ESTRO 2020 Abstract Book

S329 ESTRO 2020

Biol. 64.11 (2019)). The resulting basis materials are called eigenmaterials. Results Figure 1a compares the root-mean-square error (RMSE) of the ED and proton stopping power averaged over all inserts of both Gammex phantoms. The MARS scanner with eigenmaterial characterization outperforms all DECT- based estimation methods (eigenmaterial and a ED-Z decomposition) for both parameters. RMSE is reduced from 1.1 to 0.8% for the ED, and from 1.8 to 0.8% for the proton stopping power. With a similar analysis, figure 1b demonstrates that the MARS scanner outperforms DECT to estimate all elemental mass fractions. Figures 1c-d respectively show errors on the VNC ED and iodine concentration for each iodine vial scanned. The MARS scanner generally outperforms DECT to estimate both quantities, with the RMSE averaged over all vials respectively reduced from 0.4 to 0.2% and 0.3 to 0.1 mg/mL with the MARS scanner. Figure 2a shows the quality of VNC ED maps and iodine concentration for all iodine vials. Figure 2b shows that beam hardening effects can be mitigated with the MARS scanner, due to the presence of high energy bins.

the benefits of using more energies to characterize human tissue equivalent materials.

OC-0586 Can MRI predict pathologic response after single dose neoadjuvant partial breast irradiation? J. Vasmel 1 , M. Groot Koerkamp 1 , R. Charaghvandi 2 , C. Vreuls 3 , P. Van Diest 3 , A. Witkamp 4 , R. Koelemij 5 , A. Doeksen 5 , T. Van Dalen 6 , E. Van der Wall 7 , J. Wijnen 8 , B. Van der Velden 8 , M. Moman 9 , W. Veldhuis 9 , M. Philippens 1 , S. Mandija 1 , J. Lagendijk 1 , H. Verkooijen 10 , A. Houweling 1 , D. Van den Bongard 1 1 UMC Utrecht, Radiotherapy, Utrecht, The Netherlands ; 2 Radboud UMC, Radiotherapy, Nijmegen, The Netherlands ; 3 UMC Utrecht, Pathology, Utrecht, The Netherlands ; 4 UMC Utrecht, Surgery, Utrecht, The Netherlands ; 5 St. Antonius hospital, Surgery, Nieuwegein, The Netherlands ; 6 Diakonessenhuis, Surgery, Utrecht, The Netherlands ; 7 UMC Utrecht, Medical Oncology, Utrecht, The Netherlands ; 8 UMC Utrecht, Image Science Institute, Utrecht, The Netherlands ; 9 UMC Utrecht, Radiology, Utrecht, The Netherlands ; 10 UMC Utrecht, Imaging Division, Utrecht, The Netherlands Purpose or Objective To assess radiologic response on MRI using radiologist assessment and quantitative parameters after single ablative dose neoadjuvant partial breast irradiation (NA- PBI) in low-risk breast cancer patients in order to predict Low-risk breast cancer patients were treated with NA-PBI (n=36; 1x 20 Gy to the tumor) followed by breast conserving surgery (BCS) after an interval of 6 or 8 months. Pathologic response was assessed as pathologic complete response (pCR), near pCR (<10% tumor cells), partial response (10-50% tumor cells), stable disease (>50% tumor cells), or no response according to EUSOMA criteria. Patients underwent MRI (3T Ingenia, Philips, Best, the Netherlands) in prone position pre-radiotherapy (RT), 1 week, 2, 4, 6, and, if applicable, 8 months post-RT. For each patient at least 4 scans were assessable. Radiologic response was evaluated by radiologists and by quantitative parameters. Breast radiologists assessed dynamic contrast enhanced (DCE) and diffusion weighted (DW) MRI according to clinical practice in neoadjuvant systemic treatment. Radiologic complete response was defined as complete absence of pathologic contrast enhancement and complete absence of diffusion restriction. The positive predictive value (PPV, probability that radiologic complete response predicts pCR) and negative predictive value (NPV, the probability that no radiologic complete response predicts residual disease) was calculated for the final MRI before BCS. For quantitative analysis the tumor was manually delineated on the pre-RT DCE-MRI. The delineation was rigidly transformed to the post-RT MRIs (Fig 1). Intrascan motion of the tumor was corrected using rigid registration. Within the GTV we evaluated the relative tumor enhancement at 2 min post-contrast (wash- in) and the distribution of enhancement curve types describing the wash-out of contrast (type 1: low, 2: intermediate, 3: high probability of malignancy) for voxels with at least 50% relative enhancement. Quantitative parameters were analyzed using descriptive statistics. pathologic response. Material and Methods

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Conclusion The MARS SPCCT can provide superior accuracy than a clinical DECT scanner to quantify physical parameters useful in radiotherapy. This highlights the potential of the technology for particle therapy, where more accurate tissue characterization is required, as well as for Monte- Carlo based planning, which requires accurate elemental mass fractions. This work experimentally demonstrates