Ovarian Transposition Before Pelvic Radiation Therapy: Spatial Distribution and Dose Volume Analysis

Purpose

Methods and Materials

Results

Conclusions

18F-FDG PET-defined therapy response to predict acute hematologic toxicity for anal cancer patients treated with chemoradiation

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Background: Hematologic toxicities (HT) induced during chemoradiotherapy (CRT) for anal cancer can lead to increased infection rates, bleeding, asthenia, and unplanned breaks compromising treatment efficacy. We hypothesize that HT in anal cancer patients treated with CRT correlate with change in active bone marrow (ABM) characterized by pre- and post-CRT 18F-FDG PET/CT (PET). Methods: Twenty-eight locally advanced anal cancer patients treated with definitive CRT from 2011-2016 were identified. PET scans were obtained 0-2 weeks pre- and 6-8 weeks post-CRT. HT was evaluated by weekly white blood cell count, absolute neutrophil count (ANC), hemoglobin (Hg) and platelet nadirs. Total bone marrow (TBM) was defined on CT images, and segmented into three subregions: lumbosacral (LS), left and right iliac pelvis. PET images were normalized to bone outside of the TBM uptakes. ABM was characterized in all PET images as the volume having standard uptake value SUV > 40% of SUVmax in the TBM. Image variables (global, subregional SUVmean, SUVmax, ABMs) of pre- and post-CRT and their differential changes were evaluated as predictors of HT. Locoregional radiomics features were calculated using a 3D kernel-based approach. HT prediction was modeled by logistic regression with the Lasso algorithm with 10-fold cross-validation. HT endpoints were defined as change between baseline blood nadir and the lowest nadir values during and up to 2 weeks after CRT. Results: The lasso regression identified 5 predictors of HT (pre-SUVmax, post-LS-ABM, LS-ABM change, homogeneity texture change, and variance). Ratios of LS-ABMs to TBM were reduced from 18.9% (pre-CRT) to 16.3% (post-CRT). This reduction of LS-ABM significantly correlated with acute HT measured by ANC (p < 0.001) and Hg (p < 0.001) nadirs. Conclusions: PET-derived active BM changes between pre- and post-CRT significantly associated with HT in anal cancer patients undergoing definitive CRT. LS-ABM is a robust surrogate for evaluation of HT and can be used to develop BM-sparing radiotherapy for reduction of potential HT.

Identifying prognostic intratumor heterogeneity using pre- and post-radiotherapy 18F-FDG PET images for pancreatic cancer patients

BACKGROUND

To stratify risks of pancreatic adenocarcinoma (PA) patients using pre- and post-radiotherapy (RT) PET/CT images, and to assess the prognostic value of texture variations in predicting therapy response of patients.

METHODS

Twenty-six PA patients treated with RT from 2011-2013 with pre- and post-treatment 18F-FDG-PET/CT scans were identified. Tumor locoregional texture was calculated using 3D kernel-based approach, and texture variations were identified by fitting discrepancies of texture maps of pre- and post-treatment images. A total of 48 texture and clinical variables were identified and evaluated for association with overall survival (OS). The prognostic heterogeneity features were selected using lasso/elastic net regression, and further were evaluated by multivariate Cox analysis.

RESULTS

Median age was 69 y (range, 46-86 y). The texture map and temporal variations between pre- and post-treatment were well characterized by histograms and statistical fitting. The lasso analysis identified seven predictors (age, node stage, post-RT SUVmax, variations of homogeneity, variance, sum mean, and cluster tendency). The multivariate Cox analysis identified five significant variables: age, node stage, variations of homogeneity, variance, and cluster tendency (with P=0.020, 0.040, 0.065, 0.078, and 0.081, respectively). The patients were stratified into two groups based on the risk score of multivariate analysis with log-rank P=0.001: a low risk group (n=11) with a longer mean OS (29.3 months) and higher texture variation (>30%), and a high risk group (n=15) with a shorter mean OS (17.7 months) and lower texture variation (<15%).

