M. Gobeli

Evaluation of Deformable Image Registration Methods for Dose Monitoring in Head and Neck Radiotherapy

In the context of head and neck cancer (HNC) adaptive radiation therapy (ART), the two purposes of the study were to compare the performance of multiple deformable image registration (DIR) methods and to quantify their impact for dose accumulation, in healthy structures. Fifteen HNC patients had a planning computed tomography (CT0) and weekly CTs during the 7 weeks of intensity-modulated radiation therapy (IMRT). Ten DIR approaches using different registration methods (demons or B-spline free form deformation (FFD)), preprocessing, and similarity metrics were tested. Two observers identified 14 landmarks (LM) on each CT-scan to compute LM registration error. The cumulated doses estimated by each method were compared. The two most effective DIR methods were the demons and the FFD, with both the mutual information (MI) metric and the filtered CTs. The corresponding LM registration accuracy (precision) was 2.44 mm (1.30 mm) and 2.54 mm (1.33 mm), respectively. The corresponding LM estimated cumulated dose accuracy (dose precision) was 0.85 Gy (0.93 Gy) and 0.88 Gy (0.95 Gy), respectively. The mean uncertainty (difference between maximal and minimal dose considering all the 10 methods) to estimate the cumulated mean dose to the parotid gland (PG) was 4.03 Gy (SD = 2.27 Gy, range: 1.06–8.91 Gy).

PD-0356: 18F-FDG PET parameters during radio-chemotherapy to predict tumor recurrence in cervical cancer

These prospective study included 53 patients treated for locally advanced cervical cancer by external beam radiation therapy with concurrent chemotherapy, followed by brachytherapy and + surgery. All patients were evaluated by FDG PET/CT before treatment (PET1) and at 40 Gy (PET2). PET-parameters analysed were: maximum standardized uptake value (SUVmax1, SUVmax2), metabolic tumour volume (MTV1, MTV2), and total lesion glycolysis (TLG1, TLG2). MTV1 and MTV2 were automatically segmented (region-growing) using different thresholds (between 30% and 80% of SUVmax). The recurrence were defined based on clinical examination, MRI and PET imaging. Median follow-up was 30 months [range: 8-60]. A total of 13 patients developed disease recurrence and 7 died of disease. The predictive capabilities of the PET parameters to predict overall recurrence were tested using Cox proportional hazards regression models (p values calculated). Comparisons among different models were done by calculating the Harrel’s C-index (c).

Treatment plan library based on population shape analysis for cervical adaptive radiotherapy.

External radiotherapy is extensively used to treat cervix carcinoma. It is based on the acquisition of a planning CT scan on which the treatment is optimized before being delivered over 25 fractions. However, large pertreatment anatomical variations, hamper the dose delivery accuracy, with a risk of tumor under-dose and healthy organs over-dose resulting to recurrence and toxicity. We propose to generate a patient-specific treatment library based on a population analysis. First, the cervix meshes of the population were registered towards a template anatomy using a deformable mesh registration (DMR). The DMR follows an iterative point matching approach based on the local shape context (histogram of cylindrical neighbor coordinates and normalized geodesic distance to the cervix base), a topology constraint filter, a thin-plate-spline interpolation and a Gaussian regularization. Second, a standard principal component analysis (PCA) model was generated to estimate the dominant deformation modes of the population. Posterior PCA was computed to generate different potential anatomies of the target. For a new patient, her cervix was registered towards the template and her pre-treatment library was modeled. This method was applied on the data of 19 patients (282 images), using a leave-one-patient-out. The DMR was evaluated using point-to-point distance (mean: 1.3 mm), Hausdorff distance (5.7 mm), dice coeffi- cient (0.96) and mean triangle area difference (0.49 mm2 ). The performances of two modeled libraries (2 and 6 modeled anatomies) were compared to a classic pre-treatment library based on 3 planning CTs, showing better results according to both target and healthy organs coverage.