A single point mutation in Ms44 results in dominant male sterility and improves nitrogen use efficiency in maize.

Application of nitrogen fertilizer in the past 50 years has resulted in significant increases in crop yields. However, loss of nitrogen from crop fields has been associated with negative impacts on the environment. Developing maize hybrids with improved nitrogen use efficiency is a cost-effective strategy for increasing yield sustainably. We report that a dominant male-sterile mutant Ms44 encodes a lipid transfer protein which is expressed specifically in the tapetum. A single amino acid change from alanine to threonine at the signal peptide cleavage site of the Ms44 protein abolished protein processing and impeded the secretion of protein from tapetal cells into the locule, resulting in dominant male sterility. While the total nitrogen (N) content in plants was not changed, Ms44 male-sterile plants reduced tassel growth and improved ear growth by partitioning more nitrogen to the ear, resulting in a 9.6% increase in kernel number. Hybrids carrying the Ms44 allele demonstrated a 4%-8.5% yield advantage when N is limiting, 1.7% yield advantage under drought and 0.9% yield advantage under optimal growth conditions relative to the yield of wild type. Furthermore, we have developed an Ms44 maintainer line for fertility restoration, male-sterile inbred seed increase and hybrid seed production. This study reveals that protein secretion from the tapetum into the locule is critical for pollen development and demonstrates that a reduction in competition between tassel and ear by male sterility improves grain yield under low-nitrogen conditions in maize.

Development of a novel recessive genetic male sterility system for hybrid seed production in maize and other cross-pollinating crops.

We have developed a novel hybridization platform that utilizes nuclear male sterility to produce hybrids in maize and other cross-pollinating crops. A key component of this platform is a process termed Seed Production Technology (SPT). This process incorporates a transgenic SPT maintainer line capable of propagating nontransgenic nuclear male-sterile lines for use as female parents in hybrid production. The maize SPT maintainer line is a homozygous recessive male sterile transformed with a SPT construct containing (i) a complementary wild-type male fertility gene to restore fertility, (ii) an α-amylase gene to disrupt pollination and (iii) a seed colour marker gene. The sporophytic wild-type allele complements the recessive mutation, enabling the development of pollen grains, all of which carry the recessive allele but with only half carrying the SPT transgenes. Pollen grains with the SPT transgenes exhibit starch depletion resulting from expression of α-amylase and are unable to germinate. Pollen grains that do not carry the SPT transgenes are nontransgenic and are able to fertilize homozygous mutant plants, resulting in nontransgenic male-sterile progeny for use as female parents. Because transgenic SPT maintainer seeds express a red fluorescent protein, they can be detected and efficiently separated from seeds that do not contain the SPT transgenes by mechanical colour sorting. The SPT process has the potential to replace current approaches to pollen control in commercial maize hybrid seed production. It also has important applications for other cross-pollinating crops where it can unlock the potential for greater hybrid productivity through expanding the parental germplasm pool.

Automated Verification of IGRT-based Patient Positioning.

A system for automated quality assurance in radiotherapy of a therapist's registration was designed and tested in clinical practice. The approach compliments the clinical software's automated registration in terms of algorithm configuration and performance, and constitutes a practical approach for ensuring safe patient setups. Per our convergence analysis, evolutionary algorithms perform better in finding the global optima of the cost function with discrepancies from a deterministic optimizer seen sporadically.

Automated population-based planning for whole brain radiation therapy.