CONCLUSIONS

Locoregional metabolic texture response provides a feasible approach for evaluating and predicting clinical outcomes following treatment of PA with RT. The proposed method can be used to stratify patient risk and help select appropriate treatment strategies for individual patients toward implementing response-driven adaptive RT.

Geometric validation of self-gating k-space-sorted 4D-MRI vs 4D-CT using a respiratory motion phantom

PURPOSE

MRI is increasingly being used for radiotherapy planning, simulation, and in-treatment-room motion monitoring. To provide more detailed temporal and spatial MR data for these tasks, we have recently developed a novel self-gated (SG) MRI technique with advantage of k-space phase sorting, high isotropic spatial resolution, and high temporal resolution. The current work describes the validation of this 4D-MRI technique using a MRI- and CT-compatible respiratory motion phantom and comparison to 4D-CT.

METHODS

The 4D-MRI sequence is based on a spoiled gradient echo-based 3D projection reconstruction sequence with self-gating for 4D-MRI at 3 T. Respiratory phase is resolved by using SG k-space lines as the motion surrogate. 4D-MRI images are reconstructed into ten temporal bins with spatial resolution 1.56 × 1.56 × 1.56 mm(3). A MRI-CT compatible phantom was designed to validate the performance of the 4D-MRI sequence and 4D-CT imaging. A spherical target (diameter 23 mm, volume 6.37 ml) filled with high-concentration gadolinium (Gd) gel is embedded into a plastic box (35 × 40 × 63 mm(3)) and stabilized with low-concentration Gd gel. The phantom, driven by an air pump, is able to produce human-type breathing patterns between 4 and 30 respiratory cycles/min. 4D-CT of the phantom has been acquired in cine mode, and reconstructed into ten phases with slice thickness 1.25 mm. The 4D images sets were imported into a treatment planning software for target contouring. The geometrical accuracy of the 4D MRI and CT images has been quantified using target volume, flattening, and eccentricity. The target motion was measured by tracking the centroids of the spheres in each individual phase. Motion ground-truth was obtained from input signals and real-time video recordings.

RESULTS

The dynamic phantom has been operated in four respiratory rate (RR) settings, 6, 10, 15, and 20/min, and was scanned with 4D-MRI and 4D-CT. 4D-CT images have target-stretching, partial-missing, and other motion artifacts in various phases, whereas the 4D-MRI images are visually free of those artifacts. Volume percentage difference for the 6.37 ml target ranged from 5.3% ± 4.3% to 10.3% ± 5.9% for 4D-CT, and 1.47 ± 0.52 to 2.12 ± 1.60 for 4D-MRI. With an increase of respiratory rate, the target volumetric and geometric deviations increase for 4D-CT images while remaining stable for the 4D-MRI images. Target motion amplitude errors at different RRs were measured with a range of 0.66-1.25 mm for 4D-CT and 0.2-0.42 mm for 4D-MRI. The results of Mann-Whitney tests indicated that 4D-MRI significantly outperforms 4D-CT in phase-based target volumetric (p = 0.027) and geometric (p < 0.001) measures. Both modalities achieve equivalent accuracy in measuring motion amplitude (p = 0.828).

CONCLUSIONS

The k-space self-gated 4D-MRI technique provides a robust method for accurately imaging phase-based target motion and geometry. Compared to 4D-CT, the current 4D-MRI technique demonstrates superior spatiotemporal resolution, and robust resistance to motion artifacts caused by fast target motion and irregular breathing patterns. The technique can be used extensively in abdominal targeting, motion gating, and toward implementing MRI-based adaptive radiotherapy.

Stratification of Prognosis of Triple-Negative Breast Cancer Patients Using Combinatorial Biomarkers

Background

Triple-negative breast cancer (TNBC) is highly diverse group of cancers, and generally considered an aggressive disease associated with poor survival. Stratification of TNBC is highly desired for both prognosis and treatment decisions to identify patients who may benefit from less aggressive therapy.

