Computed Tomography Planning Research Articles

Standardizing the Cardiac Radioablation Targeting Workflow: Enabling Semi-Automated Angulation and Segmentation of the Heart According to the American Heart Association Segmented Model

PurposeCardiac radioablation has evolved as a potential treatment modality for therapy-refractory ventricular tachycardia. To standardize cardiac radioablation treatments, promote accurate communication and target identification, and to assess toxicity, robust, and reproducible methods for angulation and cardiac segmentation are paramount. In this study, we developed and evaluated a tool for semiautomated angulation and segmentation according to the American Heart Association 17-segment model. Methods and MaterialsThe semiautomated angulation and segmentation of the planning-computed tomography (CT) was based on an in-house developed tool requiring placement of only 4 point-markers and a rotation matrix. For angulation, 2 markers defining the cardiac long-axis were placed: at the cardiac apex and at the center of the mitral valve. A rotation matrix was derived that angulates the CT volume, resulting in the cardiac short axis. Segmentation was subsequently performed based on marking the 2 left ventricular hinge points. To evaluate reproducibility, 5 observers independently placed markers in planning CTs of 6 patients. ResultsThe root mean square of the standard deviation for the angulation and segmentation marker positions were ≤0.5 cm. The 17 segments were subsequently generated and compared between the observers resulting in a median Dice coefficient of 0.8 (interquartile range: 0.70-0.87) and a median of the mean Hausdorff distance of 0.09 cm (interquartile range: 0.05-0.17). The interquartile ranges of Euler angles α and β, determined by the angulation markers, was less than 3 degrees for all patients except one. For the γ angle, determined by the hinge point markers, the interquartile range was up to 12 degrees. ConclusionsIn this study a method for semiautomatic angulation and segmentation of the heart for cardiac radioablation according to the American Heart Association Segmented Model is presented and evaluated. Based on our results we believe that the segmentation is reproducible and that it can be used to promote communication between radiation oncology and cardiology, enables cardiology-oriented targeting and permits focused toxicity evaluations.

Dosimetric Effects of Air Cavities for MRI-Guided Online Adaptive Radiation Therapy (MRgART) of Prostate Bed after Radical Prostatectomy.

Purpose: To evaluate dosimetric impact of air cavities and their corresponding electron density correction for 0.35 tesla (T) Magnetic Resonance-guided Online Adaptive Radiation Therapy (MRgART) of prostate bed patients. Methods: Three 0.35 T MRgRT plans (anterior–posterior (AP) beam, AP–PA beams, and clinical intensity modulated radiation therapy (IMRT)) were generated on a prostate bed patient’s (Patient A) planning computed tomography (CT) with artificial rectal air cavities of various sizes (0–3 cm, 0.5 cm increments). Furthermore, two 0.35 T MRgART plans (‘Deformed’ and ‘Override’) were generated on a prostate bed patient’s (Patient B) daily magnetic resonance image (MRI) with artificial rectal air cavities of various sizes (0–3 cm, 0.5 cm increments) and on five prostate bed patient’s (Patient 1–5) daily MRIs (2 MRIs: Fraction A and B) with real air cavities. For each MRgART plan, daily MRI electron density map was obtained by deformable registration with simulation CT. In the ‘Deformed’ plan, a clinical IMRT plan is calculated on the daily MRI with electron density map obtained from deformable registration only. In the ‘Override’ plan, daily MRI and simulation CT air cavities are manually corrected and bulk assigned air and water density on the registered electron density map, respectively. Afterwards, the clinical IMRT plan is calculated. Results: For the MRgRT plans, AP and AP–PA plans’ rectum/rectal wall max dose increased with increasing air cavity size, where the 3 cm air cavity resulted in a 20%/17% and 13%/13% increase, relative to no air cavity, respectively. Clinical IMRT plan was robust to air cavity size, where dose change remained less than 1%. For the MRgART plans, daily MRI electron density maps, obtained from deformable registration with simulation CT, was unable to accurately produce electron densities reflecting the air cavities. However, for the artificial daily MRI air cavities, dosimetric change between ‘Deformed’ and ‘Override’ plan was small (<4%). Similarly, for the real daily MRI air cavities, clinical constraint changes between ‘Deformed’ and ‘Override’ plan was negligible and did not lead to change in clinical decision for adaptive planning except for two fractions. In these fractions, the ‘Override’ plan indicated that the bladder max dose and rectum V35.7 exceeded the constraint, while the ‘Deformed’ plan showed acceptable dose, although the absolute difference was only 0.3 Gy and 0.03 cc, respectively. Conclusion: Clinical 0.35 T IMRT prostate bed plans are dosimetrically robust to air cavities. MRgART air cavity electron density correction shows clinically insignificant change and is not warranted on low-field systems.