Treatment planning for whole-brain radiation treatment is technically a simple process, but in practice it takes valuable clinical time of repetitive and tedious tasks. This report presents a method that automatically segments the relevant target and normal tissues, and creates a treatment plan in only a few minutes after patient simulation. Segmentation of target and critical structures is performed automatically through morphological operations on the soft tissue and was validated by comparing with manual clinical segmentation using the Dice coefficient and Hausdorff distance. The treatment plan is generated by searching a database of previous cases for patients with similar anatomy. In this search, each database case is ranked in terms of similarity using a customized metric designed for sensitivity by including only geometrical changes that affect the dose distribution. The database case with the best match is automatically modified to replace relevant patient info and isocenter position while maintaining original beam and MLC settings. Fifteen patients with marginally acceptable treatment plans were used to validate the method. In each of these cases the anatomy was accurately segmented, but the beams and MLC settings led to a suboptimal treatment plan by either underdosing the brain or excessively irradiating critical normal tissues. For each case, the anatomy was automatically segmented with the proposed method, and the automated and anual segmentations were then compared. The mean Dice coefficient was 0.97, with a standard deviation of 0.008 for the brain, 0.85 ± 0.009 for the eyes, and 0.67 ± 0.11 for the lens. The mean Euclidian distance was 0.13 ± 0.13 mm for the brain, 0.27± 0.31 for the eye, and 2.34 ± 7.23 for the lens. Each case was then subsequently matched against a database of 70 validated treatment plans and the best matching plan (termed autoplanned), was compared retrospectively with the clinical plans in terms of brain coverage and maximum doses to critical structures. Maximum doses were reduced by a maximum of 8.37 Gy for the left eye (mean 2.08), 11.67 for the right eye (1.90) and, respectively, 25.44 (5.59) for the left lens and 24.40 (4.85) for the right lens. Time to generate the autoplan, including the segmentation, was 3-4min. Automated database- based matching is an alternative to classical treatment planning that improves quality while providing a cost-effective solution to planning through modifying previous validated plans to match a current patient's anatomy.

Quantitative dosimetry for yttrium-90 radionuclide therapy: tumor dose predicts fluorodeoxyglucose positron emission tomography response in hepatic metastatic melanoma.

PURPOSE: To assess a new method for generating patient-specific volumetric dose calculations and analyze the relationship between tumor dose and positron emission tomography (PET) response after radioembolization of hepatic melanoma metastases. METHODS AND MATERIALS: Yttrium-90 ((90)Y) bremsstrahlung single photon emission computed tomography (SPECT)/computed tomography (CT) acquired after (90)Y radioembolization was convolved with published (90)Y Monte Carlo estimated dose deposition kernels to create a three-dimensional dose distribution. Dose-volume histograms were calculated for tumor volumes manually defined from magnetic resonance imaging or PET/CT imaging. Tumor response was assessed by absolute reduction in maximum standardized uptake value (SUV(max)) and total lesion glycolysis (TLG). RESULTS: Seven patients with 30 tumors treated with (90)Y for hepatic metastatic melanoma with available (90)Y SPECT/CT and PET/CT before and after treatment were identified for analysis. The median (range) for minimum, mean, and maximum dose per tumor volume was 16.9 Gy (5.7-43.5 Gy), 28.6 Gy (13.8-65.6 Gy) and 36.6 Gy (20-124 Gy), respectively. Response was assessed by fluorodeoxyglucose PET/CT at a median time after treatment of 2.8 months (range, 1.2-7.9 months). Mean tumor dose (P = .03) and the percentage of tumor volume receiving ≥ 50 Gy (P < .01) significantly predicted for decrease in tumor SUV(max), whereas maximum tumor dose predicted for decrease in tumor TLG (P < .01). CONCLUSIONS: Volumetric dose calculations showed a statistically significant association with metabolic tumor response. The significant dose-response relationship points to the clinical utility of patient-specific absorbed dose calculations for radionuclide therapy.

Prior-knowledge treatment planning for volumetric arc therapy using feature-based database mining.

Treatment planning for volumetric arc therapy (VMAT) is a lengthy process that requires many rounds of optimizations to obtain the best treatment settings and optimization constraints for a given patient's geometry. We propose a feature-selection search engine that explores previously treated cases of similar anatomy, returning the optimal plan configurations and attainable DVH constraints. Using an institutional database of 83 previously treated cases of prostate carcinoma treated with volumetric-modulated arc therapy, the search procedure first finds the optimal isocenter position with an optimization procedure, then ranks the anatomical similarity as the mean distance between targets. For the best matching plan, the planning information is reformatted to the DICOM format and imported into the treatment planning system to suggest isocenter, arc directions, MLC patterns, and optimization constraints that can be used as starting points in the optimization process. The approach was tested to create prospective treatment plans based on anatomical features that match previously treated cases from the institution database. By starting from a near-optimal solution and using previous optimization constraints, the best matching test only required simple optimization steps to further decrease target inhomogeneity, ultimately reducing time spend by the therapist in planning arcs' directions and lengths.

