Accurate, repeatable, and geometrically precise diffusion-weighted imaging on a 0.35 T magnetic resonance imaging-guided linear accelerator.

Background and purpose: Diffusion weighted imaging (DWI) allows for the interrogation of tissue cellularity, which is a surrogate for cellular proliferation. Previous attempts to incorporate DWI into the workflow of a 0.35 T MR-linac (MRL) have lacked quantitative accuracy. In this study, accuracy, repeatability, and geometric precision of apparent diffusion coefficient (ADC) maps produced using an echo planar imaging (EPI)-based DWI protocol on the MRL system is illustrated, and in vivo potential for longitudinal patient imaging is demonstrated. Materials and methods: Accuracy and repeatability were assessed by measuring ADC values in a diffusion phantom at three timepoints and comparing to reference ADC values. System-dependent geometric distortion was quantified by measuring the distance between 93 pairs of phantom features on ADC maps acquired on a 0.35 T MRL and a 3.0 T diagnostic scanner and comparing to spatially precise CT images. Additionally, for five sarcoma patients receiving radiotherapy on the MRL, same-day in vivo ADC maps were acquired on both systems, one of which at multiple timepoints. Results: Phantom ADC quantification was accurate on the 0.35 T MRL with significant discrepancies only seen at high ADC. Average geometric distortions were 0.35 (±0.02) mm and 0.85 (±0.02) mm in the central slice and 0.66 (±0.04) mm and 2.14 (±0.07) mm at 5.4 cm off-center for the MRL and diagnostic system, respectively. In the sarcoma patients, a mean pretreatment ADC of 910x10-6 (±100x10-6) mm2/s was measured on the MRL. Conclusions: The acquisition of accurate, repeatable, and geometrically precise ADC maps is possible at 0.35 T with an EPI approach.

The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors.

BACKGROUND: We aimed to determine the prognostic value of an immunoscore reflecting CD3+ and CD8+ T cell density estimated from real-world transcriptomic data of a patient cohort with advanced malignancies treated with immune checkpoint inhibitors (ICIs) in an effort to validate a reference for future machine learning-based biomarker development. METHODS: Transcriptomic data was collected under the Total Cancer Care Protocol (NCT03977402) Avatar® project. The real-world immunoscore for each patient was calculated based on the estimated densities of tumor CD3+ and CD8+ T cells utilizing CIBERSORTx and the LM22 gene signature matrix. Then, the immunoscore association with overall survival (OS) was estimated using Cox regression and analyzed using Kaplan-Meier curves. The OS predictions were assessed using Harrell's concordance index (C-index). The Youden index was used to identify the optimal cut-off point. Statistical significance was assessed using the log-rank test. RESULTS: Our study encompassed 522 patients with four cancer types. The median duration to death was 10.5 months for the 275 participants who encountered an event. For the entire cohort, the results demonstrated that transcriptomics-based immunoscore could significantly predict patients at risk of death (p-value < 0.001). Notably, patients with an intermediate-high immunoscore achieved better OS than those with a low immunoscore. In subgroup analysis, the prediction of OS was significant for melanoma and head and neck cancer patients but did not reach significance in the non-small cell lung cancer or renal cell carcinoma cohorts. CONCLUSIONS: Calculating CD3+ and CD8+ T cell immunoscore using real-world transcriptomic data represents a promising signature for estimating OS with ICIs and can be used as a reference for future machine learning-based biomarker development.

Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration.

Multiomics data including imaging radiomics and various types of molecular biomarkers have been increasingly investigated for better diagnosis and therapy in the era of precision oncology. Artificial intelligence (AI) including machine learning (ML) and deep learning (DL) techniques combined with the exponential growth of multiomics data may have great potential to revolutionize cancer subtyping, risk stratification, prognostication, prediction and clinical decision-making. In this article, we first present different categories of multiomics data and their roles in diagnosis and therapy. Second, AI-based data fusion methods and modeling methods as well as different validation schemes are illustrated. Third, the applications and examples of multiomics research in oncology are demonstrated. Finally, the challenges regarding the heterogeneity data set, availability of omics data, and validation of the research are discussed. The transition of multiomics research to real clinics still requires consistent efforts in standardizing omics data collection and analysis, building computational infrastructure for data sharing and storing, developing advanced methods to improve data fusion and interpretability, and ultimately, conducting large-scale prospective clinical trials to fill the gap between study findings and clinical benefits.