Dosimetric impact of target definition in brachytherapy for cervical cancer - Computed tomography and trans rectal ultrasound versus magnetic resonance imaging.

Magnetic Resonance Imaging (MRI) based target definition in cervix brachytherapy is limited by its availability, logistics and financial implications, therefore, use of computed tomography (CT) and Trans Rectal UltraSonography (TRUS) has been explored. The current study evaluated the dosimetric impact of CT+TRUS based target volumes as compared to gold standard MRI. Images of patients (n=21) who underwent TRUS followed by MRI and CT, were delineated with High-Risk Clinical Target Volume in CT (CTVHR-CT) and in MRI (CTVHR-MR). CTVHR-CT was drawn on CT images with TRUS assistance. For each patient, two treatment plans were made, on MRI and CT, followed by fusion and transfer of CTVHR-MR to the CT images, referred as CTVHR-MRonCT. The agreement between CTVHR-MRonCT and CTVHR-CT was evaluated for dosimetric parameters (D90, D98 and D50; Dose received by 90%, 98% and 50% of the volumes) using Bland-Altman plots, linear regression, and Pearson correlation. No statistically significant systematic difference was found between MRI and CT. Mean difference (±1.96 SD) of D90, D98 and D50 between CTVHR-MRonCT and CTVHR-CT was 2.0, 1.2 and 5.6Gy respectively. The number of patients who have met the dose constraints of D90>85Gy were 90% and 80% in MR and in CT respectively, others were in the borderline, with a minimum dose of 80Gy. The mean±SD dose-difference between MR and CT plans for bladder was significant (5±13Gy; p=0.12) for D0.1cm3, while others were statistically insignificant. CT+TRUS based delineation of CTVHR appear promising, provide useful information to optimally utilize for brachytherapy planning, however, MRI remains the gold standard.

Fully automated rigid image registration versus human registration in postoperative spine stereotactic body radiation therapy: a multicenter non-inferiority study.

To confirm the fully automated rigid image registration (A-RIR) accuracy in postoperative spine stereotactic body radiation therapy (SBRT), we conducted a multicenter non-inferiority study compared to the human rigid image registration (H-RIR). Twenty-eight metastatic cancer patients who underwent postoperative spine SBRT are enrolled—image registration (IR) of planning computed tomography (CT) and CT-myelogram for delineating the spinal cord. The adopted A-RIR workflow is a contour-focused algorithm performing a rigid registration by maximizing normalized mutual information (NMI) restricted to the data contained within the automatically extracted contour. Three radiation oncologists (ROs) from multicenters were prompted to review two blinded registrations and choose one for clinical use. Indistinguishable cases were allowed to vote equivalent, counted A-RIR side. A-RIR is considered non-inferior to H-RIR if the lower limit of the 95% confidence interval (CI) of A-RIR preferable/equivalent is greater than 0.45. We also evaluated the NMI improvement from the baseline and the translational/rotational errors between A-RIR and H-RIR. The A-RIR preferable/equivalent was selected in 21 patients (0.75, 95% CI: 0.55–0.89), demonstrating non-inferiority to H-RIR. The A-RIR’s NMI improvement was greater than H-RIR in 24 patients: the mean value ± SD was 0.225 ± 0.115 in A-RIR and 0.196 ± 0.114 in H-RIR (P < 0.001). The absolute translational error was 0.38 ± 0.31 mm. The rotational error was −0.03 ± 0.20, 0.05 ± 0.19, −0.04 ± 0.20 degrees in axial, coronal, and sagittal planes (range: −0.66–0.52). In conclusion, A-RIR shows non-inferior to H-RIR in CT and CT-myelogram registration for postoperative spine SBRT planning.