Multiatlas segmentation of thoracic and abdominal anatomy with level set-based local search.

Segmentation of organs at risk (OARs) remains one of the most time-consuming tasks in radiotherapy treatment planning. Atlas-based segmentation methods using single templates have emerged as a practical approach to automate the process for brain or head and neck anatomy, but pose significant challenges in regions where large interpatient variations are present. We show that significant changes are needed to autosegment thoracic and abdominal datasets by combining multi-atlas deformable registration with a level set-based local search. Segmentation is hierarchical, with a first stage detecting bulk organ location, and a second step adapting the segmentation to fine details present in the patient scan. The first stage is based on warping multiple presegmented templates to the new patient anatomy using a multimodality deformable registration algorithm able to cope with changes in scanning conditions and artifacts. These segmentations are compacted in a probabilistic map of organ shape using the STAPLE algorithm. Final segmentation is obtained by adjusting the probability map for each organ type, using customized combinations of delineation filters exploiting prior knowledge of organ characteristics. Validation is performed by comparing automated and manual segmentation using the Dice coefficient, measured at an average of 0.971 for the aorta, 0.869 for the trachea, 0.958 for the lungs, 0.788 for the heart, 0.912 for the liver, 0.884 for the kidneys, 0.888 for the vertebrae, 0.863 for the spleen, and 0.740 for the spinal cord. Accurate atlas segmentation for abdominal and thoracic regions can be achieved with the usage of a multi-atlas and perstructure refinement strategy. To improve clinical workflow and efficiency, the algorithm was embedded in a software service, applying the algorithm automatically on acquired scans without any user interaction.

Towards automated planning for unsealed source therapy.

The purpose of this study was to develop and validate a technique for unsealed source radiotherapy planning that combines the segmentation and registration tasks of single-photon emission tomography (SPECT) and computed tomography (CT) datasets. The segmentation task is automated by an atlas registration approach that takes advantage of a hybrid scheme using a diffeomorphic demons algorithm to warp a standard template to the patient's CT. To overcome the lack of common anatomical features between the CT and SPECT datasets, registration is achieved through a narrow band approach that matches liver contours in the CT with the gradients of the SPECT dataset. Deposited dose is then computed from the SPECT dataset using a convolution operation with tracer-specific deposition kernels. Automatic segmentation showed good agreement with manual contouring, measured using the dice similarity coefficient and ranging from 0.72 to 0.87 for the liver, 0.47 to 0.93 for the kidneys, and 0.74 to 0.83 for the spinal cord. The narrow band registration achieved variations of less 0.5 mm translation and 1° rotation, as measured with convergence analysis. With the proposed combined segmentation-registration technique, the uncertainty of soft-tissue target localization is greatly reduced, ensuring accurate therapy planning.

A measure to evaluate deformable registration fields in clinical settings.

Deformable registration has migrated from a research topic to a widely used clinical tool that can improve radiotherapeutic treatment accuracy by tracking anatomical changes. Although various mathematical formulations have been reported in the literature and implemented in commercial software, we lack a straightforward method to verify a given solution in routine clinical use. We propose a metric using concepts derived from vector analysis that complements the standard evaluation tools to identify unrealistic wrappings in a displacement field. At the heart of the proposed procedure is identification of vortexes in the displacement field that do not correspond to underlying anatomical changes. Vortexes are detected and their intensity quantified using the CURL operator and presented as a vortex map overlaid on the original anatomy for rapid identification of problematic regions. We show application of the proposed metric on clinical scenarios of adaptive radiotherapy and treatment response assessment, where the CURL operator quantitatively detected errors in the displacement field and identified problematic regions that were invisible to classical voxel-based evaluation methods. Unrealistic warping not visible to standard voxel-based solution assessment can produce erroneous results when the deformable solution is applied on a secondary dataset, such as dose matrix in adaptive therapy or PET data for treatment response assessment. The proposed metric for evaluating deformable registration provides increased usability and accuracy of detecting unrealistic deformable registration solutions when compared to standard intensity-based approaches. It is computationally efficient and provides a valuable platform for the clinical acceptance of image-guided radiotherapy.

