Original CT Images Research Articles

Quantifying the Effect of 3T Magnetic Resonance Imaging Residual System Distortions and Patient-Induced Susceptibility Distortions on Radiation Therapy Treatment Planning for Prostate Cancer

Toinvestigate the effect of magnetic resonance system- and patient-induced susceptibility distortions from a 3T scanner on dose distributions for prostate cancers. Combined displacement fields from the residual system and patient-induced susceptibility distortions were used to distort 17 prostate patient CT images. VMAT dose plans were initially optimized on distorted CT images and the plan parameters transferred to the original patient CT images to calculate a new dose distribution. Maximum residual mean distortions of 3.19mm at a radial distance of 25cm and maximum mean patient-induced susceptibility shifts of 5.8mm were found using the lowest bandwidth of 122Hz per pixel. There was a dose difference of <0.5% between distorted and undistorted treatment plans. The 90% confidence intervals of the mean difference between the dCT and CT treatment plans were all within an equivalence interval of (-0.5, 0.5) for all investigated plan quality measures. Patient-induced susceptibility distortions at high field strengths in closed bore magnetic resonance scanners are larger than residual system distortions after using vendor-supplied 3-dimensional correction for the delineated regions studied. However, errors in dose due to disturbed patient outline and shifts caused by patient-induced susceptibility effects are below 0.5%.

Effect of Bone Reading CT software on radiologist performance in detecting bone metastases from breast cancer.

To evaluate the effect of CT software that generates rib unfolding images and automatically numbers ribs and thoracic spines on radiologist performance in detecting thoracic bone metastases from breast cancer. A total of 126 patients with breast cancer who underwent chest CT and fludeoxyglucose (FDG)-positron emission tomography (PET)/CT and/or bone scans were retrospectively reviewed. One board-certified radiologist (R1) and one radiology resident (R2) independently assessed the original chest CT and rib unfolding images using a commercially available post-processing software (Bone Reading) application to evaluate metastasis in the ribs and thoracic spines. Results were compared with reference standard based on CT, FDG-PET/CT and/or bone scan with follow-up. Based on reference standard, 78 metastatic bone lesions in 26 patients were identified. On per-patient-based analysis, Bone Reading assessed by R1/R2 had a sensitivity of 84.6%/80.8% and a specificity of 94.0%/94.0% with an accuracy of 92.1%/91.3%. The original CT reading yielded a sensitivity of 73.1%/57.7% and a specificity of 95.0%/94.0% with an accuracy of 90.5%/86.5%. The sensitivity and accuracy of Bone Reading were significantly higher than those of CT reading, as assessed by R2 (both p = 0.031). On per-lesion-based analysis, Bone Reading assessed by R1/R2 yielded a sensitivity of 84.6%/82.1% and a specificity of 99.7%/99.6% with an accuracy of 99.4%/99.3%, while the original CT reading yielded a sensitivity of 71.8%/62.8% and a specificity of 99.6%/99.5% with an accuracy of 99.2%/98.9%. The sensitivity and accuracy with Bone Reading application were significantly higher than those with CT reading by both readers (R1, p = 0.006 and p = 0.036, respectively; R2, both p < 0.001). The mean reading time needed for Bone Reading application was significantly shorter than that for original chest CT reading (p < 0.001). Bone Reading application helped readers find small and sclerotic lesions missed in original CT reading. In patients with breast cancer, the use of Bone Reading application improved radiologist performance in bone metastasis detection compared with original chest CT reading with reduced reading time. This software will be more helpful to inexperienced radiologists for improving the reading performance. Advances in knowledge: Small and sclerotic lesions can be easily missed in original CT reading. Using Bone Reading CT software can enhance the performance of radiologists in detecting bone metastasis in breast cancer. False-negative rates can be significantly reduced in both inexperienced and experienced readers.

Pseudo CT Estimation from MRI Using Patch-based Random Forest.

