Development and Validation of a Model for Temporal Lobe Necrosis Based on 749 Nasopharyngeal Carcinoma Patients Following IMRT

Volume 99  Number 2S  Supplement 2017

Oral Scientific Sessions S165

Abstract 353; Table 1 value j P-value j Hazard Ratio Outcome

Binomial/continuous

SUVmax-T (g/mL)

TLG-T (g)

OS

III quartile continuous value

18.80j0.04j7.26 j0.01j1.07

203.1j0.03j8.19 j0.01j1.003

SUVmean-N (g/mL)

Stage

13.30j0.05j3.53 j0.07j1.07

IVBj0.04j4.11 j0.04j2.50

DFS

III quartile continuous value



Age (5years) 11.40j0.03j8.44 j0.01j1.88 Age (5years)

EBV-DNA*(copies/mL)

P<0.05 j0.07j1.32

3500j0.05j3.71

 I-IVA vs IVB was the subdivision closest to III quartile. * cut-off derived from a previous publication.

and chemotherapy. Pts that underwent whole body 18F-FDG PET/CT for disease staging at our Institution and with a minimum follow-up of 12 months (mos) were included in this study. The following parameters were considered: maximum and mean standardized uptake value (SUVmax and SUVmean, respectively), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of primary tumor (T) and cervical nodes (N), age, disease stage and EBV-DNA load (copies/ml). The prognostic value of these parameters on overall survival (OS) and disease-free survival (DFS) was assessed using Kaplan-Meier actuarial curves and log-rank test. Continuous features were dichotomized according to the third quartile of their distribution. Finally, uni- and multivariable Cox regression analysis were performed to estimate the hazard ratio (HR) associated to dichotomized and continuous variables. Results: A total of 49 pts were available for evaluation. Median follow-up was 47 mos (14-110). OS (4 events) rate at 24 and 60 mos was 95.8% and 90.5%, respectively, while DFS (8 events, 7 with regional and/or distant site) was 83.4% at both time points. Table 1 shows HR for independent prognostic factors (binary and continuous), which resulted in significant separation (P < 0.05) for OS and DFS KM curves. A Cox bivariate model for DFS was established including SUVmean-N (HR Z 1.19) and age (HR Z 2.01), i.e. the only variables pair with P < 0.05. Being all relapse times <24 mos, a crude approach analysis (logistic regression) on pts with minimum follow-up of 24 mos was also performed. Odds ratios were 1.11 for SUVmean-N and 1.43 for age (P < 0.05 in both cases). Calibration was good: slope Z 0.95 (R2 Z 0.98), AUC Z 0.79. Conclusion: Even in a limited series, our data confirm that SUV and TLG can predict a higher risk of adverse events or death in NPC pts also in a nonendemic area. In particular, TLG-T, SUVmax-T and age predicted OS, while SUVmean-N, stage, age and EBV-DNA load were prognostic factors for DFS. Author Disclosure: A. Cavallo: None. A. Cicchetti: None. N. Iacovelli: None. A. Alessi: None. B. Padovano: None. C. Colombo: None. N. Facchinetti: None. S. Alfieri: None. P. Bossi: None. C. Resteghini: None. L. Licitra: None. C. Fallai: None. F. Crippa: None. T. Rancati: None. E. Pignoli: None. E. Orlandi: None.

354 Image-Based Data Mining for Identifying Regions Exhibiting a Dose-Response Relationship with Radiation-Induced Trismus W. Beasley,1,2 M. Thor,3 A. McWilliam,4 A. Green,1 R. Mackay,2 N. Slevin,5 C. Olsson,6 N. Pettersson,7 C. Finizia,8 J.O. Deasy,3 and M. van Herk4; 1Division of Molecular and Clinical Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom, 2Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom, 3Memorial Sloan Kettering Cancer Center, New York, NY, 4Division of Cancer Sciences, University of Manchester, Manchester, United Kingdom, 5Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, United Kingdom, 6Department of Radiation Physics, Institute of Clinical Sciences, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden, 7Department of Radiation Oncology, University of California San Diego, La Jolla, CA, 8Department of Otorhinolaryngology, Institute of Clinical Sciences, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden

Purpose/Objective(s): Image-based data mining is a powerful technique that enables identification of local dose-response relationships from dose distributions of previously treated patients. No prior information about which regions are related with the clinical endpoint is required, offering advantages over conventional structure-based analyses. Image-based data mining in radiotherapy (RT) has previously been applied in the setting of dichotomized clinical endpoints, but many endpoints are best described by continuous variables, with an advantage that the amount of information per treated patient is increased. A novel image-based data mining methodology for continuously variable clinical endpoints has been developed and applied to a cohort of head and neck cancer (HNC) patients. The studied endpoint is radiation-induced trismus, characterized by impaired mouth opening ability, a common adverse effect after RT. The aim of the study was to identify anatomic regions exhibiting a dose-response relationship with trismus. Materials/Methods: We analyzed a cohort of 90 HNC patients treated between 2007 and 2012 to 64.6 Gy e 68.0 Gy in 38/34 fractions. Trismus was described by the maximal incisor-to-incisor distance (MID) in mm at 6 months post-RT. Patient anatomies were spatially normalized using deformable image registration, transforming dose distributions to a common frame of reference. A correlation map showing the Spearman’s rank correlation coefficient (Rs) of the dose at each voxel with the MID was created. Voxels with a statistically significant dose-response relationship (a Z 0.05) were identified, after correction for multiple comparisons by permutation testing. Results: The image-based data mining revealed a single region with a statistically significant dose-response relationship with MID (P Z 0.003), containing voxels with a correlation coefficient of up to Rs Z -0.41. This region was overlapping with the anterior and superior portion of the ipsilateral masseter, suggesting that this is an important structure for radiation-induced trismus. Conclusion: Image-based data mining is a powerful technique for identifying dose-response relationships, and this study is the first to extend it to continuous clinical outcome data. Upon application to radiation-induced trismus, we have identified a region overlapping with the anterior and superior portion of the ipsilateral masseter that exhibits a strong dose-response relationship with trismus. This suggests that sparing the ipsilateral masseter may reduce radiation-induced trismus. Previous studies have highlighted the role of other mastication structures, and further work will explore the interaction of the different mastication structures and extend the patient cohort. Author Disclosure: W. Beasley: None. M. Thor: None. A. McWilliam: None. A. Green: None. R. Mackay: None. N. Slevin: None. C. Olsson: None. N. Pettersson: None. C. Finizia: None. J.O. Deasy: AAPM. M. van Herk: None.

355 Development and Validation of a Model for Temporal Lobe Necrosis Based on 749 Nasopharyngeal Carcinoma Patients Following IMRT Y. Miao,1,2 X. Ou,1,2 J. Wang,2,3 X. Wang,1,2 X. He,1,2 C. Shen,1,2 H. Ying,1,2 W. Hu,1,2 and C. Hu1,2; 1Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China, 2Department of Oncology, Fudan University Shanghai Medical College, Shanghai, China, 3Fudan University Shanghai Cancer Center, Shanghai, China Purpose/Objective(s): To minimize the probability of temporal lobe necrosis (TLN) after radiotherapy in patients with nasopharyngeal carcinoma