Six degrees of freedom CBCT-based positioning for intracranial targets treated with frameless stereotactic radiosurgery.

Frameless radiosurgery is an attractive alternative to the framed procedure if it can be performed with comparable precision in a reasonable time frame. Here, we present a positioning approach for frameless radiosurgery based on in-room volumetric imaging coupled with an advanced six-degrees-of-freedom (6 DOF) image registration technique which avoids use of a bite block. Patient motion is restricted with a custom thermoplastic mask. Accurate positioning is achieved by registering a cone-beam CT to the planning CT scan and applying all translational and rotational shifts using a custom couch mount. System accuracy was initially verified on an anthropomorphic phantom. Isocenters of delineated targets in the phantom were computed and aligned by our system with an average accuracy of 0.2 mm, 0.3 mm, and 0.4 mm in the lateral, vertical, and longitudinal directions, respectively. The accuracy in the rotational directions was 0.1°, 0.2°, and 0.1° in the pitch, roll, and yaw, respectively. An additional test was performed using the phantom in which known shifts were introduced. Misalignments up to 10 mm and 3° in all directions/rotations were introduced in our phantom and recovered to an ideal alignment within 0.2 mm, 0.3 mm, and 0.4 mm in the lateral, vertical, and longitudinal directions, respectively, and within 0.3° in any rotational axis. These values are less than couch motion precision. Our first 28 patients with 38 targets treated over 63 fractions are analyzed in the patient positioning phase of the study. Mean error in the shifts predicted by the system were less than 0.5 mm in any translational direction and less than 0.3° in any rotation, as assessed by a confirmation CBCT scan. We conclude that accurate and efficient frameless radiosurgery positioning is achievable without the need for a bite block by using our 6DOF registration method. This system is inexpensive compared to a couch-based 6 DOF system, improves patient comfort compared to systems that utilize a bite block, and is ideal for the treatment of pediatric patients with or without general anesthesia, as well as of patients with dental issues. From this study, it is clear that only adjusting for 4 DOF may, in some cases, lead to significant compromise in PTV coverage. Since performing the additional match with 6 DOF in our registration system only adds a relatively short amount of time to the overall process, we advocate making the precise match in all cases.

Dosimetric effects of manual cone-beam CT (CBCT) matching for spinal radiosurgery: our experience.

Radiosurgical treatment of cranial or extracranial targets demands accurate positioning of the isocenter at the beam and table isocenter, and immobilization of the target during treatment. For spinal radiosurgery, the standard approach involves matching of cone-beam CT (CBCT) in-room images with the planning CT (pCT) to determine translation and yaw corrections. The purpose of this study was to assess the accuracy of these techniques compared to advanced automatching using mutual information metrics, with consideration given to volume of interest (VOI) and optimizing translations and rotations in all axes. The dosimetric consequences of our current standard matching techniques were also evaluated. Ten consecutive spinal radiosurgery patients treated in the last year were subjected to analysis. For purposes of this analysis, the automatch using mutual information and a VOI was considered to create "the true isocenter" for positioning the patients. Review of the imaging from this automatch confirmed perfect superimposition of the two datasets within the VOI. Matching the CBCT to the pCT using the automatch allowed assessment of the rotations which had been previously ignored. Recalculation of the dose volume histogram was undertaken for each patient, assuming displacement of the true isocenter to the treated isocenter. Comparisons between the delivered doses and the intended doses were made. The mean absolute lateral/vertical/longitudinal translations and vector displacement between the manual CBCT-pCT matching isocenter and the true isocenter were 0.13, -0.05, and -0.39 mm, with a minimum and maximum individual pixel vector shift of 3.2 and 8.94 mm. The mean pitch, yaw, and roll correction for automatch was -0.30°, 0.25°, and 0.97° with a maximum of 1.65°, 2.92°, and 1.43°. Four of ten patients had a significant change in the coverage of the tumor due to lack of correction of translational and rotational errors. The largest errors were observed in patients with small and irregular target volumes. Our initial results show that precise positioning for spinal radiosurgery cannot be accomplished with manual pCT-CBCT matching without a clinical strategy to compensate for rotations. In the absence of this, significant underdosing of the tumor may occur.