Methods

This study retrieved 192 consecutive non-metastasis TNBC patients who had undergone a resection of a primary tumor from 2008 to 2012. All samples were negative for ER, PR, and HER2/neu. Disease-free-survival (DFS) and overall-survival (OS) were evaluated for expression of immunohistochemical biomarkers (P53, Ki-67, CK5/6 and EGFR), as well as clinicopathological variables including age, tumor size, grade, lymph node status, pathologic tumor and nodal stages. The cutoff values of the basal biomarkers, EGFR and CK5/6, were estimated by time-dependent ROC curves. The prognostic values of combinatorial variables were identified by univariate and multivariate Cox analysis. Patients were stratified into different risk groups based on expression status of identified prognostic variables.

Results

Median age was 57 years (range, 28–92 years). Patients’ tumor stage and nodal stage were significantly associated with OS and DFS. EGFR and CK5/6 were significant prognostic variables at cutoff points of 15% (p = 0.001, AUC = 0.723), and 50% (p = 0.006, AUC = 0.675), respectively. Multivariate Cox analysis identified five significant variables: EGFR (p = 0.016), CK5/6 (p = 0.018), Ki-67 (p = 0.048), tumor stage (p = 0.010), and nodal stage (p = 0.003). Patients were stratified into low basal (EGFR≤15% and CK5/6≤50%) and high basal (EGFR>15% and/or CK5/6>50%) expression groups. In the low basal expression group, patients with low expressions of Ki-67, low tumor and nodal stage had significantly better survival than those with high expressions/stages of three variables, log-rank p = 0.015 (100% vs 68% at 50 months). In the high basal expression group, patient with high basal expression of both biomarkers (EGFR >15% and CK5/6 >50%) had worse survival (mean DFS = 25 months, 41.7% event rate) than those patient with high expression of either one marker (mean DFS = 34 months, 25.5% event rate).

Conclusions

Immunoexpression of basal biomarkers, EGFR and CK5/6, is useful in predicting survival of TNBC patients. Integrated with Ki-67, tumor and nodal stages, combinatorial biomarker analysis provides a feasible clinical solution to stratify patient risks and help clinical decision-making with respect to selecting the appropriate therapies for individual patients.

Abstract P5-01-03: Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging

Introduction: Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and may benefit from molecular-targeted therapies. This study aims to stratify prognosis of TNBC patients using pre-treatment 18F-FDG PET/CT, alone and with correlation to immunohistochemistry biomarkers.

Method: 200 consecutive TNBC breast cancer patients treated between 2008 and 2012 who received lumpectomy or mastectomy as primary treatment were retrieved. Among the full cohort, 79 patients had pre-treatment 18F FDG PET/CT scans. Immunostaining status (percentage and intensity) of basal biomarkers (EGFR, CK5/6), Ki-67, P53, and other clinicopathological variables (age, tumor size, pathological T/N stage, nuclear grade, and lymph node metastasis) were obtained. Three PET image features were evaluated: maximum uptake values (SUVmax), mean uptake (SUVmean) and target volume (SUVvol) defined by SUV&gt;2.5. The relationships among tumor metabolic activities and clinicopathological factors were evaluated. All variables were analyzed versus disease-free survival (DFS) using univariate and multivariate Cox analysis, Kaplan-Meier curves and log-rank tests. The optimal cutoff points of variables were estimated using time-dependent survival receiver operating characteristic (ROC) analysis.