Recently, MR simulators gain popularity because of unnecessary radiation exposure of CT simulators being used in radiation therapy planning. We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified using feature selection to train the random forest. The well-trained random forest is used to predict the pseudo CT of a new patient. This prediction technique was tested with human brain images and the prediction accuracy was assessed using the original CT images. Peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) indexes were used to quantify the differences between the pseudo and original CT images. The experimental results showed the proposed method could accurately generate pseudo CT images from MR images. In summary, we have developed a new pseudo CT prediction method based on patch-based random forest, demonstrated its clinical feasibility, and validated its prediction accuracy. This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.

Influence of aggregates’ spatial characteristics on air-voids in asphalt mixture

Air-void is the main structure in asphalt mixture; it significantly affects the strength and durability of asphalt mixture. To better understand the influencing factors of air-voids, one group of specimens with different aggregate gradations were fabricated at the same experimental situations and evaluated at first, then, another group of specimens with the same aggregate gradation were drilled from test track and used to investigate the effect of compaction energy on air-voids. The internal structures can be obtained by X-ray computed tomography (X-CT) device, and digital image processing (DIP) technology was used to extract and reconstruct the spatial models of aggregates and air-voids based on original CT images. Influence of aggregates and compaction energy on air-voids were studied; the results show that the improved extracting and segmenting program, which divides the original CT image into a serial of annular regions firstly, can effectively identify different microstructures; 3D fractal dimension provides a quantitative value of presenting the complexity of microstructures’ morphology, it comprehensively reflects the volume, shape and distribution of aggregates and air-voids; aggregates’ angularity has a significant effect on air-voids, and compaction energy causes different characteristics of air-voids as well. Methodologies developed in this paper are effective to evaluate the influence of aggregate particles on air-voids.

Does Manual Delineation only Provide the Side Information in CT Prostate Segmentation?

Prostate segmentation, for accurate prostate localization in CT images, is regarded as a crucial yet challenging task. Nevertheless, due to the inevitable factors (e.g., low contrast, large appearance and shape changes), the most important problem is how to learn the informative feature representation to distinguish the prostate from non-prostate regions. We address this challenging feature learning by leveraging the manual delineation as guidance: the manual delineation does not only indicate the category of patches, but also helps enhance the appearance of prostate. This is realized by the proposed cascaded deep domain adaptation (CDDA) model. Specifically, CDDA constructs several consecutive source domains by employing a mask of manual delineation to overlay on the original CT images with different mask ratios. Upon these source domains, convnet will guide better transferrable feature learning until to the target domain. Particularly, we implement two typical methods: patch-to-scalar (CDDA-CNN) and patch-to-patch (CDDA-FCN). Also, we theoretically analyze the generalization error bound of CDDA. Experimental results show the promising results of our method.

Accurate Lungs Segmentation on CT Chest Images by Adaptive Appearance-Guided Shape Modeling.

To accurately segment pathological and healthy lungs for reliable computer-aided disease diagnostics, a stack of chest CT scans is modeled as a sample of a spatially inhomogeneous joint 3D Markov-Gibbs random field (MGRF) of voxel-wise lung and chest CT image signals (intensities). The proposed learnable MGRF integrates two visual appearance sub-models with an adaptive lung shape submodel. The first-order appearance submodel accounts for both the original CT image and its Gaussian scale space (GSS) filtered version to specify local and global signal properties, respectively. Each empirical marginal probability distribution of signals is closely approximated with a linear combination of discrete Gaussians (LCDG), containing two positive dominant and multiple sign-alternate subordinate DGs. The approximation is separated into two LCDGs to describe individually the lungs and their background, i.e., all other chest tissues. The second-order appearance submodel quantifies conditional pairwise intensity dependencies in the nearest voxel 26-neighborhood in both the original and GSS-filtered images. The shape submodel is built for a set of training data and is adapted during segmentation using both the lung and chest appearances. The accuracy of the proposed segmentation framework is quantitatively assessed using two public databases (ISBI VESSEL12 challenge and MICCAI LOLA11 challenge) and our own database with, respectively, 20, 55, and 30 CT images of various lung pathologies acquired with different scanners and protocols. Quantitative assessment of our framework in terms of Dice similarity coefficients, 95-percentile bidirectional Hausdorff distances, and percentage volume differences confirms the high accuracy of our model on both our database (98.4±1.0%, 2.2±1.0 mm, 0.42±0.10%) and the VESSEL12 database (99.0±0.5%, 2.1±1.6 mm, 0.39±0.20%), respectively. Similarly, the accuracy of our approach is further verified via a blind evaluation by the organizers of the LOLA11 competition, where an average overlap of 98.0% with the expert's segmentation is yielded on all 55 subjects with our framework being ranked first among all the state-of-the-art techniques compared.

