L Zhang

Comparison of 2D radiographic images and 3D cone beam computed tomography for positioning head-and-neck radiotherapy patients.

PURPOSE To assess the positioning accuracy using two-dimensional kilovoltage (2DkV) imaging and three-dimensional cone beam CT (CBCT) in patients with head and neck (H&N) cancer receiving radiation therapy. To assess the benefit of patient-specific headrest. MATERIALS AND METHODS All 21 patients studied were immobilized using thermoplastic masks with either a patient-specific vacuum bag (11 of 21, IMA) or standard clear plastic (10 of 21, IMB) headrests. Each patient was imaged with a pair of orthogonal 2DkV images in treatment position using onboard imaging before the CBCT procedure. The 2DkV and CBCT images were acquired weekly during the same session. The 2DkV images were reviewed by oncologists and also analyzed by a software tool based on mutual information (MI). RESULTS Ninety-eight pairs of assessable 2DkV-CBCT alignment sets were obtained. Systematic and random errors were <1.6 mm for both 2DkV and CBCT alignments. When we compared shifts determined by CBCT and 2DkV for the same patient setup, statistically significant correlations were observed in all three major directions. Among all CBCT couch shifts, 4.1% > or = 0.5 cm and 18.7% > or = 0.3 cm, whereas among all 2DkV (MI) shifts, 1.7% > or = 0.5 cm and 11.2% > or = 0.3 cm. Statistically significant difference was found on anteroposterior direction between IMA and IMB with the CBCT alignment only. CONCLUSIONS The differences between 2D and 3D alignments were mainly caused by the relative flexibility of certain H&N structures and possibly by rotation. Better immobilization of the flexible neck is required to further reduce the setup errors for H&N patients receiving radiotherapy.

Performance Evaluation of Automatic Anatomy Segmentation Algorithm on Repeat or Four-Dimensional Computed Tomography Images Using Deformable Image Registration Method

PURPOSE Auto-propagation of anatomic regions of interest from the planning computed tomography (CT) scan to the daily CT is an essential step in image-guided adaptive radiotherapy. The goal of this study was to quantitatively evaluate the performance of the algorithm in typical clinical applications. METHODS AND MATERIALS We had previously adopted an image intensity-based deformable registration algorithm to find the correspondence between two images. In the present study, the regions of interest delineated on the planning CT image were mapped onto daily CT or four-dimensional CT images using the same transformation. Postprocessing methods, such as boundary smoothing and modification, were used to enhance the robustness of the algorithm. Auto-propagated contours for 8 head-and-neck cancer patients with a total of 100 repeat CT scans, 1 prostate patient with 24 repeat CT scans, and 9 lung cancer patients with a total of 90 four-dimensional CT images were evaluated against physician-drawn contours and physician-modified deformed contours using the volume overlap index and mean absolute surface-to-surface distance. RESULTS The deformed contours were reasonably well matched with the daily anatomy on the repeat CT images. The volume overlap index and mean absolute surface-to-surface distance was 83% and 1.3 mm, respectively, compared with the independently drawn contours. Better agreement (>97% and <0.4 mm) was achieved if the physician was only asked to correct the deformed contours. The algorithm was also robust in the presence of random noise in the image. CONCLUSION The deformable algorithm might be an effective method to propagate the planning regions of interest to subsequent CT images of changed anatomy, although a final review by physicians is highly recommended.

Adaptive radiotherapy for head and neck cancer - Dosimetric results from a prospective clinical trial