Enhanced immune activation within the tumor microenvironment and circulation of female high-risk melanoma patients and improved survival with adjuvant CTLA4 blockade compared to males.

BACKGROUND: We hypothesized that a gender difference in clinical response may exist to adjuvant CTLA4 blockade with ipilimumab versus high-dose IFNα (HDI). We investigated differences in candidate immune biomarkers in the circulation and tumor microenvironment (TME). PATIENTS AND METHODS: This gender-based analysis was nested within the E1609 trial that tested adjuvant therapy with ipilimumab 3 mg/kg (ipi3) and 10 mg/kg (ipi10) versus HDI in high risk resected melanoma. We investigated gender differences in treatment efficacy with ipi3 and ipi10 versus HDI while adjusting for age, stage, ECOG performance (PS), ulceration, primary tumor status and lymph node number. Forest plots were created to compare overall survival (OS) and relapse free survival (RFS) between ipi and HDI. Gene expression profiling (GEP) was performed on tumors of 718 (454 male, 264 female) patients. Similarly, serum and peripheral blood mononuclear cells (PBMC) samples were tested for soluble and cellular biomarkers (N = 321 patients; 109 female and 212 male). RESULTS: The subgroups of female, stage IIIC, PS = 1, ulcerated primary, in-transit metastasis demonstrated significant improvement in RFS and/or OS with ipi3 versus HDI. Female gender was significant for both OS and RFS and was further explored. In the RFS comparison, a multivariate Cox regression model including significant variables indicated a significant interaction between gender and treatment (P = 0.024). In peripheral blood, percentages of CD3+ T cells (P = 0.024) and CD3+ CD4+ helper T cells (P = 0.0001) were higher in females compared to males. Trends toward higher circulating levels of IL1ß (P = 0.07) and IL6 (P = 0.06) were also found in females. Males had higher percentages of monocytes (P = 0.03) with trends toward higher percentages of regulatory T cells (T-reg). Tumor GEP analysis supported enhanced infiltration with immune cells including gammadelta T cells (P = 0.005), NK cells (P = 0.01), dendritic cells (P = 0.01), CD4+ T cells (P = 0.03), CD8+ T cells (P = 0.03) and T-reg (P = 0.008) in the tumors of females compared to males and a higher T-effector and IFNγ gene signature score (P = 0.0244). CONCLUSION: Female gender was associated with adjuvant CTLA4 blockade clinical benefits and female patients were more likely to have evidence of type1 immune activation within the TME and the circulation. Trial registration ClinicalTrials.gov NCT01274338. Registered 11 January 2011, https://www. CLINICALTRIALS: gov/ct2/show/NCT01274338.

Improved prognosis and evidence of enhanced immunogenicity in tumor and circulation of high-risk melanoma patients with unknown primary.

BACKGROUND: Melanoma of unknown primary (MUP) represents a poorly understood group of patients both clinically and immunologically. We investigated differences in prognosis and candidate immune biomarkers in patients with unknown compared with those with known primary melanoma enrolled in the E1609 adjuvant trial that tested ipilimumab at 3 and 10 mg/kg vs high-dose interferon-alfa (HDI). PATIENTS AND METHODS: MUP status was defined as initial presentation with cutaneous, nodal or distant metastasis without a known primary. Relapse-free survival (RFS) and overall survival (OS) rates were estimated by the Kaplan-Meier method. Stratified (by stage) log-rank test was used to compare RFS and OS by primary tumor status. Gene expression profiling (GEP) was performed on the tumor biopsies of a subset of patients. Similarly, peripheral blood samples were tested for candidate soluble and cellular immune biomarkers. RESULTS: MUP cases represented 12.8% of the total population (N=1699) including 11.7% on the ipilimumab arms and 14.7% on the HDI arm. Stratifying by stage, RFS (p=0.001) and overall survival (OS) (p=0.009) showed outcomes significantly better for patients with unknown primary. The primary tumor status remained prognostically significant after adjusting for treatment and stage in multivariate Cox proportional hazards models. Including only ipilimumab-treated patients, RFS (p=0.005) and OS (p=0.023) were significantly better in favor of those with unknown primary. Among patients with GEP data (n=718; 102 MUP, 616 known), GEP identified pathways and genes related to autoimmunity, inflammation, immune cell infiltration and immune activation that were significantly enriched in the MUP tumors compared with known primaries. Further investigation into infiltrating immune cell types estimated significant enrichment with CD8 +and CD4+T cells, B cells and NK cells as well as significantly higher major histocompatibility complex (MHC)-I and MHC-II scores in MUP compared with known primary. Among patients tested for circulating biomarkers (n=321; 66 unknown and 255 known), patients with MUP had significantly higher circulating levels of IL-2R (p=0.04). CONCLUSION: Patients with MUP and high-risk melanoma had significantly better prognosis and evidence of significantly enhanced immune activation within the TME and the circulation, supporting the designation of MUP as a distinct prognostic marker in patients with high-risk melanoma.