Plain Radiographs Underestimate Varus Deformity of the Tibial Plafond

Understanding plain radiograph in association with 3-dimensional (3D) morphology of the ankle is essential for treatment about varus ankle osteoarthritis (OA). The aims of this study were to investigate whether the alignment of the tibial plafond as determined on plain radiograph reflected the alignment of the tibial plafond on computed tomography (CT) in varus ankle OA and whether the alignment of the tibial plafond changed as the OA progressed. The 3D CT and plain radiographs from 101 ankles with varus ankle OA were analyzed and compared with 40 ankles in control group. The tibial plafond was assessed in the coronal and sagittal planes using 3D CT. The medial angle between the vertical line and the tibial plafond was measured on 3 different coronal plane CT images which was anterior, middle and posterior area of the tibial plafond. The medial distal tibial angle on plain radiograph reflected the posterior area of the tibial plafond on CT. The amount of varus angulation on CT was larger in anterior and middle area of the tibial plafond than the posterior area. There was a difference in the degree of varus of the tibial plafond between control group and OA patients; however, there was no difference among patients in different stages of varus ankle OA. Weightbearing plain radiographs underestimate the varus deformity in anterior and middle area of the tibial plafond and there is no significant difference in deformity of the tibial plafond among patients in different stages of varus ankle OA.

Point-Based Brachytherapy in Cervical Cancer With Limited Residual Disease: A Low- and Middle-Income Country Experience in the Era of Magnetic Resonance-Guided Adaptive Brachytherapy.

PURPOSETo evaluate the clinical outcomes in patients with cervical cancer with limited residual disease at brachytherapy (BT) treated with point-based dose prescription.METHODSPatients with locally advanced squamous cell carcinoma of the cervix treated with computed tomography (CT)-based intracavitary BT were considered for analysis. Patients with good response to external beam radiotherapy and limited residual disease suitable for intracavitary BT alone were included. Postapplication CT scans were performed before each fraction and individual plans were made for each session. The dose per fraction was 9Gy high dose rate, prescribed to point-A. Two sessions were planned, 1 week apart. The organs at risk were contoured, and cumulative dose-volume histograms were computed. Local control, pelvic control, disease-free survival, and overall survival were evaluated and late toxicities were documented.RESULTSFour hundred ninety patients were included. Overall, 79.8% had International Federation of Gynecology and Obstetrics (FIGO) stage IB2 to IIB disease and 20.2% had stage III to IVA disease. Median dose at point A (EQD210Gy) was 74.4 Gy (interquartile range [IQR] 72.3-74.5 Gy) and median D2cc (EQD23Gy) for bladder, rectum, and sigmoid were 82.5 Gy (IQR, 65.5-90.8 Gy), 66.5 Gy (IQR, 60.7-75.7 Gy), and 54.1 Gy (IQR, 50.5-77.3 Gy), respectively. At a median follow-up of 62 (IQR, 33-87) months, the 5-year local and pelvic control rates were 90.1% and 88.3%, respectively. The 5-year disease-free survival was 80% and overall survival was 88%. Rates of grade 3-4 bladder and rectosigmoid toxicities were 6.93% and 4.08%, respectively.CONCLUSIONIn patients with limited residual disease at BT, point-based dose prescription with CT planning results in good local control and acceptable toxicity. In a resource-constrained setting, patients may be triaged to receive point-based BT or magnetic resonance imaging–guided adaptive BT depending on the extent of residual disease.