Noninvasive microwave ablation zone radii estimation using x-ray CT image analysis.

The aims of this study were to noninvasively and automatically estimate both the radius of the ablated liver tissue and the radius encircling the treated zone, which also defines where the tissue is definitely untreated during a microwave (MW) thermal ablation procedure. Fourteen ex vivo bovine fresh liver specimens were ablated at 40 W using a 14 G microwave antenna, for durations of 3, 6, 8, and 10 min. The tissues were scanned every 5 s during the ablation using an x-ray CT scanner. In order to estimate the radius of the ablation zone, the acquired images were transformed into a polar presentation by displaying the Hounsfield units (HU) as a function of angle and radius. From this polar presentation, the average HU radial profile was analyzed at each time point and the ablation zone radius was estimated. In addition, textural analysis was applied to the original CT images. The proposed algorithm identified high entropy regions and estimated the treated zone radius per time. The estimated ablated zone radii as a function of treatment durations were compared, by means of correlation coefficient and root mean square error (RMSE) to gross pathology measurements taken immediately post-treatment from similarly ablated tissue. Both the estimated ablation radii and the treated zone radii demonstrated strong correlation with the measured gross pathology values (R(2) ≥ 0.89 and R(2) ≥ 0.86, respectively). The automated ablation radii estimation had an average discrepancy of less than 1 mm (RMSE = 0.65 mm) from the gross pathology measured values, while the treated zone radii showed a slight overestimation of approximately 1.5 mm (RMSE = 1.6 mm). Noninvasive monitoring of MW ablation using x-ray CT and image analysis is feasible. Automatic estimations of the ablation zone radius and the radius encompassing the treated zone that highly correlate with actual ablation measured values can be obtained. This technique can therefore potentially be used to obtain real time monitoring and improve the clinical outcome.

Fecal microbiota transplantation via fluoroscopy-guided nasojejunal catheter placement: indications, technique, and the role of radiology.

Clostridium difficile is a well-established cause of nosocomial gastrointestinal disease. Although antibiotics remain an effective first-line treatment for C. difficile colitis (CDC), relapse and recurrence are common. FMT has emerged as one of the safest and most effective known therapies available for recurrent or refractory CDC, which is likely due to restoration of the protective microbiotic barrier of the gastrointestinal tract. FMT varies greatly across institutions by route of delivery, dose, and protocol. We present our experience with FMT via fluoroscopic-guided nasojejunal catheter placement. The discussion will include indications and contraindications, protocol, and procedural technique, and include a case presentation incorporating original CT and fluoroscopic images. Specifically, we will address the advantages and disadvantages of image-guided FMT via the upper GI tract with respect to nasogastric-, colonoscopic-, and enema-based delivery. The efficacy of FMT for the treatment of C. difficile has been widely demonstrated in several prospective and case studies. We feel that nasojejunal FMT is an underutilized radiologic procedure which can benefit selected patients, particularly given the advantages in risk profile, cost, convenience, and lack of routine sedation.