Local Control After Stereotactic Body Radiation Therapy for Stage I Non-Small Cell Lung Cancer.

PURPOSE: Numerous dose and fractionation schedules have been used to treat medically inoperable stage I non-small cell lung cancer (NSCLC) with stereotactic body radiation therapy (SBRT) or stereotactic ablative radiation therapy. We evaluated published experiences with SBRT to determine local control (LC) rates as a function of SBRT dose. METHODS AND MATERIALS: One hundred sixty published articles reporting LC rates after SBRT for stage I NSCLC were identified. Quality of the series was assessed by evaluating the number of patients in the study, homogeneity of the dose regimen, length of follow-up time, and reporting of LC. Clinical data including 1, 2, 3, and 5-year tumor control probabilities for stages T1, T2, and combined T1 and T2 as a function of the biological effective dose were fitted to the linear quadratic, universal survival curve, and regrowth models. RESULTS: Forty-six studies met inclusion criteria. As measured by the goodness of fit χ2/ndf, with ndf as the number of degrees of freedom, none of the models were ideal fits for the data. Of the 3 models, the regrowth model provides the best fit to the clinical data. For the regrowth model, the fitting yielded an α-to-ß ratio of approximately 25 Gy for T1 tumors, 19 Gy for T2 tumors, and 21 Gy for T1 and T2 combined. To achieve the maximal LC rate, the predicted physical dose schemes when prescribed at the periphery of the planning target volume are 43 ± 1 Gy in 3 fractions, 47 ± 1 Gy in 4 fractions, and 50 ± 1 Gy in 5 fractions for combined T1 and T2 tumors. CONCLUSIONS: Early-stage NSCLC is radioresponsive when treated with SBRT or stereotactic ablative radiation therapy. A steep dose-response relationship exists with high rates of durable LC when physical doses of 43-50 Gy are delivered in 3 to 5 fractions.

Patterns of failure after stereotactic body radiation therapy or lobar resection for clinical stage I non-small-cell lung cancer.

INTRODUCTION: The purpose of this study was to compare patterns of failure between lobar resection (lobectomy or pneumonectomy) and stereotactic body radiation therapy (SBRT) for patients with clinical stage I non-small-cell lung cancer (NSCLC). METHODS: From January 2004 to January 2008, 338 patients underwent definitive treatment for pathologically confirmed clinical stage I NSCLC with lobar resection (n = 260) or SBRT (n = 78). Most surgical patients underwent lobectomy (n = 237). SBRT patients received a biologically effective dose of at least 100 Gy10. Lobar resection patients were younger, healthier, and had superior pulmonary function, whereas most of the patients in the SBRT group had T1 tumors. Final pathology upstaged 32.7% of surgery patients, and 20.0% received adjuvant chemotherapy. No SBRT patients received adjuvant chemotherapy. RESULTS: In an unmatched comparison, 4-year lobar local control (98.7% versus 93.6%, p = 0.015) was greater for lobar resection versus SBRT, respectively, though primary tumor (98.7% versus 95.3%, p = 0.088), regional (82.9% versus 78.1%, p = 0.912), and distant control (76.1% versus 54.0%, p = 0.152) were similar. Overall survival (OS, 63.5% versus 29.6%, p < 0.0001) was greater for lobar resection, though cause-specific survival (CSS, 81.3% versus 75.3%, p = 0.923) was similar. In a T-stage matched comparison of 152 patients, there was no significant difference in patterns of failure or CSS, whereas OS favored surgery. CONCLUSION: Lobectomy/pneumonectomy or SBRT results in comparable patterns of failure for clinical stage I NSCLC. In this retrospective comparison, OS was superior for surgery, though CSS was similar. Randomized trials are necessary to control for fundamental differences in comorbidity, which impact interpretation of both tumor control and survival.

Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma.

PURPOSE: Several methods have been proposed for the segmentation of ¹8F-FDG uptake in PET. In this study, we assessed the performance of four categories of ¹8F-FDG PET image segmentation techniques in pharyngolaryngeal squamous cell carcinoma using clinical studies where the surgical specimen served as the benchmark. METHODS: Nine PET image segmentation techniques were compared including: five thresholding methods; the level set technique (active contour); the stochastic expectation-maximization approach; fuzzy clustering-based segmentation (FCM); and a variant of FCM, the spatial wavelet-based algorithm (FCM-SW) which incorporates spatial information during the segmentation process, thus allowing the handling of uptake in heterogeneous lesions. These algorithms were evaluated using clinical studies in which the segmentation results were compared to the 3-D biological tumour volume (BTV) defined by histology in PET images of seven patients with T3-T4 laryngeal squamous cell carcinoma who underwent a total laryngectomy. The macroscopic tumour specimens were collected "en bloc", frozen and cut into 1.7- to 2-mm thick slices, then digitized for use as reference. RESULTS: The clinical results suggested that four of the thresholding methods and expectation-maximization overestimated the average tumour volume, while a contrast-oriented thresholding method, the level set technique and the FCM-SW algorithm underestimated it, with the FCM-SW algorithm providing relatively the highest accuracy in terms of volume determination (-5.9 ± 11.9%) and overlap index. The mean overlap index varied between 0.27 and 0.54 for the different image segmentation techniques. The FCM-SW segmentation technique showed the best compromise in terms of 3-D overlap index and statistical analysis results with values of 0.54 (0.26-0.72) for the overlap index. CONCLUSION: The BTVs delineated using the FCM-SW segmentation technique were seemingly the most accurate and approximated closely the 3-D BTVs defined using the surgical specimens. Adaptive thresholding techniques need to be calibrated for each PET scanner and acquisition/processing protocol, and should not be used without optimization.

Determination of planning target volume for whole stomach irradiation using daily megavoltage computed tomographic images.

PURPOSE: Whole stomach radiation therapy is often used in the management of gastric lymphoma. However, very limited data exist with regard to planning target volume requirements for the whole stomach. This study retrospectively analyzed daily megavoltage computed tomographic (CT) scans of gastric lymphoma patients in order to help determine the interfraction variation of the stomach position. METHODS AND MATERIALS: Forty-one daily megavoltage CT images from 3 gastric lymphoma patients were used for stomach contouring. Each patient's megavoltage CT images were rigidly registered to their CT simulation data sets, and the margin in each direction that covered at least 95% of the daily stomach volumes was computed using a simple grid search. Patient setup variation was also calculated from the daily patient shifts. The organ motion margin was then added to the setup margin to render the total margin. RESULTS: A uniform margin of 2.2 cm is required to cover 95% of the stomach over the treatment course. However, direction-specific margins were observed from 1.72, 1.88, 0.92, 2.23, 1.90, and 0.86 cm for the right, left, posterior, anterior, superior, and inferior directions, respectively. CONCLUSIONS: The results of this study provide helpful 3-dimensional volumetric information to the limited existing data on margin requirements for whole stomach radiation therapy.

Event (error and near-miss) reporting and learning system for process improvement in radiation oncology.