Modern Imaging Techniques and Their Role in Contact Radiation Therapy (Brachytherapy) Planning

The paper considers an algorithm for the diagnostic study of patients with cancer of different localization, the possibility and feasibility of involving imaging techniques in radiation therapy and brachytherapy (BT) planning. The most widely used ultrasound in BT planning does not exclude a subjective assessment of the boundaries of the tumor and organs at risk, as well as the inaccuracies caused by endostatic devices. Magnetic resonance imaging (MRI) provides a high level of achievement of the criteria necessary for BT planning, but it has financial constraints and the need for individual selection of research conditions. Computed tomography (CT) is the most effective technique for visualizing the tumor, endostatic devices, and organs at risk for BT 3D planning. The involvement of MRI and positron emission tomography with CT in BT planning is a promising area that requires equipping with a mathematical tool for double and triple contouring of the tumor and organs at risk and for defining protection priorities. The prescribed and used focal dose should be controlled by direct dosimetry methods to ensure quality assurance.

Dual-layer spectral CT for proton, helium, and carbon ion beam therapy planning of brain tumors.

Pretreatment computed tomography (CT) imaging is an essential component of the particle therapy treatment planning chain. Treatment planning and optimization with charged particles require accurate and precise estimations of ion beam range in tissues, characterized by the stopping power ratio (SPR). Reduction of range uncertainties arising from conventional CT‐number‐to‐SPR conversion based on single‐energy CT (SECT) imaging is of importance for improving clinical practice. Here, the application of a novel imaging and computational methodology using dual‐layer spectral CT (DLCT) was performed toward refining patient‐specific SPR estimates.A workflow for DLCT‐based treatment planning was devised to evaluate SPR prediction for proton, helium, and carbon ion beam therapy planning in the brain. DLCT‐ and SECT‐based SPR predictions were compared in homogeneous and heterogeneous anatomical regions. This study included eight patients scanned for diagnostic purposes with a DLCT scanner. For each patient, four different treatment plans were created, simulating tumors in different parts of the brain.For homogeneous anatomical regions, mean SPR differences of about 1% between the DLCT‐ and SECT‐based approaches were found. In plans of heterogeneous anatomies, relative (absolute) proton range shifts of 0.6% (0.4 mm) in the mean and up to 4.4% (2.1 mm) at the distal fall‐off were observed. In the investigated cohort, 12% of the evaluated organs‐at‐risk (OARs) presented differences in mean or maximum dose of more than 0.5 Gy (RBE) and up to 6.8 Gy (RBE) over the entire treatment. Range shifts and dose differences in OARs between DLCT and SECT in helium and carbon ion treatment plans were similar to protons.In the majority of investigated cases (75th percentile), SECT‐ and DLCT‐based range estimations were within 0.6 mm. Nonetheless, the magnitude of patient‐specific range deviations between SECT and DLCT was clinically relevant in heterogeneous anatomical sites, suggesting further study in larger, more diverse cohorts. Results indicate that patients with brain tumors may benefit from DLCT‐based treatment planning.

Radiogenomic and Deep Learning Network Approaches to Predict KRAS Mutation and Microsatellite Instability Status From Radiotherapy Plan