S166

International Journal of Radiation Oncology  Biology  Physics

(NPC) while minimizing the impact on the planning target volume (PTV) dose, a quantitative complication model of TLN covering both dosimetric and clinical factors was generated to help physicists and physicians predict the personalized risk level of the patients. Materials/Methods: A cohort of 749 NPC patients from January 2009 to December 2010 was used in this study. With a median follow-up of 48.8 months, 38 (5.07%) of the patients showed symptoms of TLN. The dose volume histogram (DVH) parameters were preprocessed using principal component analysis (PCA). Derived PC variables combined with clinical factors were analyzed relative to TLN outcome using logistic regression. A 10-fold cross-validation technique was used to train the model. Model validation was performed on test data to prove the stability. Results: The model enrolled only dosimetric principal components (PCs). Tstage is positively correlated with TLN (OR Z 1.470, P < 0.05). However, when this parameter was combined with other factors, it was not selected during variable selection. Its effect is considered originated from a prescription dose difference. Most correlated DVH variable with first dimension of principal component PC1 was D9cc whose area under the curve (AUC) is 0.668. Further analysis conducted between DVH variables found out that the focal dose D0.5cc is the optimal univariate predictor in prediction of TLN (AUC Z 0.684). In addition, odds ratio of D0.5cc is 1.147 (95% CI: 1.102 1.193, P < 0.05). Compared to QUANTEC data (suggested 70 Gy, 5% incidence, 3DCRT), higher dose limitation in IMRT era is more acceptable. Conclusion: The generated logistic regression model of dose parameters can effectively predict the risk of TLN occurrence. IMRT technique provides a chance to avoid necrosis even with high dose radiation. Constrains on both the focal dose (D0.5cc, TD5 Z 73.66 Gy) and relatively large volume dose (D9cc, TD5 Z 58.00 Gy) are helpful to control the incidence of TLN. Author Disclosure: Y. Miao: None. X. Ou: None. J. Wang: None. X. WANG: None. X. He: None. C. Shen: None. H. Ying: None. W. Hu: None. C. Hu: None.

for executive function decline. In most cases, both Fisher’s exact test and fitting to the logistic function showed mild or no correlation between the incidence of complications and considered dose-volume parameters. The normalized slope of the logistic function ranged between 0.10 and 0.25, indicative of weak dependence. A strong dependence was observed for specific endpoints and dose-volume parameters. Specifically, DKEFS letter fluency decline (a measure of executive function) showed strong correlation with maximum dose to right hippocampus (D50 Z 35.7 Gy, normalized slope Z 0.97, P<0.001), but not with median or mean dose. There were no significant correlations between dose and scores on the HVLT verbal memory tests. Conclusion: In this prospective cohort of brain tumor patients who received RT, maximum dose to the right hippocampus predicted for decrease in executive functioning at 6-months post-RT. Further NTCP analyses are warranted with evaluation of other normal brain ROIs, along with longer neurocognitive follow-up of this cohort. Author Disclosure: M. Huynh-Le: None. K.R. Tringale: None. R. Karunamuni: None. T.M. Seibert: Research Grant; Varian Medical Systems. Honoraria; WebMD, Inc. T. Nguyen: None. C. McDonald: None. V. Moiseenko: Honoraria; Varian Medical Systems. Travel Expenses; Varian Medical Systems. J.A. Hattangadi-Gluth: Research Grant; Varian Medical Systems.

356 Radiation Dose to Temporal Lobes and Hippocampi as Predictors of Neurocognitive Decline: Normal Tissue Complication Probability (NTCP) Analysis of a Prospective Cohort Study M.P. Huynh-Le, K.R. Tringale, R. Karunamuni, T.M. Seibert, T. Nguyen, C. McDonald, V. Moiseenko, and J.A. Hattangadi-Gluth; University of California, San Diego, La Jolla, CA Purpose/Objective(s): Brain radiotherapy (RT) can lead to neurocognitive decline in memory and executive functioning. However, it is unclear which dose-volume histogram (DVH) parameters to the hippocampus and temporal lobes are predictive of cognitive deterioration. We sought to determine the dosimetric predictors of cognitive decline in a prospective cohort of brain tumor patients treated with RT. Materials/Methods: Twenty-five patients with primary brain tumors who received brain RT were enrolled on a prospective cohort study where neurocognitive assessments (NCA) were performed prior to the initiation of RT and 6 months after completion of RT. NCA measured performance on verbal learning and memory tests (Hopkins Verbal Learning Test [HVLT] total and delayed recall) and executive functioning (Delis-Kaplan Executive Function System [DKEFS] letter fluency and category switching total). Reliable change indices and Z scores were calculated as a normalized measure of change in cognition from pre- to post-RT. Decline was a binary variable based on these change scores. Regions of interest (bilateral temporal lobes, bilateral hippocampi) were delineated and verified by two radiation oncologists based on high-resolution brain MRI and neuroanatomy atlases. Tumor was censored from ROIs for analyses. DVHs were exported from the treatment planning system and maximum, median, and mean doses were extracted. Fisher’s exact test on median splits and logistic function were used to search for dosimetric predictors of cognitive decline. Bonferroni correction was applied to account for multiple independent tests. Results: Most patients (n Z 15, 60%) had benign or low grade tumors. Median prescription dose was 54 Gy (range 50.4-60 Gy). Incidence of cognitive decline ranged from 48 to 81%, with a particularly high incidence

