N. Riaz2, J.L. Humm1, J. Jeong1, A. Fontanella1, J.O. Deasy1 1 Memorial Sloan Kettering Cancer Center, Medical Physics, New York, USA 2 Memorial Sloan Kettering Cancer Center, Radiation Oncology, New York, USA Purpose or Objective To develop a mechanistic radiobiological model of tumor control probability (TCP) for predicting changes in tumor hypoxia during chemoradiotherapy, based on pretreatment imaging of perfusion and hypoxia with 18FFluoromisonidazole (FMISO) dynamic PET and of glucose metabolism with 18F-Fluorodeoxyglucose (FDG) PET.
Material and Methods The mechanistic prediction is based on a radiobiological TCP model describing the interplay between tumor cell proliferation and hypoxia (Jeong et al., PMB 2013). The study presented here (see Sup. Figure 1) focuses on a cohort of 35 head and neck cancer patients treated with chemoradiotherapy which received baseline FDG PET and FMISO dynamic PET, and intra-treatment FMISO dynamic PET scans, and which excluded subjects having a significant increase in hypoxia during treatment. The model is used to predict the radiobiological evolution of each tumor voxel of the baseline image up until the intratreatment scan (9.2±3.4 days). The main inputs to the model are the initial fractions of proliferative and hypoxic tumor cells in each voxel, obtained from an approximate solution to a system of linear equations relating cell fractions to voxel-level FDG uptake, perfusion (FMISO K1) and hypoxia (FMISO k3). For each lesion, the predicted levels of intra-treatment hypoxia are compared to the measured k3 from the intra-treatment scan. A single global parameter (the average fraction of extremely hypoxic cells that take up FMISO) is determined from a training subset of 29 lesions by minimizing the average discrepancy between each lesion’s measured and predicted intratreatment k3 histograms (Cramér-von Mises criterion). A validation subset of 10 lesions is held out to test the resulting model.
Results The average fraction of extremely hypoxic cells that take up FMISO is 0.15 (95% CI 0.05 – 0.30 on bootstrap). In the training subset, the model predicts the mean, median and standard deviation of each lesion’s intra-treatment k3 histograms (Pearson’s linear correlation coefficients between predicted and measured values of ρ=0.62, 0.60 and 0.69 respectively, all with positive 95% CI on bootstrap – see Sup. Table 1). In the validation subset, only the predictions of the intra-treatment mean and median k3 of each lesion are significant (ρ=0.59 and 0.60 respectively).
realistic VMs can help to optimize clinical imaging protocols and image analysis tools. PO-0888 Response monitoring by 18FDG-PET in locally advanced NSCLC treated with concurrent chemoradiotherapy J.N.A. Van Diessen1, M. La Fontaine2, M. Van den Heuvel3, W. Vogel4, J.S.A. Belderbos1, J.J. Sonke2 1 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Radiation Oncology, Amsterdam, The Netherlands 2 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Academic Physics, Amsterdam, The Netherlands 3 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Pulmonology, Amsterdam, The Netherlands 4 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Nuclear Medicine, Amsterdam, The Netherlands Purpose or Objective The randomized phase 2 Raditux-trial (NTR2230) in locally advanced non-small cell lung cancer (NSCLC), investigating the additional benefit of Cetuximab to concurrent chemoradiotherapy (CCRT) did not show improved survival but revealed a remarkable 5-year overall survival (OS) of 37.3% [1]. Patients were staged with 18FDG-PET-scans before and 4 weeks after CCRT. The purpose of this study was to investigate whether PET metrics have prognostic value in relation to local, regional, and distant failure. Material and Methods In the Raditux-trial, 102 stage IIIA-B NSCLC patients were included. CCRT consisted of 66 Gy in 24 fractions (using IMRT) combined with daily low dose Cisplatin. A subgroup of the patients had a repeat 18FDG-PET-scan for response evaluation of the primary tumor and lymph nodes after a median of 4.2 weeks (range, 1.6-10.1). Twenty patients underwent additional surgery and were excluded. Ten patients were excluded due to technical reasons. The preand post-treatment 18FDG-PET-scans from the remaining 42 patients were anatomically registered with the planning CT-scan. The following pre-and post-treatment PET metrics were calculated of the primary tumor (PT) as well as the combined lymph nodes (LNs): SUVmax, total lesion glycolysis (TLG) and metabolic tumor volume (MTV). The response ratio between the pre- and post-treatment values was also calculated. These parameters were tested as prognostic factors using the Kaplan-Meier method and Cox regression analysis for univariate and multivariate analyses. Results Forty-two patients were evaluated for the prognostic value of the PET metrics. The median follow-up and OS was 32 and 33 months, respectively. Median GTV of the PT and the LNs was 80 cc (range, 2-439) and 27 cc (range, 2195). The SUVmax of both PT and LNs decreased significantly as well as TLG of the PT and MTV of the LNs (p≤0.001). The post-treatment and the response ratio of the SUVmax of the LNs was correlated significantly with regional failure (p=0.009; p=0.009) (Table 1). The response ratio of the SUVmax of the LNs was also significantly correlated with OS (p=0.014). No parameters corresponded with local and distant failure. Table 1 The P-values and HR of the PET metrics of the primary tumor (PT) related to local failure and combined lymph nodes (LNs) related to regional failure of the pre- and post-treatment 18FDG-PET-scan as well as the response ratio.