Personalizing Radiotherapy Prescription Dose Using Genomic Markers of Radiosensitivity and Normal Tissue Toxicity in NSCLC.

INTRODUCTION: Cancer sequencing efforts have revealed that cancer is the most complex and heterogeneous disease that affects humans. However, radiation therapy (RT), one of the most common cancer treatments, is prescribed on the basis of an empirical one-size-fits-all approach. We propose that the field of radiation oncology is operating under an outdated null hypothesis: that all patients are biologically similar and should uniformly respond to the same dose of radiation. METHODS: We have previously developed the genomic-adjusted radiation dose, a method that accounts for biological heterogeneity and can be used to predict optimal RT dose for an individual patient. In this article, we use genomic-adjusted radiation dose to characterize the biological imprecision of one-size-fits-all RT dosing schemes that result in both over- and under-dosing for most patients treated with RT. To elucidate this inefficiency, and therefore the opportunity for improvement using a personalized dosing scheme, we develop a patient-specific competing hazards style mathematical model combining the canonical equations for tumor control probability and normal tissue complication probability. This model simultaneously optimizes tumor control and toxicity by personalizing RT dose using patient-specific genomics. RESULTS: Using data from two prospectively collected cohorts of patients with NSCLC, we validate the competing hazards model by revealing that it predicts the results of RTOG 0617. We report how the failure of RTOG 0617 can be explained by the biological imprecision of empirical uniform dose escalation which results in 80% of patients being overexposed to normal tissue toxicity without potential tumor control benefit. CONCLUSIONS: Our data reveal a tapestry of radiosensitivity heterogeneity, provide a biological framework that explains the failure of empirical RT dose escalation, and quantify the opportunity to improve clinical outcomes in lung cancer by incorporating genomics into RT.

MR-based attenuation correction for hybrid PET-MR brain imaging systems using deformable image registration.

PURPOSE: Realization of combined positron emission tomography (PET)--magnetic resonance (MR) scanners has the potential to significantly change healthcare and revolutionize clinical practice as it allows, simultaneously, visualization of molecular imaging and anatomical imaging. PET-MR, acquired in one imaging study, will likely become the advanced imaging modality of choice for neurological studies, certain forms of cancer, stroke, and the emerging study of stem cell therapy. A challenge toward the implementation and operation of combined PET-MR scanners is that attenuation corrections maps are not directly available due to space and cost constraints. This article presents a method to obtain accurate patient-specific PET attenuation coefficients maps in head imaging by warping an atlas computed tomography (CT) data set to the patient-specific MR data set using a deformable registration model. METHODS: A multimodality optical flow deformable model has been developed that establishes a voxel-to-voxel correspondence between the CT atlas and patient MR images. Once the mapping is established, the atlas is warped with the deformation field obtained by the registration to create a simulated CT image study that matches the patient anatomy, which could be used for attenuation correction. RESULTS: To evaluate the accuracy of the deformable-based attenuation correction, 17 clinical brain tumor cases were studied using acquired MR-CT images. A simulated CT was compared to the patient's true CT to assess geometrical accuracy of the deformation module as well as voxel-to-voxel comparison of Hounsfield units (HUs). In all cases, mapping from the atlas CT to the individual MR was achieved with geometrical accuracy as judged using quantitative inspection tools. The mean distance between simulated and true CT external contour and bony anatomy was 1.26 and 2.15 mm, respectively. In terms of HU unit comparison, the mean voxel-to-voxel difference was less than 2 HU for all cases. CONCLUSIONS: Attenuation correction for hybrid PET-MR scanners was easily achieved by individualizing an atlas CT to the MR data set using a deformable model without requiring user interaction. The method provided clinical accuracy while eliminating the need for an additional CT scan for PET attenuation correction.