SU‐F‐T‐37: Dosimetric Evaluation of Planned Versus Decay Corrected Treatment Plans for the Treatment of Tandem‐Based Cervical HDR Brachytherapy

Purpose:This study evaluated dosimetric parameters for actual treatment plans versus decay corrected treatment plans for cervical HDR brachytherapy.Methods:125 plans of 25 patients, who received 5 fractions of HDR brachytherapy, were evaluated in this study. Dose was prescribed to point A (ICRU‐38) and High risk clinical tumor volume (HR‐CTV) and organs at risk (OAR) were, retrospectively, delineated on original CT images by treating physician. First HDR plan was considered as reference plan and decay correction was applied to calculate treatment time for subsequent fractions, and was applied, retrospectively, to determine point A, HR‐CTV D90, and rectum and bladder doses.Results:The differences between mean point A reference doses and the point A doses of the plans computed using decay times were found to be 1.05%±0.74% (−2.26% to 3.26%) for second fraction; −0.25%±0.84% (−3.03% to 3.29%) for third fraction; 0.04%±0.70% (−2.68% to 2.56%) for fourth fraction and 0.30%±0.81% (−3.93% to 2.67%) for fifth fraction. Overall mean point A dose difference, for all fractions, was 0.29%±0.38% (within ± 5%). Mean rectum and bladder dose differences were calculated to be −3.46%±0.12% and −2.47%±0.09%, for points, respectively, and −1.72%±0.09% and −0.96%±0.06%, for D2cc, respectively. HR‐CTV D90 mean dose difference was found to be −1.67% ± 0.11%. There was no statistically significant difference between the reference planned point A doses and that calculated using decay time to the subsequent fractions (p&lt;0.05).Conclusion:This study reveals that a decay corrected treatment will provide comparable dosimetric results and can be utilized for subsequent fractions of cervical HDR brachytherapy instead of actual treatment planning. This approach will increase efficiency, decrease workload, reduce patient observation time between applicator insertion and treatment delivery. This would be particularly useful for institutions with limited resources or large patient populations with limited access to care.

TH-AB-207A-12: CT Lung Cancer Screening and the Effects of Further Dose Reduction On CAD Performance

Purpose: CT lung screening is already performed at low doses. In this study, we investigated the effects of further dose reduction on a lung-nodule CAD detection algorithm. Methods: The original raw CT data and images from 348 patients were obtained from our local database of National Lung Screening Trial (NLST) cases. 61 patients (17.5%) had at least one nodule reported on the NLST reader forms. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, a CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST forms. Sensitivities and false-positive rates (FPR) were calculated for each dose level, with a sub-analysis by nodule LungRADS category. Results: For larger category 4 nodules, median sensitivities were 100% at all three dose levels, and mean sensitivity decreased with dose. For the more challenging category 2 and 3 nodules, the dose dependence was less obvious. Overall, mean subject-level sensitivity varied from 38.5% at 100% dose to 40.4% at 50% dose, a difference of only 1.9%. However, median FPR quadrupled from 1 per case at 100% dose to 4 per case at 25% dose. Conclusions: Dose reduction affected nodule detectability differently depending on the LungRADS category, and FPR was very sensitive at sub-screening levels. Care should be taken to adapt CAD for the very challenging noise characteristics of screening. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.

TU‐AB‐BRA‐02: An Efficient Atlas‐Based Synthetic CT Generation Method

Purpose:A major obstacle for MR‐only radiotherapy is the need to generate an accurate synthetic CT (sCT) from MR image(s) of a patient for the purposes of dose calculation and DRR generation. We propose here an accurate and efficient atlas‐based sCT generation method, which has a computation speed largely independent of the number of atlases used.Methods:Atlas‐based sCT generation requires a set of atlases with co‐registered CT and MR images. Unlike existing methods that align each atlas to the new patient independently, we first create an average atlas and pre‐align every atlas to the average atlas space. When a new patient arrives, we compute only one deformable image registration to align the patient MR image to the average atlas, which indirectly aligns the patient to all pre‐aligned atlases. A patch‐based non‐local weighted fusion is performed in the average atlas space to generate the sCT for the patient, which is then warped back to the original patient space. We further adapt a PatchMatch algorithm that can quickly find top matches between patches of the patient image and all atlas images, which makes the patch fusion step also independent of the number of atlases used.Results:Nineteen brain tumour patients with both CT and T1‐weighted MR images are used as testing data and a leave‐one‐out validation is performed. Each sCT generated is compared against the original CT image of the same patient on a voxel‐by‐voxel basis. The proposed method produces a mean absolute error (MAE) of 98.6±26.9 HU overall. The accuracy is comparable with a conventional implementation scheme, but the computation time is reduced from over an hour to four minutes.Conclusion:An average atlas space patch fusion approach can produce highly accurate sCT estimations very efficiently. Further validation on dose computation accuracy and using a larger patient cohort is warranted. The author is a full time employee of Elekta, Inc.

Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests

AbstractMaterial engineers use interrupted in situ tensile testing to investigate the damage mechanisms in composite materials. For each subsequent scan, the load is incrementally increased until the specimen is completely fractured. During the interrupted in situ testing of glass fiber reinforced polymers (GFRPs) defects of four types are expected to appear: matrix fracture, fiber/matrix debonding, fiber pull‐out, and fiber fracture. There is a growing demand for the detection and analysis of these defects among the material engineers. In this paper, we present a novel workflow for the detection, classification, and visual analysis of defects in GFRPs using interrupted in situ tensile tests in combination with X‐ray Computed Tomography. The workflow is based on the automatic extraction of defects and fibers. We introduce the automatic Defect Classifier assigning the most suitable type to each defect based on its geometrical features. We present a visual analysis system that integrates four visualization methods: 1) the Defect Viewer highlights defects with visually encoded type in the context of the original CT image, 2) the Defect Density Maps provide an overview of the defect distributions according to type in 2D and 3D, 3) the Final Fracture Surface estimates the material fracture's location and displays it as a 3D surface, 4) the 3D Magic Lens enables interactive exploration by combining detailed visualizations in the region of interest with overview visualizations as context. In collaboration with material engineers, we evaluate our solution and demonstrate its practical applicability.

Anatomic structure-based deformable image registration of brachytherapy implants in the treatment of locally advanced cervix cancer

PurposeTo examine the impact of anatomic structure-based image sets in deformable image registration (DIR) for cervical cancer patients. Methods and MaterialsCT examinations of 7 patients previously treated for locally advanced cervical cancer with external beam radiation therapy and from three to five fractions of high-dose-rate brachytherapy (HDR-BT) were used. Structure-based image sets were created from “free” structures already made for planning purposes, with each structure of interest assigned a unique, homogeneous Hounsfield number. Subsequent HDR fractions were registered to the pretreatment external beam radiation therapy and/or the first HDR fraction using commercially available software by rigid alignment (RIG) followed by DIR. Comparison methods included quantification of external contour displacement between source and target images and calculation of mean voxel displacement values. Registration results for structure-based image sets were then compared and contrasted to intensity-based registrations of the original grayscale images. ResultsUtilization of anatomic structure-based image sets resulted in better initial rigid matching (A-RIG) with more importance on applicator positioning and soft tissue structures. Subsequent DIR of anatomic structure-based images allowed for intermodality registrations, whereas all intermodality registrations using original CT images failed to produce anatomically feasible results. ConclusionsWe have investigated the use of structure-based CT image sets for image registrations and have produced anatomically favorable registrations with excellent matching of external contours as compared to registrations of original grayscale images. Commercial software registrations using treatment-planning structures required no manual tweaking on a per-patient basis, suggesting results are reproducible and broadly applicable.

3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes.

By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes.

Application of 3D-printing kidney and stones for PCNL planning and teaching: a preliminary research

Objective To explore the possibility of three-dimensional (3D) kidney replications for clinical and teaching of percutaneous nephrolithotomy (PCNL). Methods The CT urography (CTU) DICOM format data from 5 patients with kidney calculi were selected from March 1st to June 1st, 2015.Thresholding technique, region growing technique, edit mask technique and multiple slice edit technique were used in sequence by Mimics software.And five 3D replications were printed by Object 500 3D printer. The sizes of the replications were measured and the replications were punctured. Results The 3D replications of the kidneys were successfully designed and printed.The average difference of the long axes between 3D replications and patients' kidneys was 0.283cm, the average difference of the diameters was 0.212cm, and the average difference of the diameter of the stones was 0.244cm. The sizes of the 3D replications were basically consistent with those of patients' kidneys.The simulative puncturing was successful. Conclusions After comparing the 3D replications with their original 2D CT images, the anatomical details are found basically the same.The 3D replications could provide 3D visual observations of organ anatomy for surgeons. Key words: Kidney calculi; Nephrostomy, percutaneous; 3D-printing; Surgical simulation; Teaching and training