<h3>Purpose/Objective(s)</h3> We aimed to investigate the role of radiogenomic and deep learning approaches in predicting the KRAS mutation and microsatellite instability (MSI) status of a tumor using the radiotherapy planning computed tomography (CT) images of 110 patients who received neoadjuvant concurrent chemoradiation for locally advanced rectal cancer. <h3>Materials/Methods</h3> After surgical resection, 30 (27.3%) tumors were found to have KRAS mutation and 2 (1.8%) had MSI-high status. We adopted both the radiogenomic and deep learning approaches to predict KRAS mutation and MSI. A total of 378 texture features were extracted from the boost clinical target volume (CTV) in the radiotherapy planning CT images. The least absolute shrinkage and selection operator method was performed to select the features associated with KRAS and MSI status. Tuning parameter (λ) was determined by 10-fold cross validation. The radiogenomic score was calculated by combining the coefficients of the selected features. Meanwhile, we developed a deep learning network based on the three-dimensional input of the CTV. Performance of models was internally validated. <h3>Results</h3> The predictive ability of the radiogenomic score model revealed AUCs of 0.73 for KRAS mutation and 0.99 for MSI status, whereas that for the deep learning model demonstrated worse performance, with AUCs of 0.63 for KRAS and 0.58 for MSI. <h3>Conclusion</h3> Compared with the deep learning network model, the radiogenomic score model was a more feasible approach to predict KRAS and MSI status. These results should be externally validated on a larger dataset

Automatic Contouring of the Clinical Target Volume (CTV) for Cervical Cancer Adjuvant Radiotherapy Using Deep Learning Algorithm

The aim of this study was to develop a deep learning model for automated delineation of the clinical target volume (CTV) for cervical cancer adjuvant radiotherapy after radical hysterectomy.A total of 263 planning-computed tomography (CT) scans of postoperative radiotherapy in cervical cancer patients after radical hysterectomy treated at our institution were used to train and test the automatic contouring models. Among these sets, 236 were used for training, 27 for testing. In the study, three models were investigated: CMU-Net, V-net (3D neural network) and Unet++ (2D neural network). Multi-U-Net (CMU-Net), a novel segmentation approach, recognized the upper and lower bounds of CTV and then segmented them accurately. Dice similarity coefficient (DSC), Hausdorff distances (HD), Average symmetric surface distance (ASD) were assessed and compared between models and manual contours for testing sets.The mean DSC, HD and ASD of V-Net, Unet++, CMU-Net were 86.39, 85.74, 92.16; 5.97, 5.35, 2.72; 0.89, 0.76, and 0.52, respectively.Among the three models, CMU-Net provided the best in automatic contouring of the CTV for cervical cancer adjuvant radiotherapy, and could help physicians to further reduce the time cost in the clinical practice.

Deep learning model for automatic contouring of cardiovascular substructures on radiotherapy planning CT images: Dosimetric validation and reader study based clinical acceptability testing

Background and purposeLarge radiotherapy (RT) planning imaging datasets with consistently contoured cardiovascular structures are essential for robust cardiac radiotoxicity research in thoracic cancers. This study aims to develop and validate a highly accurate automatic contouring model for the heart, cardiac chambers, and great vessels for RT planning computed tomography (CT) images that can be used for dose–volume parameter estimation. Materials and methodsA neural network model was trained using a dataset of 127 expertly contoured planning CT images from RT treatment of locally advanced non-small-cell lung cancer (NSCLC) patients. Evaluation of geometric accuracy and quality of dosimetric parameter estimation was performed on 50 independent scans with contrast and without contrast enhancement. The model was further evaluated regarding the clinical acceptability of the contours in 99 scans randomly sampled from the RTOG-0617 dataset by three experienced radiation oncologists. ResultsMedian surface dice at 3 mm tolerance for all dedicated thoracic structures was 90% in the test set. Median absolute difference between mean dose computed with model contours and expert contours was 0.45 Gy averaged over all structures. The mean clinical acceptability rate by majority vote in the RTOG-0617 scans was 91%. ConclusionThis model can be used to contour the heart, cardiac chambers, and great vessels in large datasets of RT planning thoracic CT images accurately, quickly, and consistently. Additionally, the model can be used as a time-saving tool for contouring in clinic practice.

Computed Tomography-Based Assessment of Transvalvular Pressure Gradient in Aortic Stenosis.