Results: All PET features significantly correlated with proliferation marker Ki-67 (all p&lt;0.010). SUVmax stratified the prognosis of TNBC patients with optimal cutoff derived by ROC analysis (≤3.5 vs &gt;3.5, AUC=0.654, p=0.006). Basal biomarkers EGFR and CK5/6 and image features SUVmax, SUVmean, SUVvol were significant associated with DFS in univariate Cox analysis, whereas SUVmax (p=0.001) and EGFR (p=0.001) were also significant in multivariate Cox analysis. To integrate prognosis of biological and imaging markers, patients were first stratified by EGFR into low (≤15%) and high (&gt;15%) risk groups. Further, SUVmax was used as a variable to stratify the two EGFR groups. In the high EGFR group, patients with high FDG uptake (SUVmax&gt;3.5) had worse survival outcome (median DFS=7.6 months) than those patients with low FDG uptake (SUVmax≤3.5, median DFS=11.6 months). In the low EGFR group, high SUVmax also indicated worse survival outcome (17.2 months) than low SUVmax (22.8 months). The risk stratification with integrative EGFR and PET was statistically significant with log-rank p&lt;&lt;0.001.

Multivariate Cox analysis for disease-free survivalVariablesHR (95% CI)p-valuePathology, T stage, ≤ 3 vs &gt;32.337(0.428-7.384)0.148EGFR, ≤15% vs &gt; 15%9.109(1.997-41.55)0.004CK5/6, ≤ 50% vs &gt; 50%1.471(0.598-3.614)0.401SUVmax, ≤3.5 vs &gt; 3.53.883(1.13-13.32)0.031

TNBC patient risk groups stratified by EGFR and SUVmax (with the median values of variables)Risk groups (EGFR&gt;15, SUVmax&gt;3.5)patient#DFS monthsEGFR %SUVmaxSUVmeanSUVvolKi-67%1 (-, -)1222.852.00.60.2342 (-, +)1517.258.94.37.2673 (+, -)1311.6502.72.60.9354 (+, +)377.66011.35.210.960

Conclusions: Pre-treatment 18F-FDG PET/CT imaging has significant prognostic value for predicting survival outcome of TNBC patients. Integrated with basal-biomarker EGFR, PET imaging can further stratify patient risks in the pre-treatment stage, and help select appropriate treatment strategies for individual patients.

Citation Format: Yue Y, Cui X, Bose S, Audeh W, Zhang X, Fraass B. Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-01-03.

Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging

This study aims to stratify prognosis of triple-negative breast cancer (TNBC) patients using pre-treatment 18F-FDG-PET/CT, alone and with correlation to immunohistochemistry biomarkers. 200 consecutive TNBC breast cancer patients treated between 2008 and 2012 were retrieved. Among the full cohort, 79 patients had pre-treatment 18F-FDG-PET/CT scans. Immunostaining status of basal biomarkers (EGFR, CK5/6) and other clinicopathological variables were obtained. Three PET image features were evaluated: maximum uptake values (SUVmax), mean uptake (SUVmean), and metabolic volume (SUVvol) defined by SUV > 2.5. All variables were analyzed versus disease-free survival (DFS) using univariate and multivariate Cox analysis, Kaplan-Meier curves, and log-rank tests. The optimal cutoff points of variables were estimated using time-dependent survival receiver operating characteristic (ROC) analysis. All PET features significantly correlated with proliferation marker Ki-67 (all p < 0.010). SUVmax stratified the prognosis of TNBC patients with optimal cutoff derived by ROC analysis (≤3.5 vs. >3.5, AUC = 0.654, p = 0.006). SUVmax and EGFR were significant prognostic factors in univariate and multivariate Cox analyses. To integrate prognosis of biological and imaging markers, patients were first stratified by EGFR into low (≤15 %) and high (>15 %) risk groups. Further, SUVmax was used as a variable to stratify the two EGFR groups. In the high EGFR group, patients with high FDG uptake (SUVmax > 3.5) had worse survival outcome (median DFS = 7.6 months) than those patients with low FDG uptake (SUVmax ≤ 3.5, median DFS = 11.6 months). In the low EGFR group, high SUVmax also indicated worse survival outcome (17.2 months) than low SUVmax (22.8 months). The risk stratification with integrative EGFR and PET was statistically significant with log-rank p ≪ 0.001. Pre-treatment 18F-FDG-PET/CT imaging has significant prognostic value for predicting survival outcome of TNBC patients. Integrated with basal-biomarker EGFR, PET imaging can further stratify patient risks in the pre-treatment stage and help select appropriate treatment strategies for individual patients.