Comparison between helical tomotherapy and intensity-modulated radiotherapy on acute toxicity in patients with rectal cancer

Objective To compare acute toxicity for stage Ⅱ-Ⅲ patients with rectal cancer irradiated with helical tomotherapy (HT) and conventional five-field intensity-modulated radiotherapy (5-IMRT). Methods The data of 84 stage Ⅱ-Ⅲ patients with rectal adenocarcinoma treated with concurrent chemoradiotherapy (CRT) were retrospectively analyzed. 19 patients underwent postoperative CRT, and 65 patients underwent preoperative CRT. 43 patients received radiotherapy with HT and 41 patients with 5-IMRT. The delineation on clinical target volume (CTV) and gross tumor target (GTV) was similar for two groups. The CTV to plan tumor volume (PTV) margins were 1.0 cm for patients with 5-IMRT and 0.5 cm for patients with HT. For all patients, a dose of 45.0-50.4 Gy, in daily fractions of 1.8 Gy, was delivered to PTV. For 45 patients with high risk factors, simultaneous integrated boost (SIB) was given to the tumor or tumor bed of a total dose of 55.0-60.0 Gy, in daily fractions of 2.1-2.3 Gy. Before treatment, the patients treated with HT underwent scanning by the tomotherapy-integrated megavoltage computed tomography (MVCT) scan modality and were positioned by co-registration of these images to the original kilovoltage planning CT image set. Concurrent capecitabine every day 1 600 mg/m2, twice daily on every day in the week. Results The rates of grade ≥2 acute cystitis were 7.0 % (3 cases) in HT group and 2.4 % (1 case) in 5-IMRT group (P= 0.616), and ≥3 grade acute diarrhea were 4.7 % (2 cases) and 12.2 % (5 cases), respectively (P= 0.259). ≥2 grade leukopenia were 48.8 % (21 cases) and 19.5 % (8 cases), respectively (P= 0.005), ≥1 grade anemia were 34.9 % (15 cases) and 14.6 % (6 cases), respectively (P= 0.032), and ≥1 grade thrombocytopenia were 23.3 % (10 cases) and 14.6 % (6 cases), respectively (P= 0.314). Conclusions There is no significant difference in acute diarrhea and cystitis for patients treated with HT and 5-IMRT. Leukopenia and anemia in patients treated with HT are worse than those in patients with 5-IMRT, and thrombocytopenia is similar in the two groups. Key words: Rectal neoplasms; Chemoradiotherapy; Helical tomotherapy; Acute toxicity

The impact of set-up errors on dose distribution during the image-guided intensity-modulated radiotherapy in elderly patients with prostate cancer

Objective To analyze the impact of set-up errors on planning target volume (PTV) for tumors and radiation dose distributions, then to investigate the necessity of on-line set-up error correction for prostate cancer during IMRT. Methods Cone-beam CT (CBCT) scanning images in 16 patients with prostate cancer were acquired with a total of 214 times during IMRT. The CBCT images and the original planning CT images were matched to acquire the translational errors of the x, y and z axis. The dose distributions were recalculated based on the data of each set-up error. The PTV, radiation dose distribution in organs at risk including bladder and rectum, and dose volume parameters were calculated in the re-planning, and then compared with the original planning by paired t-test. Results The PTV 95% dose volume (D95) and PTV minimal dose volume (Dmin) were lower in the re-planning than in the original planning after 214 times set-up (7613.73 cGy vs. 7764.25 cGy, 80.2% vs. 86.8%, t=2.494 and 5.536, P=0.025 or <0.001), but it could be acceptable. Bladder received 50 Gy dose volume (V50), 30% bladder volume dose (D30), rectume received 50 Gy dose volume (V50) and 25% rectume volume dose (D25) in the re-planning had no statistical differences with those in the original planning. Conclusions The set-up errors lead to the decrease of PTV D95 but be acceptable. The radiation dose received by bladder and rectum has no obvious changes in the re-planning as compared with the original planning. The on-line set-up error correction for prostate cancer may improve the treatment accuracy during IMRT. Key words: Prostatic neoplasms; Radiotherapy; Radiation dosage; Image processing, computer-assisted

Dosimetric effects of roll rotational setup errors on lung stereotactic ablative radiotherapy using volumetric modulated arc therapy.