PURPOSE To conduct a clinical trial evaluating adaptive head and neck radiotherapy (ART). METHODS Patients with locally advanced oropharyngeal cancer were prospectively enrolled. Daily CT-guided setup and deformable image registration permitted mapping of dose to avoidance structures and CTVs. We compared four planning scenarios: (1) original IMRT plan aligned daily to marked isocenter (BB); (2) original plan aligned daily to bone (IGRT); (3) IGRT with one adaptive replan (ART1); and (4) actual treatment received by each study patient (IGRT with one or two adaptive replans, ART2). RESULTS All 22 study patients underwent one replan (ART1); eight patients had two replans (ART2). ART1 reduced mean dose to contralateral parotid by 0.6 Gy or 2.8% (paired t-test; p=0.003) and ipsilateral parotid by 1.3 Gy (3.9%) (p=0.002) over the IGRT alone. ART2 further reduced the mean contralateral parotid dose by 0.8 Gy or 3.8% (p=0.026) and ipsilateral parotid by 4.1 Gy or 9% (p=0.001). ART significantly reduced integral body dose. CONCLUSIONS This pilot trial suggests that head and neck ART dosimetrically outperforms IMRT. IGRT that leverages conventional PTV margins does not improve dosimetry. One properly timed replan delivers the majority of achievable dosimetric improvement. The clinical impact of ART must be confirmed by future trials.

A beam-specific planning target volume (PTV) design for proton therapy to account for setup and range uncertainties

PURPOSE To report a method for explicitly designing a planning target volume (PTV) for treatment planning and evaluation in heterogeneous media for passively scattered proton therapy and scanning beam proton therapy using single-field optimization (SFO). METHODS AND MATERIALS A beam-specific PTV (bsPTV) for proton beams was derived by ray-tracing and shifting ray lines to account for tissue misalignment in the presence of setup error or organ motion. Range uncertainties resulting from inaccuracies in computed tomography-based range estimation were calculated for proximal and distal surfaces of the target in the beam direction. The bsPTV was then constructed based on local heterogeneity. The bsPTV thus can be used directly as a planning target as if it were in photon therapy. To test the robustness of the bsPTV, we generated a single-field proton plan in a virtual phantom. Intentional setup and range errors were introduced. Dose coverage to the clinical target volume (CTV) under various simulation conditions was compared between plans designed based on the bsPTV and a conventional PTV. RESULTS The simulated treatment using the bsPTV design performed significantly better than the plan using the conventional PTV in maintaining dose coverage to the CTV. With conventional PTV plans, the minimum coverage to the CTV dropped from 99% to 67% in the presence of setup error, internal motion, and range uncertainty. However, plans using the bsPTV showed minimal drop of target coverage from 99% to 94%. CONCLUSIONS The conventional geometry-based PTV concept used in photon therapy does not work well for proton therapy. We investigated and validated a beam-specific PTV method for designing and evaluating proton plans.

Measuring Computed Tomography Scanner Variability of Radiomics Features.

ObjectivesThe purpose of this study was to determine the significance of interscanner variability in CT image radiomics studies. Materials and MethodsWe compared the radiomics features calculated for non–small cell lung cancer (NSCLC) tumors from 20 patients with those calculated for 17 scans of a specially designed radiomics phantom. The phantom comprised 10 cartridges, each filled with different materials to produce a wide range of radiomics feature values. The scans were acquired using General Electric, Philips, Siemens, and Toshiba scanners from 4 medical centers using their routine thoracic imaging protocol. The radiomics feature studied included the mean and standard deviations of the CT numbers as well as textures derived from the neighborhood gray-tone difference matrix. To quantify the significance of the interscanner variability, we introduced the metric feature noise. To look for patterns in the scans, we performed hierarchical clustering for each cartridge. ResultsThe mean CT numbers for the 17 CT scans of the phantom cartridges spanned from −864 to 652 Hounsfield units compared with a span of −186 to 35 Hounsfield units for the CT scans of the NSCLC tumors, showing that the phantoms dynamic range includes that of the tumors. The interscanner variability of the feature values depended on both the cartridge material and the feature, and the variability was large relative to the interpatient variability in the NSCLC tumors for some features. The feature interscanner noise was greatest for busyness and least for texture strength. Hierarchical clustering produced different clusters of the phantom scans for each cartridge, although there was some consistent clustering by scanner manufacturer. ConclusionsThe variability in the values of radiomics features calculated on CT images from different CT scanners can be comparable to the variability in these features found in CT images of NSCLC tumors. These interscanner differences should be considered, and their effects should be minimized in future radiomics studies.