Four-dimensional MRI using three-dimensional radial sampling with respiratory self-gating to characterize temporal phase-resolved respiratory motion in the abdomen

PURPOSE

To develop a four-dimensional MRI (4D-MRI) technique to characterize the average respiratory tumor motion for abdominal radiotherapy planning.

METHODS

A continuous spoiled gradient echo sequence was implemented with 3D radial trajectory and 1D self-gating for respiratory motion detection. Data were retrospectively sorted into different respiratory phases based on their temporal locations within a respiratory cycle, and each phase was reconstructed by means of a self-calibrating CG-SENSE program. Motion phantom, healthy volunteer and patient studies were performed to validate the respiratory motion detected by the proposed method against that from a 2D real-time protocol.

RESULTS

The proposed method successfully visualized the respiratory motion in phantom and human subjects. The 4D-MRI and real-time 2D-MRI yielded comparable superior-inferior (SI) motion amplitudes (intraclass correlation = 0.935) with up-to one pixel mean absolute differences in SI displacements over 10 phases and high cross-correlation between phase-resolved displacements (phantom: 0.985; human: 0.937-0.985). Comparable anterior-posterior and left-right displacements of the tumor or gold fiducial between 4D and real-time 2D-MRI were also observed in the two patients, and the hysteresis effect was shown in their 3D trajectories.

CONCLUSION

We demonstrated the feasibility of the proposed 4D-MRI technique to characterize abdominal respiratory motion, which may provide valuable information for radiotherapy planning.

18F-FDG PET as a predictor of resectability and clinical outcomes in locally advanced pancreatic cancer patients treated with radiotherapy

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Background: Surgical resection is the preferred approach for localized pancreatic adenocarcinoma, yet likelihood of margin positive resection precludes its use in patients with locally advanced (LAPA) disease. Whereas CT imaging is the standard for defining resectability, studies suggest reduced accuracy following radiotherapy (RT). Given the potential clinical implications, improved methods to define resectability are needed. We investigate whether PET and other clinical factors can be used to predict likelihood of margin negative resection in LAPA patients. Methods: We reviewed LAPA patients treated with RT from 2011-2013 who also underwent pre- and 6-week post-RT PET/CT. Mann-Whitney test and Cox modeling were used to identify predictors of margin negative resection and progression-free survival (PFS), respectively. Variables assessed included: pre- and post-RT SUV max, mean, coefficient of variation (CV), total lesion glycolysis, CA19-9 and tumor size. Results: Eighteen LAPA patients treated with RT were identified. Median age was 66 years. Seven were considered resectable following RT. 6 patients underwent margin negative resection, while the 7thpatient refused surgery. An additional 2 patients were technically resectable, but developed metastatic disease. Mean value for post-RT SUV max was 3.5 in resected patients versus 4.9 in unresected patients. This difference was borderline significant (p=.08) for predicting resectability. Similarly, pre- to post-RT change in SUV max was -4.37 in resected patients and -1.26 in unresected patients, which was also not significant (p=.17). Median PFS was 13 months for resected patients and 8.5 months for unresected patients (p=.06). Predictors of PFS included post-RT SUV CV (p=.05) and pre-RT CA19-9 (p=.03). Conclusions: Mean post-RT SUV max was borderline significant for predicting which LAPA patients may undergo successful margin negative resection. Post-RT metabolic response was also predictive of improved PFS, further validating PET/CT as an important prognostic imaging tool. Studies are ongoing to further validate these predictors of resectability given the potential clinical significance.