To evaluate the dosimetric effects of roll-rotational setup errors of stereotactic ablative radiotherapy (SABR) for lung cancer using volumetric modulated arc therapy (VMAT). A total of 23 lung SABR cases were evaluated retrospectively. Each of the planning CT images was intentionally rotated by ±1°, ±2° and ±3°. After that, to simulate the translational couch correction, rotated CT images were moved along the x, y and z axis to match the centroid of the target volume in the rotated CT images with that in the original CT images. The differences in D95% and V100% of the target volume, D0.35cc of spinal cord, D0.35cc and D5cc of oesophagus and V20Gy of lung between the original and the rotated CT images were calculated. The average differences in D95% and V100% of target volume, D0.35cc of spinal cord, D0.35cc and D5cc of oesophagus and V20Gy of lung were -0.3% ± 0.4% and -0.7% ± 2.4%, 1.6 ± 27.9 cGy, -1.6 ± 37.6 cGy, 15.9 ± 25.3 cGy and 0.0% ± 0.1%, respectively. The dosimetric changes in organs at risk (OARs) near the target volume were sometimes considerable due to roll-rotational setup errors, despite the translational correction, and those were patient specific. In the case of coplanar VMAT for lung SABR, dosimetric changes to the target volume due to roll-rotational setup errors could be compensated by translational correction, whereas those to the OARs could not in some cases. Roll-rotational setup errors would increase the dose to OARs despite the translational correction.

3D Reconstruction of Funnel Flow Boundary Using Automatic Point Set Extraction

Abstract The paper presents an automatic point set extraction method for reconstructing 3D tomography images of funnel flow boundary. The method clearly shows the boundary between the funnel flow and stagnant zone during silo discharging process. After adjusting the contrast of the original X-ray CT image and applying filter function, the intensity profile of the image shows a high jump corresponding to the local flow boundary position at a specific height of the silo model. By extracting and connecting those jump points gave us a boundary line of the funnel flow from the stagnant. The outcome of segmented image opens a door for analysing further about funnel flow in 3D images.

Enhanced reading time efficiency by use of automatically unfolded CT rib reformations in acute trauma

Rationale of this study was to evaluate whether unfolded rib images enhance time efficiency in detection of rib fractures and time efficiency in patients with acute thoracic trauma.51 subsequent patients with thoracic trauma underwent 64-slice computed tomography. 1mm thick axial slices were reformatted using a commercially available post-processing software application generating rotatable unfolded rib images. Diagnostic accuracy was evaluated by 3 readers and compared to multiplanar reformations of the original CT images. Reformation and evaluation times were recorded.116 rib fractures were detected. The multiplanar reformation analysis yielded a sensitivity of 87.9%/93.9%/79.7% with a specificity of 97%/97%/82.2%, whilst the unfolded rib image analysis yielded a sensitivity of 94.8%/94.8%/92.2% and a specificity of 85.2/87.8%/82.4 (p=0.06/0.8/0.04) with high inter-observer agreement (k=0.79–0.85). The mean reading time for the multiplanar reformations was significantly longer (reader 1: 103.7±27.1s/reader 2: 81.8±40.6s/reader 3: 154.3±39.2s) than the evaluation of the unfolded rib images (19.4±4.9s/26.9±15.0s/49.9±18.7s; p<0.01).Concluding, the unfolded rib display reduces reading time for detection of rib fractures in acute thoracic trauma patients significantly and does not compromise the diagnostic accuracy significantly in experienced radiologists. However, unexperienced readers may profit from use of this display.