Conclusion The post-treatment and response SUVmax of the LNs were found to be significant prognostic factors for regional failure and OS in patients with locally advanced NSCLC treated with hypofractionated CCRT. These parameters might be useful in the selection of patients for additional therapy. PO-0889 FLT PET kinetic analysis biomarkers of resistance to radiotherapy for nasal tumours in canines U. Simoncic1, T.J. Bradshaw2, L. Kubicek3, L.J. Forrest4, R. Jeraj5 1 Jozef Stefan Institute, F-8, Ljubljana, Slovenia 2 University of Wisconsin, Department of Radiology, Madison, USA 3 Angell Animal Medical Center, Angell Animal Medical Center, Boston, USA 4 University of Wisconsin, Department of Surgical Sciences- School of Veterinary Medicine, Madison, USA 5 University of Wisconsin, Department of Medical Physics, Madison, USA Purpose or Objective Imaging biomarkers of resistance to radiotherapy are prerequisite for precise treatment. Multiple imaging biomarkers are typically provided by a separate multitracer or multimodal imaging. This study assessed kinetic analysis as a means to create multiple imaging biomarkers of resistance to radiotherapy from a dynamic 3’(18F)fluoro-3’-deoxy-L-thymidine (FLT) positron emission tomography (PET) scan. Material and Methods Sixteen canine cancer patients with spontaneous nasal tumours were imaged dynamically with FLT PET before and during the radiotherapy. Images were analysed for kinetics on a voxel basis using a two tissue, four rateconstant compartmental model. Overall parameter values (mean and median over the region of intrests (ROI)) and heterogeneity measures (coefficient of variation (COV), ratio of interquartile range to median (IQR/median)) were evaluated over the tumour gross target volume for the transport (Ki=K1k3/(k2+k3)), perfusion/permeability (K1) and vascular fraction (Vb) parametric images. Response biomarkers were evaluated as a ratio of mid-therapy to pre-therapy regional values, (i.e. mean, median, COV, IQR/median). Alternative, spatial responses were evaluated as a mean, median, COV or IQR/median taken on a ratio of mid-therapy to pre-therapy prametric images. The time to progression after radiotherapy (TTP) was estimated by assessing the therapy response according to the RECIST. Kaplan-Meier analysis and univariate Cox proportional hazards (PH) regression were used to assess the impact of each imaging biomarker on the TTP. Results Pre- or mid-therapy overall Ki parameters were significant predictors of TTP after the radiotherapy. However, many imaging biomarkers based on K1 and Vb parameters had higher predictive power for the radiation therapy response. Table shows results of univariate Cox proportional hazard regression for imaging biomarkers derived from FLT PET parametric images. Hazard is significantly increased for higher pre- or mid-therapy overall Ki parameter values, higher or increasing pre- or mid-therapy overall K1 parameter value, lower or
S489 ESTRO 36 _______________________________________________________________________________________________
decreasing pre- or mid-therapy K1 spatial heterogeneity, higher but decreasing pre- or mid-therapy overall Vb parameter value, and lower pre-therapy Vb spatial heterogeneity.
Figure shows selected results of Kaplan-Meier analyses that illustrates prognostic power of some imaging biomarkers based on FLT PET parametric images.
Conclusion Worse outcome after radiotherapy was significantly associated with higher pre- or mid-therapy overall Ki. Additionally, we found that various imaging biomarkers derived from vascular parameters or their change through the therapy, contains even stronger prognostic information than the FLT transport parameter, which justify use of kinetic analysis. PO-0890 PET-based radiobiological modeling of changes in tumor hypoxia during chemoradiotherapy M. Crispin Ortuzar1, M. Grkovski1, B.J. Beattie1, N.Y. Lee2, N. Riaz2, J.L. Humm1, J. Jeong1, A. Fontanella1, J.O. Deasy1 1 Memorial Sloan Kettering Cancer Center, Medical Physics, New York, USA 2 Memorial Sloan Kettering Cancer Center, Radiation Oncology, New York, USA Purpose or Objective To develop a mechanistic radiobiological model of tumor control probability (TCP) for predicting changes in tumor hypoxia during chemoradiotherapy, based on pretreatment imaging of perfusion and hypoxia with 18FFluoromisonidazole (FMISO) dynamic PET and of glucose metabolism with 18F-Fluorodeoxyglucose (FDG) PET.
Material and Methods The mechanistic prediction is based on a radiobiological TCP model describing the interplay between tumor cell proliferation and hypoxia (Jeong et al., PMB 2013). The study presented here (see Sup. Figure 1) focuses on a cohort of 35 head and neck cancer patients treated with chemoradiotherapy which received baseline FDG PET and FMISO dynamic PET, and intra-treatment FMISO dynamic PET scans, and which excluded subjects having a significant increase in hypoxia during treatment. The model is used to predict the radiobiological evolution of each tumor voxel of the baseline image up until the intratreatment scan (9.2±3.4 days). The main inputs to the model are the initial fractions of proliferative and hypoxic tumor cells in each voxel, obtained from an approximate solution to a system of linear equations relating cell fractions to voxel-level FDG uptake, perfusion (FMISO K1) and hypoxia (FMISO k3). For each lesion, the predicted levels of intra-treatment hypoxia are compared to the measured k3 from the intra-treatment scan. A single global parameter (the average fraction of extremely hypoxic cells that take up FMISO) is determined from a training subset of 29 lesions by minimizing the average discrepancy between each lesion’s measured and predicted intratreatment k3 histograms (Cramér-von Mises criterion). A validation subset of 10 lesions is held out to test the resulting model.
Results The average fraction of extremely hypoxic cells that take up FMISO is 0.15 (95% CI 0.05 – 0.30 on bootstrap). In the training subset, the model predicts the mean, median and standard deviation of each lesion’s intra-treatment k3 histograms (Pearson’s linear correlation coefficients between predicted and measured values of ρ=0.62, 0.60 and 0.69 respectively, all with positive 95% CI on bootstrap – see Sup. Table 1). In the validation subset, only the predictions of the intra-treatment mean and median k3 of each lesion are significant (ρ=0.59 and 0.60 respectively).