Dosimetric performance of the new high-definition multileaf collimator for intracranial stereotactic radiosurgery.

The objective was to evaluate the performance of a high-definition multileaf collimator (MLC) of 2.5 mm leaf width (MLC2.5) and compare to standard 5 mm leaf width MLC (MLC5) for the treatment of intracranial lesions using dynamic conformal arcs (DCA) technique with a dedicated radiosurgery linear accelerator. Simulated cases of spherical targets were created to study solely the effect of target volume size on the performance of the two MLC systems independent of target shape complexity. In addition, 43 patients previously treated for intracranial lesions in our institution were retrospectively planned using DCA technique with MLC2.5 and MLC5 systems. The gross tumor volume ranged from 0.07 to 40.57 cm3 with an average volume of 5.9 cm3. All treatment parameters were kept the same for both MLC-based plans. The plan evaluation was performed using figures of merits (FOM) for a rapid and objective assessment on the quality of the two treatment plans for MLC2.5 and MLC5. The prescription isodose surface was selected as the greatest isodose surface covering >or= 95% of the target volume and delivering 95% of the prescription dose to 99% of target volume. A Conformity Index (CI) and conformity distance index (CDI) were used to quantifying the dose conformity to a target volume. To assess normal tissue sparing, a normal tissue difference (NTD) was defined as the difference between the volume of normal tissue receiving a certain dose utilizing MLC5 and the volume receiving the same dose using MLC2.5. The CI and normal tissue sparing for the simulated spherical targets were better with the MLC2.5 as compared to MLC5. For the clinical patients, the CI and CDI results indicated that the MLC2.5 provides better treatment conformity than MLC5 even at large target volumes. The CI's range was 1.15 to 2.44 with a median of 1.59 for MLC2.5 compared to 1.60-2.85 with a median of 1.71 for MLC5. Improved normal tissue sparing was also observed for MLC2.5 over MLC5, with the NTD always positive, indicating improvement, and ranging from 0.1 to 8.3 for normal tissue receiving 50% (NTV50), 70% (NTV70) and 90% (NTV90) of the prescription dose. The MLC2.5 has a dosimetric advantage over the MLC5 in Linac-based radiosurgery using DCA method for intracranial lesions, both in treatment conformity and normal tissue sparing when target shape complexity increases.

Patient-specific quality assurance method for VMAT treatment delivery.

Volumetric modulated arc therapy (VMAT) is a system for intensity-modulated radiotherapy treatment delivery that achieves high dose conformality by optimizing the dose rate, gantry speed, and the leaf positions of the dynamic multileaf collimator (DMLC). The aim of this work is to present a practical approach for patient-specific volumetric reconstruction of the dose delivered of a VMAT treatment using the DMLC and treatment controller log (Dynalog) files. The accuracy of VMAT delivery was analyzed for five prostate patients. For each patient, a clinical treatment was delivered and values recorded in the log files for the gantry angle, dose rate, and leaf positions were converted to a new DICOM-compliant plan using a custom-developed software system. The plan was imported in a treatment planning system and the dose distribution was recreated on the original CT by simply recomputing the dose. Using the standard evaluation tools, it is straightforward to assess if reconstructed dose meets clinical endpoints, as well as to compare side-by-side reconstructed and original plans. The study showed that log files can be directly used for dose reconstruction without resorting to phantom measurements or setups. In all cases, analysis of the leaf positions showed a maximum error of -0.26 mm (mean of 0.15 mm). Gantry angle deviation was less than 1degree and the total MU was within 0.5 from the planned value. Differences between the reconstructed and the intended dose matrices were less than 1.46% for all cases. Measurements using the MATRIXX system in a phantom were used to validate the dosimetric accuracy of the proposed method, with an agreement of at least 96% in all pixels as measured using the gamma index. The methodology provides a volumetric evaluation of the dose reconstructed by VMAT plans which is easily achieved by automated analysis of Dynalog files without additional measurements or phantom setups. This process provides a valuable platform for adaptive therapy in the future.

