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1.  Adaptive Management of Liver Cancer Radiotherapy 
Seminars in radiation oncology  2010;20(2):107-115.
Adaptive radiation therapy for liver cancer has the potential to reduce normal tissue complications and enable dose escalation, allowing the potential for tumor control in this challenging site. Using adaptive techniques to tailor treatment margins to reflect patient specific breathing motions and image-guidance techniques can reduce the high dose delivered to surrounding normal tissues while ensuring the prescription dose is delivered to the tumor. Several treatment planning and delivery techniques have been developed for use in the liver, including a margin to encompass the full breathing motion, mean position techniques, which evaluate the probability of tumor location during breathing, breath hold, gating, and tracking. Patient selection, clinical workflow, and quality assurance must be considered and developed prior to integrating these techniques into clinical practice.
PMCID: PMC2856079  PMID: 20219548
The actual distribution of radiation dose accumulated in normal tissues over the complete course of radiation therapy is, in general, poorly quantified. Differences in the patient anatomy between planning and treatment can occur gradually (e.g., tumor regression, resolution of edema) or relatively rapidly (e.g., bladder filling, breathing motion) and these undermine the accuracy of the planned dose distribution. Current efforts to maximize the therapeutic ratio require models that relate the true accumulated dose to clinical outcome. The needed accuracy can only be achieved through the development of robust methods that track the accumulation of dose within the various tissues in the body. Specific needs include the development of segmentation methods, tissue-mapping algorithms, uncertainty estimation, optimal schedules for image-based monitoring, and the development of informatics tools to support subsequent analysis. These developments will not only improve radiation outcomes modeling but will address the technical demands of the adaptive radiotherapy paradigm. The next 5 years need to see academia and industry bring these tools into the hands of the clinician and the clinical scientist.
PMCID: PMC4041516  PMID: 20171508
Dose accumulation; Normal tissue effects; Deformation; Four-dimensional; Informatics
3.  Accumulated Dose in Liver Stereotactic-Body Radiotherapy: Positioning, Breathing and Deformation Effects 
To investigate the accumulated dose deviations to tumors and normal tissues in liver stereotactic-body radiotherapy (SBRT), and investigate their geometric causes.
Methods and Materials
Thirty previously treated liver cancer patients were retrospectively evaluated. SBRT was planned on the static exhale CT for 27 – 60 Gy in 6 fractions, and patients were treated in free-breathing with daily cone-beam CT (CBCT) guidance. Biomechanical model-based deformable image registration accumulated dose over both the planning 4DCT (predicted breathing dose), and also over each fraction’s respiratory-correlated CBCT (accumulated treatment dose). The contribution of different geometric errors on changes between the accumulated and predicted breathing dose were quantified.
Twenty one patients (70%) had accumulated dose deviations relative to the planned static prescription dose greater than 5%, ranging from −15 to 5% in tumors and −42 to 8% in normal tissues. Sixteen patients (53%) still had deviations relative to the 4DCT-predicted dose, which were similar in magnitude. Thirty two tissues in these 16 patients had deviations > 5% relative to the 4DCT-predicted dose, and residual setup errors (n=17) were most often the largest cause of the deviations, followed by deformations (n=8) and breathing variations (n=7).
The majority of patients had accumulated dose deviations greater than 5% relative to the static plan. Significant deviations relative to the predicted breathing dose still occurred in over half the patients, commonly due to residual setup errors. Accumulated SBRT dose may be warranted to pursue further dose-escalation, adaptive SBRT, and aid in correlation with clinical outcomes.
PMCID: PMC3337347  PMID: 22208969
Deformable registration; Dose accumulation; Image-guided radiotherapy; Stereotactic-body radiotherapy; Liver cancer
4.  Imaging and IGRT in Liver Cancer 
Seminars in radiation oncology  2011;21(4):247-255.