PURPOSE: The value of near-miss and error reporting processes in many industries is well appreciated and typically can be supported with data that have been collected over time. While it is generally accepted that such processes are important in the radiation therapy (RT) setting, studies analyzing the effects of organized reporting and process improvement systems on operation and patient safety in individual clinics remain scarce. The purpose of this work is to report on the design and long-term use of an electronic reporting system in a RT department and compare it to the paper-based reporting system it replaced. METHODS: A specifically designed web-based system was designed for reporting of individual events in RT and clinically implemented in 2007. An event was defined as any occurrence that could have, or had, resulted in a deviation in the delivery of patient care. The aim of the system was to support process improvement in patient care and safety. The reporting tool was designed so individual events could be quickly and easily reported without disrupting clinical work. This was very important because the system use was voluntary. The spectrum of reported deviations extended from minor workflow issues (e.g., scheduling) to errors in treatment delivery. Reports were categorized based on functional area, type, and severity of an event. The events were processed and analyzed by a formal process improvement group that used the data and the statistics collected through the web-based tool for guidance in reengineering clinical processes. The reporting trends for the first 24 months with the electronic system were compared to the events that were reported in the same clinic with a paper-based system over a seven-year period. RESULTS: The reporting system and the process improvement structure resulted in increased event reporting, improved event communication, and improved identification of clinical areas which needed process and safety improvements. The reported data were also useful for the evaluation of corrective measures and recognition of ineffective measures and efforts. The electronic system was relatively well accepted by personnel and resulted in minimal disruption of clinical work. Event reporting in the quarters with the fewest number of reported events, though voluntary, was almost four times greater than the most events reported in any one quarter with the paper-based system and remained consistent from the inception of the process through the date of this report. However, the acceptance was not universal, validating the need for improved education regarding reporting processes and systematic approaches to reporting culture development. CONCLUSIONS: Specially designed electronic event reporting systems in a radiotherapy setting can provide valuable data for process and patient safety improvement and are more effective reporting mechanisms than paper-based systems. Additional work is needed to develop methods that can more effectively utilize reported data for process improvement, including the development of standardized event taxonomy and a classification system for RT.

Multimodality imaging of gene transfer with a receptor-based reporter gene.

UNLABELLED: Gene therapy trials have traditionally used tumor and tissue biopsies for assessing the efficacy of gene transfer. Noninvasive imaging techniques offer a distinct advantage over tissue biopsies in that the magnitude and duration of gene transfer can be monitored repeatedly. Human somatostatin receptor subtype 2 (SSTR2) has been used for the nuclear imaging of gene transfer. To extend this concept, we have developed a somatostatin receptor-enhanced green fluorescent protein fusion construct (SSTR2-EGFP) for nuclear and fluorescent multimodality imaging. METHODS: An adenovirus containing SSTR2-EGFP (AdSSTR2-EGFP) was constructed and evaluated in vitro and in vivo. SCC-9 human squamous cell carcinoma cells were infected with AdEGFP, AdSSTR2, or AdSSTR2-EGFP for in vitro evaluation by saturation binding, internalization, and fluorescence spectroscopy assays. In vivo biodistribution and nano-SPECT imaging studies were conducted with mice bearing SCC-9 tumor xenografts directly injected with AdSSTR2-EGFP or AdSSTR2 to determine the tumor localization of (111)In-diethylenetriaminepentaacetic acid (DTPA)-Tyr3-octreotate. Fluorescence imaging was conducted in vivo with mice receiving intratumoral injections of AdSSTR2, AdSSTR2-EGFP, or AdEGFP as well as ex vivo with tissues extracted from mice. RESULTS: The similarity between AdSSTR2-EGFP and wild-type AdSSTR2 was demonstrated in vitro by the saturation binding and internalization assays, and the fluorescence emission spectra of cells infected with AdSSTR2-EGFP was almost identical to the spectra of cells infected with wild-type AdEGFP. Biodistribution studies demonstrated that the tumor uptake of (111)In-DTPA-Tyr3-octreotate was not significantly different (P > 0.05) when tumors (n = 5) were injected with AdSSTR2 or AdSSTR2-EGFP but was significantly greater than the uptake in control tumors. Fluorescence was observed in tumors injected with AdSSTR2-EGFP and AdEGFP in vivo and ex vivo but not in tumors injected with AdSSTR2. Although fluorescence was observed, there were discrepancies between in vivo imaging and ex vivo imaging as well as between nuclear imaging and fluorescent imaging. CONCLUSION: These studies showed that the SSTR2-EGFP fusion construct can be used for in vivo nuclear and optical imaging of gene transfer.

A miR-200 microRNA cluster as prognostic marker in advanced ovarian cancer.

