Purpose: Deformable image registration (DIR) plays an important role in dose accumulation, such as incorporating breathing motion into the accumulation of the delivered dose based on daily 4DCBCT images. However, it is not yet well understood how the uncertainties associated with DIR methods affect the dose calculations and resulting clinical metrics. The purpose of this study is to evaluate the impact of DIR uncertainty on the clinical metrics derived from its use in dose accumulation. Methods: A biomechanical model based DIR method and a biomechanical-intensity-based hybrid method, which reduced the average registration error by 1.6 mm, were applied to ten lung cancer patients. A clinically relevant dose parameter [minimum dose to 0.5 cm 3 (Dmin)] was calculated for three dose scenarios using both algorithms. Dose scenarios included static (no breathing motion), predicted (breathing motion at the time of planning), and total accumulated (interfraction breathing motion). The relationship between the dose parameter and a combination of DIR uncertainty metrics, tumor volume, and dose heterogeneity of the plan was investigated. Results: Depending on the dose heterogeneity, tumor volume, and DIR uncertainty, in over 50% of the patients, differences greater than 1.0 Gy were observed in the Dmin of the tumor in the static dose calculation on exhale phase of the 4DCT. Such differences were due to the errors in propagating the tumor contours from the reference planning 4DCT phase onto a subsequent 4DCT phase using each DIR algorithm and calculating the dose on that phase. The differences in predicted dose were more subtle when breathing motion was modeled explicitly at the time of planning with only one patient exhibiting a greater than 1.0 Gy difference in Dmin. Dmin differences of up to 2.5 Gy were found in the total accumulated delivered dose due to difference in quantifying the interfraction variations. Such dose uncertainties could potentially be clinically significant. Conclusions: Reductions in average uncertainty in DIR algorithms by 1.6 mm may have a clinically significant impact on the decision-making metrics used in dose planning and dose accumulation assessment. C

Purpose Deformable Image Registration (DIR) has been extensively studied over the past two decades due to its essential role in many image-guided interventions (IGI). IGI demands a highly accurate registration that maintains its accuracy across the entire region of interest. This work evaluates the improvement in accuracy and consistency by refining the results of Morfeus, a biomechanical model-based DIR algorithm. Methods and Materials A Hybrid DIR algorithm is proposed based on, a biomechanical model–based DIR algorithm and a refinement step based on a B-spline intensity-based algorithm. Inhale and exhale reconstructions of 4DCT lung images from 31 patients were initially registered using the biomechanical DIR by modeling contact surface between the lungs and the chest cavity. The resulting deformations were then refined using the intensity-based algorithm to reduce any residual uncertainties. Important parameters in the intensity-based algorithm, including grid spacing, number of pyramids, and regularization coefficient, were optimized on 10 randomly-chosen patients (out of 31). Target Registration Error (TRE) was calculated by measuring the Euclidean distance of common anatomical points on both images after registration. For each patient a minimum of 30 points/lung were used. Results Grid spacing of 8 mm, 5 levels of grid pyramids, and regularization coefficient of 3.0 were found to provide optimal results on 10 randomly chosen patients. Overall the entire patient population (n = 31), the Hybrid method resulted in mean±SD (90th%) TRE of 1.5±1.4 (2.9) mm compared to 3.1±1.9 (5.6) using biomechanical DIR and 2.6±2.5 (6.1) using intensity-based DIR alone. Conclusions The proposed hybrid biomechanical modeling intensity based algorithm is a promising DIR technique which could be used in various IGI procedures. The current investigation shows the efficacy of this approach for the registration of 4DCT images of the lungs with average accuracy of 1.5 mm.

Purpose MRI is under evaluation for image-guided intervention for prostate cancer. The sensitivity and specificity of MRI parameters is determined via correlation with the gold-standard of histopathology. Whole-mount histopathology of prostatectomy specimens can be digitally registered to in vivo imaging for correlation. When biomechanical-based deformable registration is employed to account for deformation during histopathology processing, the ex vivo biomechanical properties are required. However, these properties are altered by pathology fixation, and vary with disease. Hence, this study employs magnetic resonance elastography (MRE) to measure ex vivo prostate biomechanical properties before and after fixation. Methods A quasi-static MRE method was employed to measure high resolution maps of Young’s modulus (E) before and after fixation of canine prostate and prostatectomy specimens (n=4) from prostate cancer patients who had previously received radiation therapy. For comparison, T1, T2 and apparent diffusion coefficient (ADC) were measured in parallel. Results E (kPa) varied across clinical anatomy and for histopathology-identified tumor: peripheral zone: 99(±22), central gland: 48(±37), tumor: 85(±53), and increased consistently with fixation (factor of 11±5; p<0.02). T2 decreased consistently with fixation, while changes in T1 and ADC were more complex and inconsistent. Conclusion The biomechanics of the clinical prostate specimens varied greatly with fixation, and to a lesser extent with disease and anatomy. The data obtained will improve the precision of prostate pathology correlation, leading to more accurate disease detection and targeting.

Purpose: Validation of MRI-guided tumor boundary delineation for targeted prostate cancer therapy is achieved via correlation with gold-standard histopathology of radical prostatectomy specimens. Challenges to accurate correlation include matching the pathology sectioning plane with the in vivo imaging slice plane and correction for the deformation that occurs between in vivo imaging and histology. A methodology is presented for matching of the histological sectioning angle and position to the in vivo imaging slices. Methods: Patients (n = 4) with biochemical failure following external beam radiotherapy underwent diagnostic MRI to confirm localized recurrence of prostate cancer, followed by salvage radical prostatectomy. High-resolution 3-D MRI of the ex vivo specimens was acquired to determine the pathology sectioning angle that best matched the in vivo imaging slice plane, using matching anatomical features and implanted fiducials. A novel sectioning device was developed to guide sectioning at the correct angle, and to assist the insertion of reference dye marks to aid in histopathology reconstruction. Results: The percentage difference in the positioning of the urethra in the ex vivo pathology sections compared to the positioning in in vivo images was reduced from 34% to 7% through slicing at the best match angle. Reference dye marks were generated, which were visible in ex vivo imaging, in the tissue sections before and after processing, and in histology sections. Conclusions: The method achieved an almost fivefold reduction in the slice-matching error and is readily implementable in combination with standard MRI technology. The technique will be employed to generate datasets for correlation of whole-specimen prostate histopathology with in vivo diagnostic MRI using 3-D deformable registration, allowing assessment of the sensitivity and specificity of MRI parameters for prostate cancer. Although developed specifically for prostate, the method is readily adaptable to other types of whole tissue specimen, such as mastectomy or liver resection. C 2016 American Association of Physicists in Medicine. [http://dx

No abstract