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 We propose that the field of radiation oncology is operating under an outdated null hypothesis: that all patients are biologically similar and should uniformly respond to the same dose of radiation.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.

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 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.

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.

MRI-based computed tomography metal artifact correction method for improving proton range calculation accuracy.

PURPOSE: Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. METHODS AND MATERIALS: The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR. Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. RESULTS: The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. CONCLUSIONS: Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts.

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.

Locoregional tumor failure after definitive radiation for patients with stage III non-small cell lung cancer.

BACKGROUND: Locoregional tumor failure (LRF) after definitive chemoradiation for patients with stage III NSCLC remains unacceptably high. This analysis sought to further define where LRF occurs relative to radiation dose received and pre-treatment PET scan-defined maximum standard uptake value (SUVmax). METHODS: This was a retrospective study analyzing patients with stage III NSCLC treated with definitive radiation between 2006 and 2011. LRF was defined as failure within the ipsilateral lung, hilum or mediastinum. The CT simulation scan with the radiation dose distribution was registered to the CT or PET/CT documenting LRF. The region of LRF was contoured, and the dose to 95% of the volume (D95) of LRF was extracted. The pre-treatment SUVmax was also extracted for the anatomic region of LRF. RESULTS: Sixty-one patients were identified. Median follow-up time was 19.1 months (range 2.37-76.33). Seventy four percent of patients were treated with 3-D conformal technique (3DCRT), 15% were treated with Intensity Modulated Radiotherapy (IMRT), and 11% were treated with a combination of 3DCRT and IMRT. Median prescribed radiation dose for all patients was 66 Gy (39.6-74). Concurrent chemotherapy was delivered in 90% of patients. Twenty-two patients (36%) developed a LRF, with a total of 39 anatomic regions of LRF identified. Median time to LRF was 11.4 months (3.5-44.6). Failures were distributed as follows: 36% were in-field failures, 27% were out-of-field failures, 18% were in-field and out-of-field failures, and 18% were in-field and marginal (recurrences within the field edge) failures. There were no isolated marginal failures. Of the patients that developed a LRF, 73% developed a LRF with an in-field component. Sixty-two percent of LRFs were nodal. The median pre-treatment SUVmax for the anatomic region of LRF for patients with an in-field failure was 13. The median D95 of in-field LRF was 63 Gy. CONCLUSIONS: LRF after definitive chemoradiation are comprised primarily of in-field failures, though out-of field failures are not insignificant. Marginal failures are rare, indicating field margins are appropriate. Although radiation dose escalation to standard radiation fields has not yielded success, using PET parameters to define high-risk regions remains worthy of further investigation.

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.

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.

Four-dimensional (4D) motion detection to correct respiratory effects in treatment response assessment using molecular imaging biomarkers.

Observing early metabolic changes in positron emission tomography (PET) is an essential tool to assess treatment efficiency in radiotherapy. However, for thoracic regions, the use of three-dimensional (3D) PET imaging is unfeasible because the radiotracer activity is smeared by the respiratory motion and averaged during the imaging acquisition process. This motion-induced degradation is similar in magnitude with the treatment-induced changes, and the two occurrences become indiscernible. We present a customized temporal-spatial deformable registration method for quantifying respiratory motion in a four-dimensional (4D) PET dataset. Once the motion is quantified, a motion-corrected (MC) dataset is created by tracking voxels to eliminate breathing-induced changes in the 4D imaging scan. The 4D voxel-tracking data is then summed to yield a 3D MC-PET scan containing only treatment-induced changes. This proof of concept is exemplified on both phantom and clinical data, where the proposed algorithm tracked the trajectories of individual points through the 4D datasets reducing motion to less than 4 mm in all phases. This correction approach using deformable registration can discern motion blurring from treatment-induced changes in treatment response assessment using PET imaging.

Characterization of primary prostate carcinoma by anti-1-amino-2-[(18)F] -fluorocyclobutane-1-carboxylic acid (anti-3-[(18)F] FACBC) uptake.

Anti-1-amino-3-[(18)F] fluorocyclobutane-1-carboxylic acid (anti-3-[(18)F] FACBC) is a synthetic amino acid positron emission tomography (PET) radiotracer with utility in the detection of recurrent prostate carcinoma. The aim of this study is to correlate uptake of anti-3-[(18)F] FACBC with histology of prostatectomy specimens in patients undergoing radical prostatectomy and to determine if uptake correlates to markers of tumor aggressiveness such as Gleason score. Ten patients with prostate carcinoma pre-radical prostatectomy underwent 45 minute dynamic PET-CT of the pelvis after IV injection of 347.8 ± 81.4 MBq anti-3-[(18)F] FACBC. Each prostate was co-registered to a separately acquired MR, divided into 12 sextants, and analyzed visually for abnormal focal uptake at 4, 16, 28, and 40 min post-injection by a single reader blinded to histology. SUVmax per sextant and total sextant activity (TSA) was also calculated. Histology and Gleason scores were similarly recorded by a urologic pathologist blinded to imaging. Imaging and histologic analysis were then compared. In addition, 3 representative sextants from each prostate were chosen based on highest, lowest and median SUVmax for immunohistochemical (IHC) analysis of Ki67, synaptophysin, P504s, chromogranin A, P53, androgen receptor, and prostein. 79 sextants had malignancy and 41 were benign. Highest combined sensitivity and specificity was at 28 min by visual analysis; 81.3% and 50.0% respectively. SUVmax was significantly higher (p<0.05) for malignant sextants (5.1±2.6 at 4 min; 4.5±1.6 at 16 min; 4.0±1.3 at 28 min; 3.8±1.0 at 40 min) compared to non-malignant sextants (4.0±1.9 at 4 min; 3.5±0.8 at 16 min; 3.4±0.9 at 28 min; 3.3±0.9 at 40 min), though there was overlap of activity between malignant and non-malignant sextants. SUVmax also significantly correlated (p<0.05) with Gleason score at all time points (r=0.28 at 4 min; r=0.42 at 16 min; r=0.46 at 28 min; r=0.48 at 40 min). There was no significant correlation of anti-3-[(18)F] FACBC SUVmax with Ki-67 or other IHC markers. Since there was no distinct separation between malignant and non-malignant sextants or between Gleason score levels, we believe that anti-3-[(18)F] FACBC PET should not be used alone for radiation therapy planning but may be useful to guide biopsy to the most aggressive lesion.