OBJECTIVE: Ovarian cancer is one of the most deadly human cancers, resulting in over 15,000 deaths in the US each year. A reliable method that could predict disease outcome would improve care of patients with this disease. The main aim of this study is to identify novel prognostic biomarkers for advanced ovarian cancer. METHODS: We hypothesized that microRNAs (miRNAs) may predict outcome and have examined the prognostic value of these small RNA molecules on disease outcome prediction. miRNAs are a newly identified family of non-coding RNA genes, and recent studies have shown that miRNAs are extensively involved in the tumor development process. We have profiled the expression of miRNAs in advanced ovarian cancer using a novel PCR-based platform and correlated miRNA expression profiles with disease outcome. RESULTS: By performing miRNA expression profiling analysis of 55 advanced ovarian tumors, we have shown that three miR-200 miRNAs (miR-200a, miR-200b and miR-429) in the miR-200b-429 cluster are significantly associated with cancer recurrence and overall survival. Further target analysis indicates that these miR-200 miRNAs target multiple genes that are involved in cancer development. In addition, we have also shown that overexpression of this miR-200 cluster inhibits ovarian cancer cell migration. CONCLUSIONS: miR-200b-429 may be used as a prognostic marker for ovarian cancer outcome, and low-level expression of miR-200 miRNAs in this cluster predicts poor survival. In addition, our study suggests that miR-200 miRNAs could play an important regulatory role in ovarian cancer.

Estimation of setup uncertainty using planar and MVCT imaging for gynecologic malignancies.

PURPOSE: This prospective study investigates gynecologic malignancy online treatment setup error corrections using planar kilovoltage/megavoltage (KV/MV) imaging and helical MV computed tomography (MVCT) imaging. METHODS AND MATERIALS: Twenty patients were divided into two groups. The first group (10 patients) was imaged and treated using a conventional linear accelerator (LINAC) with image-guidance capabilities, whereas the second group (10 patients) was treated using tomotherapy with MVCT capabilities. Patients treated on the LINAC underwent planar KV and portal MV imaging and a two-dimensional image registration algorithm was used to match these images to digitally reconstructed radiographs (DRRs). Patients that were treated using tomotherapy underwent MVCT imaging, and a three-dimensional image registration algorithm was used to match planning CT to MVCT images. Subsequent repositioning shifts were applied before each treatment and recorded for further analysis. To assess intrafraction motion, 5 of the 10 patients treated on the LINAC underwent posttreatment planar imaging and DRR matching. Based on these data, patient position uncertainties along with estimated margins based on well-known recipes were determined. RESULTS: The errors associated with patient positioning ranged from 0.13 cm to 0.38 cm, for patients imaged on LINAC and 0.13 cm to 0.48 cm for patients imaged on tomotherapy. Our institutional clinical target volume-PTV margin value of 0.7 cm lies inside the confidence interval of the margins established using both planar and MVCT imaging. CONCLUSION: Use of high-quality daily planar imaging, volumetric MVCT imaging, and setup corrections yields excellent setup accuracy and can help reduce margins for the external beam treatment of gynecologic malignancies.

Prediction of both conserved and nonconserved microRNA targets in animals.

MOTIVATION: MicroRNAs (miRNAs) are involved in many diverse biological processes and they may potentially regulate the functions of thousands of genes. However, one major issue in miRNA studies is the lack of bioinformatics programs to accurately predict miRNA targets. Animal miRNAs have limited sequence complementarity to their gene targets, which makes it challenging to build target prediction models with high specificity. RESULTS: Here we present a new miRNA target prediction program based on support vector machines (SVMs) and a large microarray training dataset. By systematically analyzing public microarray data, we have identified statistically significant features that are important to target downregulation. Heterogeneous prediction features have been non-linearly integrated in an SVM machine learning framework for the training of our target prediction model, MirTarget2. About half of the predicted miRNA target sites in human are not conserved in other organisms. Our prediction algorithm has been validated with independent experimental data for its improved performance on predicting a large number of miRNA down-regulated gene targets. AVAILABILITY: All the predicted targets were imported into an online database miRDB, which is freely accessible at http://mirdb.org.

Comparison of helical, maximum intensity projection (MIP), and averaged intensity (AI) 4D CT imaging for stereotactic body radiation therapy (SBRT) planning in lung cancer.