357 An Analysis on Local Control of Chemoradiation Therapy for Locally Advanced Pancreatic Cancer Using a Biophysical Model X. Chen,1 A. Tai,1 P.W. Prior Jr,1 W.A. Hall,2 B.A. Erickson,2 J. Herman,3 and A. Li1; 1Medical College of Wisconsin, Milwaukee, WI, 2Medical College of Wisconsin Department of Radiation Oncology and Clement J Zablocki VA Medical Center, Milwaukee, WI, 3The University of Texas MD Anderson Cancer Center, Houston, TX Purpose/Objective(s): Chemoradiotherapy (CRT) has played a key role in the treatment of unresectable locally advanced pancreatic cancer (LAPC). This work aims to analyze published clinical data on CRT for LAPC and to estimate a set of plausible radiosensitivity parameters that may be used to help design new radiation treatment schemes. Materials/Methods: A thorough literature search from 1996 to 2016 yielded a total of 51 clinical studies on CRT for LAPC using different radiation fractionation regimens ranging from conventional fractionation to stereotactic body radiotherapy (SBRT). Among these studies, 38 (total # of patients: 1270) reported tumor control data. These 38 studies were categorized into 5 groups in this analysis: (1) 12 SBRT studies (RT fraction dose d  3 Gy) with gemcitabine (GEM) based chemotherapy ; (2) 9 conventional RT fractionation (1.8 Gy  d < 3 Gy) studies with GEM; (3) 11 conventional RT fractionation (1.8 Gy  d < 3 Gy) studies with 5-FU or other agents based chemotherapy; (4) 3 RT alone studies; and (5) 3 Carbon-ion RT studies. A modified linear-quadratic tumor control probability model (mLQTCP) that considers Poisson TCP model, RT fractionation dependent biologically effective dose (BED), and tumor repopulation, was used to fit the TCP data reported in the selected studies. The mLQ-TCP model includes 4 radiobiologic parameters: a, a/b, the tumor doubling time Td, the initial tumor clonogenic cell number N0. A chemotherapy factor (fc) is used to account for the combined effect of chemotherapy on BED. In addition, radiosensitivity parameter a is assumed to have a Gaussian distribution (sa) to account for the inhomogeneity of tumor radiosensitivity that may be correlated with the tumor histopathological grades. Results: A large spread of TCP as a function of BED was observed. For the SBRT group, there is clear correlation between TCP and BED, which can be fitted by the mLQ-TCP model with the fitting parameters as: a Z 0.29 Gy-1, sa Z 0.12, Td Z 42 days, N0 Z 1.44 x 107, fc Z 1.40 with fixed parameters of a/b Z 10 Gy. The goodness of this fit was c2/dof Z 2.3. By varying a and sa and keeping the other parameters fixed, we obtained the upper and lower TCP-BED limit curves, with a Z 0.24 Gy-1, sa Z 0.12 for lower limit and a Z 0.32 Gy-1, sa Z 0.04 for the upper limit. These ranges of a and sa parameters are consistent with those reported for different tumor grades. According to the model calculation, 14.9 Gy and 10.9 Gy per fraction are needed to achieve 95% LC for a 3-fraction and 5-fraction SBRT, respectively.