Automated quality assurance for image-guided radiation therapy.

The use of image-guided patient positioning requires fast and reliable Quality Assurance (QA) methods to ensure the megavoltage (MV) treatment beam coincides with the integrated kilovoltage (kV) or volumetric cone-beam CT (CBCT) imaging and guidance systems. Current QA protocol is based on visually observing deviations of certain features in acquired kV in-room treatment images such as markers, distances, or HU values from phantom specifications. This is a time-consuming and subjective task because these features are identified by human operators. The method implemented in this study automated an IGRT QA protocol by using specific image processing algorithms that rigorously detected phantom features and performed all measurements involved in a classical QA protocol. The algorithm was tested on four different IGRT QA phantoms. Image analysis algorithms were able to detect QA features with the same accuracy as the manual approach but significantly faster. All described tests were performed in a single procedure, with acquisition of the images taking approximately 5 minutes, and the automated software analysis taking less than 1 minute. The study showed that the automated image analysis based procedure may be used as a daily QA procedure because it is completely automated and uses a single phantom setup.

Performance evaluation of Calypso 4D localization and kilovoltage image guidance systems for interfraction motion management of prostate patients.

Prostate cancer represents a model site for advances in understanding inter- and intrafraction motion for radiotherapy. In this study, we examined the correlation of the electromagnetic transponder system/Calypso 4D Localization System with conventional on-board imaging (OBI) using kilovoltage imaging. Initially using a quality assurance (QA) phantom and subsequently using data of seven patients, the vector distances between Calypso- and OBI-recorded shifts were compared using the t-test. For the 30 phantom measurements, the average differences between the measured Calypso offset and the calculated OBI shift were 0.4 +/- 0.4, 0.2 +/- 0.3, and 0.4 +/- 0.3 mm in the lateral, longitudinal, and vertical directions, respectively (p = 0.73, p = 0.91, and p = 0.99, respectively), and the average difference vector for all sessions was 0.8 +/- 0.4 mm. For the 259 patient measurements, the average differences between the measured Calypso offset and the calculated OBI shift were 0.7 +/- 0.5, 1.1 +/- 0.9, and 1.2 +/- 0.9 mm in the lateral, longitudinal, and vertical directions, respectively (p = 0.45, p = 0.28, and p = 0.56, respectively), and the average difference vector for all sessions was 2.1 +/- 1.0 mm. Our results demonstrated good correlation between Calypso and OBI. While other studies have explored the issue of Calypso/OBI correlation, our analysis is unique in our use of phantom validation and in our performing the patient analysis on an initial population prior to routine setup using Calypso without OBI. Implications for Calypso's role as a QA tool are discussed.

A registration based approach for 4D cardiac micro-CT using combined prospective and retrospective gating.

Recent advances in murine cardiac studies with three-dimensional cone beam micro-computed tomography (CT) have used either prospective or retrospective gating technique. While prospective gating ensures the best image quality and the highest resolution, it involves longer sampling times and higher radiation dose. Sampling is faster and the radiation dose can be reduced with retrospective gating but the image quality is affected by the limited number of projections with an irregular angular distribution which complicate the reconstruction process, causing significant streaking artifacts. This work involves both prospective and retrospective gating in sampling. Deformable registration is used between a high quality image set acquired with prospective gating with the multiple data sets during the cardiac cycle obtained using retrospective gating. Tests were conducted on a four-dimensional (4D) cardiac mouse phantom and after optimization, the method was applied to in vivo cardiac micro-CT data. Results indicate that, by using our method, the sampling time can be reduced by a factor of 2.5 and the radiation dose can be reduced 35% compared to the prospective sampling while the image quality can be maintained. In conclusion, we proposed a novel solution to 4D cine cardiac micro-CT based on a combined prospective with retrospective gating in sampling and deformable registration post reconstruction that mixed the advantages of both strategies.

PET-CT fusion in radiation management of patients with anorectal tumors.