Pretreatment [18F] FDG-PET texture analysis to predict local response of pancreatic cancer to radiotherapy

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Background: Accurate assessment of radiographic response following radiotherapy (RT) for pancreatic adenocarcinoma is challenging. Morphologic and textural features of FDG-PET have been shown to correlate with pathologic response and clinical outcomes in other solid tumors (PMID 23204495). The goal of this study was to develop a predictive algorithm derived from textural features of PET scans to predict response to RT. Methods: With IRB approval, we reviewed 10 patients with locally advanced pancreatic cancer treated with stereotactic body radiation therapy (25-30 Gy in 5 daily fractions). 18FDG-PET/CT scans were obtained 2 weeks pre-RT and 6 weeks post-RT. Pre-RT PET/CT images were deformably registered to the RT planning CT. Tumor volumes of interest were divided into (4.8mm)^3 subvolumes and characterized by mean SUV uptake, RT dose and comprehensive texture analysis. These pre-RT variables were correlated to post-RT mean SUV to identify potential predictors of treatment response. Response prediction was modeled by logistic regression with the Lasso algorithm and validated by 10-fold cross-validation. Model performance was assessed using cross-validated area under the receiver operating characteristic curves (AUC). Results: Mean uptake, RT dose and 6 texture features (energy, correlation, variance, sum mean, cluster tendency, and inverse variance) on pre-RT PET scans were significant in predicting treatment response (AUC 0.85). Within this model, each of the above noted variables was predictive of post-RT response (p<.05). Conclusions: Subvolume-based metabolic and texture features of pre-treatment PET scans were predictive of response following RT. Studies are ongoing to further correlate these variables to RECIST and pathologic response. This should serve as a useful model to help direct response-driven adaptive radiotherapy in patients with locally advanced pancreatic cancer.

Safety considerations for IGRT: Executive summary

Radiation therapy is an effective cancer treatment that is constantly being transformed by technological innovation. Dedicated devices for fraction-by-fraction imaging and guidance within the treatment room have enabled image guided radiation therapy (IGRT) allowing clinicians to pursue highly conformal dose distributions, higher dose prescriptions, and shorter fractionation schedules. Capitalizing on IGRT-enabled accuracy and precision requires a strong link between IGRT practices and planning target volume (PTV) design. This is clearly central to high quality, safe radiation therapy. Failure to properly apply IGRT methods or to coordinate their use with an appropriate PTV margin can result in a treatment that is 'precisely wrong'. The white paper summarized in this executive summary recommends foundational elements and specific activities to maximize the safety and effectiveness of IGRT.

TU-E-211-01: Establishing Multidisciplinary Collaboration as a Medical Physicist

Many medical physicists are scientists at heart and their career fulfillment includes a balance of clinical service and research development. Multidisciplinary collaboration is a great way for the medical physicists to advance science and technology of our fields and the fields of our collaborators. Cross-pollination among scientists of different fields has been the key for some of the most significant breakthroughs in science and medicine and produced some of the most rewarding experiences for the individuals involved. However, medical physicists face unique challenges in establishing multidisciplinary collaboration because our time and resources for research are often quite limited compared to basic scientists. Yet we medical physicists are uniquely positioned and have a tremendous opportunity to create/contribute to multidisciplinary research: our fields are already multidisciplinary in nature and hospital environment is problem rich. How do we establish and carry out research collaboration with scientists of other fields? How to balance research with your higher priority clinical service? How do you find the right multidisciplinary collaboration in your own environment? We will discuss the challenges, provide real exemplary solutions to the above questions, and offer advise to medical physicists who are interested in starting or improving their multidisciplinary collaboration. There are different kinds of multidisciplinary collaborations a medical physicist can create and participate at different involvement levels. Multidisciplinary collaboration is not for every medical physicist but for those who seek and devote time to it, the experience can be truly rewarding and the impact can be enormous.

LEARNING OBJECTIVES

1. Learn the types of multidisciplinary collaboration medical physicists can created/participated 2. Learn the approaches and strategies to develop collaborations with scientists and professional of other fields3. Understand the challenges and different approaches to balance clinical service and multidisciplinary research collaboration.