A deformable image registration method to handle distended rectums in prostate cancer radiotherapy

In image-guided adaptive radiotherapy, it is important to have the capability to automatically and accurately delineate the rectal wall, which is a major dose-limiting organ in prostate cancer radiotherapy. As image registration is a process to find the spatial correspondence between two images, a major challenge in intensity-based deformable image registration is to deal with the situation where no correspondence exists for some objects between the two images to be registered. One example is the variation of rectal contents due to the presence and absence of bowel gas. The intensity-based deformable image registration methods alone cannot create the correct spatial transformation if there is no correspondence between the source and target images. In this study we implemented an automatic image intensity modification procedure to create artificial gas pockets in the planning computed tomography (CT) images. A diffusion-based deformable image registration algorithm was developed to use an adaptive smoothing algorithm to better handle large organ deformations. The process was tested in 15 prostate cancer cases and 30 daily CT images containing the largest distended rectums. The manually delineated rectums agreed well with the autodelineated rectums when using the image-intensity modification procedure.

Automatic segmentation of whole breast using atlas approach and deformable image registration.

PURPOSE To compare interobserver variations in delineating the whole breast for treatment planning using two contouring methods. METHODS AND MATERIALS Autosegmented contours were generated by a deformable image registration-based breast segmentation method (DEF-SEG) by mapping the whole breast clinical target volume (CTVwb) from a template case to a new patient case. Eight breast radiation oncologists modified the autosegmented contours as necessary to achieve a clinically appropriate CTVwb and then recontoured the same case from scratch for comparison. The times to complete each approach, as well as the interobserver variations, were analyzed. The template case was also mapped to 10 breast cancer patients with a body mass index of 19.1-35.9 kg/m(2). The three-dimensional surface-to-surface distances and volume overlapping analyses were computed to quantify contour variations. RESULTS The median time to edit the DEF-SEG-generated CTVwb was 12.9 min (range, 3.4-35.9) compared with 18.6 min (range, 8.9-45.2) to contour the CTVwb from scratch (30% faster, p = 0.028). The mean surface-to-surface distance was noticeably reduced from 1.6 mm among the contours generated from scratch to 1.0 mm using the DEF-SEG method (p = 0.047). The deformed contours in 10 patients achieved 94% volume overlap before correction and required editing of 5% (range, 1-10%) of the contoured volume. CONCLUSION Significant interobserver variations suggested a lack of consensus regarding the CTVwb, even among breast cancer specialists. Using the DEF-SEG method produced more consistent results and required less time. The DEF-SEG method can be successfully applied to patients with different body mass indexes.

ibex: An open infrastructure software platform to facilitate collaborative work in radiomics

PURPOSE Radiomics, which is the high-throughput extraction and analysis of quantitative image features, has been shown to have considerable potential to quantify the tumor phenotype. However, at present, a lack of software infrastructure has impeded the development of radiomics and its applications. Therefore, the authors developed the imaging biomarker explorer (IBEX), an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. METHODS The IBEX software package was developed using the MATLAB and c/c++ programming languages. The software architecture deploys the modern model-view-controller, unit testing, and function handle programming concepts to isolate each quantitative imaging analysis task, to validate if their relevant data and algorithms are fit for use, and to plug in new modules. On one hand, IBEX is self-contained and ready to use: it has implemented common data importers, common image filters, and common feature extraction algorithms. On the other hand, IBEX provides an integrated development environment on top of MATLAB and c/c++, so users are not limited to its built-in functions. In the IBEX developer studio, users can plug in, debug, and test new algorithms, extending IBEXs functionality. IBEX also supports quality assurance for data and feature algorithms: image data, regions of interest, and feature algorithm-related data can be reviewed, validated, and/or modified. More importantly, two key elements in collaborative workflows, the consistency of data sharing and the reproducibility of calculation result, are embedded in the IBEX workflow: image data, feature algorithms, and model validation including newly developed ones from different users can be easily and consistently shared so that results can be more easily reproduced between institutions. RESULTS Researchers with a variety of technical skill levels, including radiation oncologists, physicists, and computer scientists, have found the IBEX software to be intuitive, powerful, and easy to use. IBEX can be run at any computer with the windows operating system and 1GB RAM. The authors fully validated the implementation of all importers, preprocessing algorithms, and feature extraction algorithms. Windows version 1.0 beta of stand-alone IBEX and IBEXs source code can be downloaded. CONCLUSIONS The authors successfully implemented IBEX, an open infrastructure software platform that streamlines common radiomics workflow tasks. Its transparency, flexibility, and portability can greatly accelerate the pace of radiomics research and pave the way toward successful clinical translation.