Voxel clustering for quantifying PET-based treatment response assessment.

PURPOSE: Imaging biomarkers are crucial in managing treatment options for cancer patients. They are extremely powerful tools since they allow personalized treatment assessment early during therapy by using repeated imaging to detect and quantify tumor response. Currently, treatment response assessment from consecutive imaging is measured by simple global measures that do not capture a tumor's heterogeneous response. The authors present an automated, multivoxel metric that groups voxels into clusters of changes for a local definition of radiation treatment efficiency from multiple PET imaging studies acquired at different time periods for assessing therapeutic response. METHODS: The algorithm employs level-set mathematics to extract changing features to classify voxels into response patterns. First, pretreatment and post-treatment PET images were aligned using a deformable registration to correct for posture and soft tissue changes. The detailed mapping was modeled by free form deformations B-spline optimized using the limited memory L-BFGS algorithm. The posture-corrected datasets are then subtracted to produce an image of molecular changes embedded with noise. Once images were aligned and subtracted, a segmentation algorithm combining the concepts of voxel and distance-based techniques classified voxels into patterns of signal reduction or enhancement. Although signal reduction is evidence of successful treatment, signal-enhancing regions are an indication of treatment failure. For an in depth analysis of potential treatment errors, patterns of signal enhancement were correlated with the radiation treatment dose and anatomical structures from the treatment plan using image registration methods. RESULTS: The algorithm was retrospectively applied to PET∕CT and radiotherapy (RT) oncology data from an NCI-sponsored clinical trial (81 clinical cases from RTOG 0522 Trial) for combined drug and radiation therapy in head and neck carcinomas. This clinical trial dataset presented a realistic environment for implementing and validating our algorithm to correlate local response as observed in serial PET with delivered dose. The technique was instrumental in detecting geographical and segmentation misses on the actual clinical cases by providing accurate voxel-by-voxel analysis of metabolic changes. Results of the level-set based clustering algorithm are saved as a detailed report of enhancing∕nonenhancing regions and their location, and can be further displayed as a colorwash laid over the original anatomy for in depth analysis. CONCLUSIONS: The automated technique was instrumental in analyzing treatment response in the clinical cases and provided an useful tool for accurate, outcome-based response assessment of the radiation treatment process. The developed method is general and should be extendable to other high-resolution diagnostic imaging with minor modifications.

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.

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.

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.

Current and future directions in frailty research.

The concept of frailty has been evolving dramatically for the past 30 years. Through its evolution, a variety of single and multidimensional models have been used to describe frailty. This article reviews the current literature related to the defining dimensions of frailty and identifies the gaps in the literature requiring additional research. A detailed literature review was performed to identify key dimensions and models currently being used to define frailty, classify interventions that have been developed to reverse frailty, and identify potential areas for future research within this field. Despite the large body of research defining the dimensions of frailty, no consensus exists on a comprehensive, operational definition. A standardized definition will be critical to design effective interventions at earlier stages along the continuum of frailty and interpret findings from evaluation studies. Identified gaps in the literature include studies supporting the utility of expanding the definition of frailty to incorporate social determinants, studies evaluating the role of obesity in the development of frailty, and the need for longitudinal studies for defining the pathways to developing frailty. This review highlights the need for an accurate definition of frailty and for longitudinal research to explore the development of frailty and evaluate the effectiveness of the frailty reversal interventions that may avert or delay adverse outcomes within this susceptible population. These future research needs are discussed within the context of the growing pressures to bring down health care costs, and the role of comparative effectiveness research and cost-effectiveness research in identifying interventions with the potential to help slow the growth of health care spending among the elderly.

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.

Technical Aspects of PET/CT-Based Radiotherapy Planning.

PET/computed tomography (CT) has been used for both diagnosis/ staging of cancer and guiding the cancer treatment planning process. PET-guided radiotherapy (RT) planning has been increasingly used to assist in determining the tumor locations so that therapy procedures can be focused on the tumor, minimizing damage to the surrounding tissue. However, incorporating PET/CT into the treatment planning process raises challenges in areas of immobilization, image registration, and target volume segmentation. This article focuses on the technical aspects of integrating PET/CT into radiotherapy planning and presents a general overview of the clinical workflow and challenges involved in the planning.