Imaging for radiation therapy treatment planning and delivery is a critical component of the radiation planning process for liver cancer. Due to the lack of inherent contrast between liver tumors and the surrounding liver, intravenous contrast is required for accurate target delineation on the planning CT. The appropriate phase of contrast is tumor specific, with arterial phase imaging usually used to define hepatocellular carcinoma, and venous phase imaging for vascular thrombosis related to hepatocellular carcinoma and most types of liver metastases. Breathing motion and changes in the liver position day-to-day may be substantial and need to be considered at the time of radiation planning and treatment. Many types of integrated imaging-radiation treatment systems and image guidance strategies are available to produce volumetric and/or planar imaging at the time of treatment delivery to reduce the negative impact of geometric changes that may occur. Image guided radiation therapy (IGRT) can improve the precision of radiation therapy, so that the prescribed doses are more likely to represent those actually delivered.
PMCID: PMC3428059  PMID: 21939853
For patients receiving liver stereotactic body radiotherapy (SBRT), abdominal compression can reduce organ motion, and daily image guidance can reduce setup error. The reproducibility of liver shape under compression may impact treatment delivery accuracy. The purpose of this study was to measure the interfractional variability in liver shape under compression, after best-fit rigid liver-to-liver registration from kilovoltage (kV) cone beam computed tomography (CBCT) scans to planning computed tomography (CT) scans and its impact on gross tumor volume (GTV) position.
Methods and Materials
Evaluable patients were treated in a Research Ethics Board–approved SBRT six-fraction study with abdominal compression. Kilovoltage CBCT scans were acquired before treatment and reconstructed as respiratory sorted CBCT scans offline. Manual rigid liver-to-liver registrations were performed from exhale-phase CBCT scans to exhale planning CT scans. Each CBCT liver was contoured, exported, and compared with the planning CT scan for spatial differences, by use of in house–developed finite-element model–based deformable registration (MORFEUS).
We evaluated 83 CBCT scans from 16 patients with 30 GTVs. The mean volume of liver that deformed by greater than 3 mm was 21.7%. Excluding 1 outlier, the maximum volume that deformed by greater than 3 mm was 36.3% in a single patient. Over all patients, the absolute maximum deformations in the left–right (LR), anterior–posterior (AP), and superior–inferior directions were 10.5 mm (SD, 2.2), 12.9 mm (SD, 3.6), and 5.6 mm (SD, 2.7), respectively. The absolute mean predicted impact of liver volume displacements on GTV by use of center of mass displacements was 0.09 mm (SD, 0.13), 0.13 mm (SD, 0.18), and 0.08 mm (SD, 0.07) in the left–right, anterior–posterior, and superior–inferior directions, respectively.
Interfraction liver deformations in patients undergoing SBRT under abdominal compression after rigid liver-to-liver registrations on respiratory sorted CBCT scans were small in most patients (<5 mm).
PMCID: PMC3037422  PMID: 20947263
Liver radiotherapy; Abdominal compression; Deformable registration
6.  Effect of Breathing Motion on Radiotherapy Dose Accumulation in the Abdomen Using Deformable Registration 
To investigate the effect of breathing motion and dose accumulation on the planned radiotherapy dose to liver tumors and normal tissues using deformable image registration.
Method and Materials
Twenty one free-breathing stereotactic liver cancer radiotherapy patients, planned on static exhale CT for 27 – 60 Gy in 6 fractions, were included. A biomechanical model-based deformable image registration algorithm, retrospectively deformed each exhale CT to inhale CT. This deformation map was combined with exhale and inhale dose grids from the treatment planning system to accumulate dose over the breathing cycle. Accumulation was also investigated using a simple rigid liver-to-liver registration. Changes to tumor and normal tissue dose were quantified.