BACKGROUND AND PURPOSE: To compare helical, MIP and AI 4D CT imaging, for the purpose of determining the best CT-based volume definition method for encompassing the mobile gross tumor volume (mGTV) within the planning target volume (PTV) for stereotactic body radiation therapy (SBRT) in stage I lung cancer. MATERIALS AND METHODS: Twenty patients with medically inoperable peripheral stage I lung cancer were planned for SBRT. Free-breathing helical and 4D image datasets were obtained for each patient. Two composite images, the MIP and AI, were automatically generated from the 4D image datasets. The mGTV contours were delineated for the MIP, AI and helical image datasets for each patient. The volume for each was calculated and compared using analysis of variance and the Wilcoxon rank test. A spatial analysis for comparing center of mass (COM) (i.e. isocenter) coordinates for each imaging method was also performed using multivariate analysis of variance. RESULTS: The MIP-defined mGTVs were significantly larger than both the helical- (p=0.001) and AI-defined mGTVs (p=0.012). A comparison of COM coordinates demonstrated no significant spatial difference in the x-, y-, and z-coordinates for each tumor as determined by helical, MIP, or AI imaging methods. CONCLUSIONS: In order to incorporate the extent of tumor motion from breathing during SBRT, MIP is superior to either helical or AI images for defining the mGTV. The spatial isocenter coordinates for each tumor were not altered significantly by the imaging methods.

Comparison of spirometry and abdominal height as four-dimensional computed tomography metrics in lung.

An important consideration in four-dimensional CT scanning is the selection of a breathing metric for sorting the CT data and modeling internal motion. This study compared two noninvasive breathing metrics, spirometry and abdominal height, against internal air content, used as a surrogate for internal motion. Both metrics were shown to be accurate, but the spirometry showed a stronger and more reproducible relationship than the abdominal height in the lung. The abdominal height was known to be affected by sensor placement and patient positioning while the spirometer exhibited signal drift. By combining these two, a normalization of the drift-free metric to tidal volume may be generated and the overall metric precision may be improved.

Quantitation of the reconstruction quality of a four-dimensional computed tomography process for lung cancer patients.

We have developed a four-dimensional computed tomography (4D CT) technique for mapping breathing motion in radiotherapy treatment planning. A multislice CT scanner (1.5 mm slices) operated in ciné mode was used to acquire 12 contiguous slices in each couch position for 15 consecutive scans (0.5 s rotation, 0.25 s between scans) while the patient underwent simultaneous quantitative spirometry measurements to provide a sorting metric. The spirometry-sorted scans were used to reconstruct a 4D data set. A critical factor for 4D CT is quantifying the reconstructed data set quality which we measure by correlating the metric used relative to internal-object motion. For this study, the internal air content within the lung was used as a surrogate for internal motion measurements. Thresholding and image morphological operations were applied to delineate the air-containing tissues (lungs, trachea) from each CT slice. The Hounsfield values were converted to the internal air content (V). The relationship between the air content and spirometer-measured tidal volume (v) was found to be quite linear throughout the lungs and was used to estimate the overall accuracy and precision of tidal volume-sorted 4D CT. Inspection of the CT-scan air content as a function of tidal volume showed excellent correlations (typically r>0.99) throughout the lung volume. Because of the discovered linear relationship, the ratio of internal air content to tidal volume was indicative of the fraction of air change in each couch position. Theoretically, due to air density differences within the lung and in room, the sum of these ratios would equal 1.11. For 12 patients, the mean value was 1.08 +/- 0.06, indicating the high quality of spirometry-based image sorting. The residual of a first-order fit between v and V was used to estimate the process precision. For all patients, the precision was better than 8%, with a mean value of 5.1% +/- 1.9%. This quantitative analysis highlights the value of using spirometry as the metric in sorting CT scans. The 4D reconstruction provides the CT data required to measure the three-dimensional trajectory of tumor and lung tissue during free breathing.

Comparison of spirometry and abdominal height as four-dimensional computed tomography metrics in lung.

An important consideration in four-dimensional CT scanning is the selection of a breathing metric for sorting the CT data and modeling internal motion. This study compared two noninvasive breathing metrics, spirometry and abdominal height, against internal air content, used as a surrogate for internal motion. Both metrics were shown to be accurate, but the spirometry showed a stronger and more reproducible relationship than the abdominal height in the lung. The abdominal height was known to be affected by sensor placement and patient positioning while the spirometer exhibited signal drift. By combining these two, a normalization of the drift-free metric to tidal volume may be generated and the overall metric precision may be improved.