PURPOSE: To compare computed tomography (CT) with positron emission tomography-CT (PET-CT) scans with respect to anorectal tumor volumes, correlation in overlap, and influence on radiation treatment fields and patient care. PATIENTS AND METHODS: From March to November 2003, 20 patients with rectal cancer and 3 patients with anal cancer were treated with preoperative or definitive chemoradiation, respectively. Computed tomography simulation data generated a CT gross tumor volume (CT-GTV) and CT planning target volume (CT-PTV) and (18)F-fluoro-2-deoxy-glucose PET (FDG-PET) created a PET-GTV and PET-PTV. The PET-CT and CT images were fused using manual coregistration. Patients were treated with three-dimensional conformal therapy to traditional doses. The PET, CT, and overlap volumes (OVs) were measured in cubic centimeters. RESULTS: Mean PET-GTV was smaller than the mean CT-GTV (91.7 vs. 99.6 cm(3)). The mean OV was 46.7%. As tumor volume increased, PET and CT OV correlated significantly (p < 0.001). In 17% of patients PET-CT altered the PTV, and in 26% it changed the radiation treatment plan. For 25% of patients with rectal cancer, PET detected distant metastases and changed overall management. Ten rectal cancer patients underwent surgery. When the pretreatment PET standardized uptake value was >10 and the posttreatment PET standardized uptake value was <6, 100% achieved pathologic downstaging (p = 0.047). CONCLUSIONS: Variation in volume was significant, with 17% and 26% of patients requiring a change in treatment fields and patient management, respectively. Positron emission tomography can change the management for anorectal tumors by early detection of metastatic disease or disease outside standard radiation fields.

Quantitative evaluation of a cone-beam computed tomography-planning computed tomography deformable image registration method for adaptive radiation therapy.

Deformable (non-rigid) registration is an essential tool in both adaptive radiation therapy and image-guided radiation therapy to account for soft-tissue changes during the course of treatment. The evaluation method most commonly used to assess the accuracy of deformable image registration is qualitative human evaluation. Here,we propose a method for systematically measuring the accuracy of an algorithm in recovering artificially introduced deformations in cases of rigid geometry, and we use that method to quantify the ability of a modified basis spline (B-Spline) registration algorithm to recover artificially introduced deformations. The evaluation method is entirely computer-driven and eliminates biased interpretation associated with human evaluation; it can be applied to any chosen method of image registration. Our method involves using planning computed tomography (PCT) images acquired with a conventional CT simulator and cone-beam computed tomography (CBCT) images acquired daily by a linear accelerator-mounted kilovoltage image system in the treatment delivery room. The deformation that occurs between the PCT and daily CBCT images is obtained using a modified version of the B-Spline deformable model designed to overcome the low soft-tissue contrast and the artifacts and distortions observed in CBCT images. Clinical CBCT images and contours of phantom and central nervous system cases were deformed (warped) with known random deformations. In registering the deformed with the non-deformed image sets, we tracked the algorithm's ability to recover the original, non-deformed set. Registration error was measured as the mean and maximum difference between the original and the registered surface contours from outlined structures. Using this approach, two sets of tests can be devised. To measure the residual error related to the optimizer's convergence performance, the warped CBCT image is registered to the unwarped version of itself, eliminating unknown factors such as noise and positioning errors. To study additional errors introduced by artifacts and noise in the CBCT image, the warped CBCT image is registered to the original PCT image. Using a B-Spline deformable image registration algorithm, mean residual error introduced by the algorithm's performance on noise-free images was less than 1 mm, with a maximum of 2 mm. The chosen deformable image registration model was capable of accommodating significant variability in structures over time, because the artificially introduced deformation magnitude did not significantly influence the residual error. On the second type of test, noise and artifacts reduced registration accuracy to a mean of 1.33 mm and a maximum of 4.86 mm.The accuracy of deformable image registration can be easily and consistently measured by evaluating the algorithm's ability to recover artificially introduced deformations in rigid cases in which the true solution is known a priori. The method is completely automated, applicable to any chosen registration algorithm, and does not require user interaction of any kind.