Relative to static plans, mean dose change (range) after deformable dose accumulation (as % of prescription dose) was −1 (−14, 8) to minimum tumor, −4 (−15, 0) to max bowel, −4 (−25, 1) to max duodenum, 2 (−1, 9) to max esophagus, −2 (−13, 4) to max stomach, 0 (−3, 4) to mean liver, and −1 (−5, 1) and −2 (−7, 1) to mean left and right kidneys. Compared to deformable registration, rigid modeling had changes up to 8% to minimum tumor and 7% to maximum normal tissues.
Deformable registration and dose accumulation revealed potentially significant dose changes to either a tumor or normal tissue in the majority of cases due to breathing motion. These changes may not be accurately accounted for with rigid motion.
PMCID: PMC3010501  PMID: 20732755
Deformable image registration; respiratory motion; 4D dose calculations; stereotactic body radiotherapy; liver cancer
7.  Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data 
BMC Medical Physics  2012;12:1.
Biologically-based models that utilize 3D radiation dosimetry data to estimate the risk of late cardiac effects could have significant utility for planning radiotherapy in young patients. A major challenge arises from having only 2D treatment planning data for patients with long-term follow-up. In this study, we evaluate the accuracy of an advanced deformable image registration (DIR) and navigator channels (NC) adaptation technique to reconstruct 3D heart volumes from 2D radiotherapy planning images for Hodgkin's Lymphoma (HL) patients.
Planning CT images were obtained for 50 HL patients who underwent mediastinal radiotherapy. Twelve image sets (6 male, 6 female) were used to construct a male and a female population heart model, which was registered to 23 HL "Reference" patients' CT images using a DIR algorithm, MORFEUS. This generated a series of population-to-Reference patient specific 3D deformation maps. The technique was independently tested on 15 additional "Test" patients by reconstructing their 3D heart volumes using 2D digitally reconstructed radiographs (DRR). The technique involved: 1) identifying a matching Reference patient for each Test patient using thorax measurements, 2) placement of six NCs on matching Reference and Test patients' DRRs to capture differences in significant heart curvatures, 3) adapting the population-to-Reference patient-specific deformation maps to generate population-to-Test patient-specific deformation maps using linear and bilinear interpolation methods, 4) applying population-to-Test patient specific deformation to the population model to reconstruct Test-patient specific 3D heart models. The percentage volume overlap between the NC-adapted reconstruction and actual Test patient's true heart volume was calculated using the Dice coefficient.
The average Dice coefficient expressed as a percentage between the NC-adapted and actual Test model was 89.4 ± 2.8%. The modified NC adaptation technique made significant improvements to the population deformation heart models (p = 0.01). As standard evaluation, the residual Dice error after adaptation was comparable to the volumetric differences observed in free-breathing heart volumes (p = 0.62).
The reconstruction technique described generates accurate 3D heart models from limited 2D planning data. This development could potentially be used to retrospectively calculate delivered dose to the heart for historically treated patients and thereby provide a better understanding of late radiation-related cardiac effects.
PMCID: PMC3398341  PMID: 22257738
8.  Biomechanical model-based deformable registration of MRI and histopathology for clinical prostatectomy 
A biomechanical model-based deformable image registration incorporating specimen-specific changes in material properties is optimized and evaluated for correlating histology of clinical prostatectomy specimens with in vivo MRI. In this methodology, a three-step registration based on biomechanics calculates the transformations between histology and fixed, fixed and fresh, and fresh and in vivo states. A heterogeneous linear elastic material model is constructed based on magnetic resonance elastography (MRE) results. The ex vivo tissue MRE data provide specimen-specific information for the fresh and fixed tissue to account for the changes due to fixation. The accuracy of the algorithm was quantified by calculating the target registration error (TRE) by identifying naturally occurring anatomical points within the prostate in each image. TRE were improved with the deformable registration algorithm compared to rigid registration alone. The qualitative assessment also showed a good alignment between histology and MRI after the proposed deformable registration.
PMCID: PMC3312716  PMID: 22811954
Biomechanical models; correlative pathology; deformable registration; finite element model; magnetic resonance elastography

Results 1-8 (8)