Effectiveness of Using Fewer Implanted Fiducial Markers for Prostate Target Alignment

PURPOSE To evaluate the impact of the number and location of intraprostatic fiducial markers on the accuracy and reproducibility of daily prostate target alignment and to evaluate the migration of such markers. METHODS AND MATERIALS Three gold fiducial markers were implanted transrectally under ultrasound guidance near the apex, middle, and base of the prostate in 10 prostate cancer patients. The patients had pretreatment in-room computed tomography (CT) scans three times a week, for approximately 25 CT scans per patient during the 8-week treatment course. A total of 1280 alignments were performed using different alignment scenarios: whole-prostate soft tissue alignment (the gold standard), bone alignment, and seven permutations of alignments using one, two, or three fiducial markers. The results of bone alignment and fiducial alignment were compared with the results of whole-prostate alignment. Fiducial migration was also evaluated. RESULTS Single-fiducial-marker alignment was more accurate and reproducible than bone alignment. However, due to organ deformation, single fiducial markers did not always reliably represent the position of the entire prostate. The use of two-fiducial combinations was more accurate and reproducible than single-fiducial alignment, and use of all three fiducials was the best. Use of an apex fiducial together with a base fiducial rivaled the use of all three fiducials markers together. Fiducial migration was minimal. CONCLUSIONS The number and the location of implanted fiducial markers affect the accuracy and reliability of daily prostate target alignment. The use of two or more fiducial markers is recommended.

Stage III Non–Small Cell Lung Cancer: Prognostic Value of FDG PET Quantitative Imaging Features Combined with Clinical Prognostic Factors

PURPOSE To determine whether quantitative imaging features from pretreatment positron emission tomography (PET) can enhance patient overall survival risk stratification beyond what can be achieved with conventional prognostic factors in patients with stage III non-small cell lung cancer (NSCLC). MATERIALS AND METHODS The institutional review board approved this retrospective chart review study and waived the requirement to obtain informed consent. The authors retrospectively identified 195 patients with stage III NSCLC treated definitively with radiation therapy between January 2008 and January 2013. All patients underwent pretreatment PET/computed tomography before treatment. Conventional PET metrics, along with histogram, shape and volume, and co-occurrence matrix features, were extracted. Linear predictors of overall survival were developed from leave-one-out cross-validation. Predictive Kaplan-Meier curves were used to compare the linear predictors with both quantitative imaging features and conventional prognostic factors to those generated with conventional prognostic factors alone. The Harrell concordance index was used to quantify the discriminatory power of the linear predictors for survival differences of at least 0, 6, 12, 18, and 24 months. Models were generated with features present in more than 50% of the cross-validation folds. RESULTS Linear predictors of overall survival generated with both quantitative imaging features and conventional prognostic factors demonstrated improved risk stratification compared with those generated with conventional prognostic factors alone in terms of log-rank statistic (P = .18 vs P = .0001, respectively) and concordance index (0.62 vs 0.58, respectively). The use of quantitative imaging features selected during cross-validation improved the model using conventional prognostic factors alone (P = .007). Disease solidity and primary tumor energy from the co-occurrence matrix were found to be selected in all folds of cross-validation. CONCLUSION Pretreatment PET features were associated with overall survival when adjusting for conventional prognostic factors in patients with stage III NSCLC.