Background: In patients with aortic stenosis, computed tomography (CT) provides important information about cardiovascular anatomy for treatment planning but is limited in determining relevant hemodynamic parameters such as the transvalvular pressure gradient (TPG).Purpose: In the present study, we aimed to validate a reduced-order model method for assessing TPG in aortic stenosis using CT data.Methods: TPGCT was calculated using a reduced-order model requiring the patient-specific peak-systolic aortic flow rate (Q) and the aortic valve area (AVA). AVA was determined by segmentation of the aortic valve leaflets, whereas Q was quantified based on volumetric assessment of the left ventricle. For validation, invasively measured TPGcatheter was calculated from pressure measurements in the left ventricle and the ascending aorta. Altogether, 84 data sets of patients with aortic stenosis were used to compare TPGCT against TPGcatheter.Results: TPGcatheter and TPGCT were 50.6 ± 28.0 and 48.0 ± 26 mmHg, respectively (p = 0.56). A Bland–Altman analysis revealed good agreement between both methods with a mean difference in TPG of 2.6 mmHg and a standard deviation of 19.3 mmHg. Both methods showed good correlation with r = 0.72 (p < 0.001).Conclusions: The presented CT-based method allows assessment of TPG in patients with aortic stenosis, extending the current capabilities of cardiac CT for diagnosis and treatment planning.

Dosimetry Comparison of Palliative Radiation Plans Generated From Available Diagnostic CT Images Versus Dedicated CT Simulation for Inpatients.

IntroductionThe morbidity sequelae of advanced cancer are often irreversible. Early palliative radiation can prevent, delay, and even improve these consequences. Treatment may be delayed due to a packed computed tomography (CT) simulation schedule or other logistics, including the cost and burden of arranging ambulance transportation when radiation centers are off-site.ObjectivesThe primary objective was to determine the feasibility of using a recent diagnostic CT scan in lieu of a dedicated simulation CT to generate an adequate plan without sacrificing dosimetric goals and subsequent efficacy or tolerability. Secondary objectives included how much the lesion has grown, and how much earlier treatment could start if planned on a diagnostic CT scan.Materials/MethodsFor each inpatient treated with palliative radiation, a prior recent diagnostic CT scan was imported into the RayStation (RaySearch Laboratories, Stockholm, Sweden) planning system. From these diagnostic scans, planning treatment volumes (PTV) and organs at risk (OAR) were contoured using the same technique as the patient’s actual treatment. The primary outcome was to compare both the PTV coverage and OAR dose between the plan generated from the diagnostic CT compared to that from the simulation CT. Our secondary outcomes include the mean time between CT simulation and first treatment, change in tumor volume between diagnostic scan and CT simulation, and the hottest 1% of each plan (D1).ResultsBetween May and August 2019, a total of 22 inpatients were treated palliatively. Of those 22 patients, 10 patients (ages 32-92 years, median 64.5 years, 50% spine) met study criteria and had a diagnostic CT scan that was obtained within 14 days of simulation CT that was also compatible with our planning software. In the plans that were delivered, a mean of 98.8% (range 94.4-100%) of PTV was covered by at least 95% prescription dose. In the diagnostic CT plans, a mean of 95.4% (range 84.5-100%) of PTV was covered by at least 95% prescription dose. The difference between plans trended towards significance (p=0.061). When looking at patients receiving treatment to the spine or having a diagnostic CT within four days of the simulation CT, there was no statistically significant difference between the two plans (p=0.032 and 0.030, respectively). The OARs received, on average, 1.4% less mean radiation dose in the hypothetical plans (p=0.911). All OAR constraints were met in both groups. The mean time between diagnostic CT and CT simulation was 5.9 days and between CT simulation and first treatment was 1.9 days (range 0-5 days). The mean change in tumor volume was 22.64% smaller in the diagnostic CT scan plan. The D1 was an average 1% hotter in the hypothetical plans (p=0.16).ConclusionIn hospitalized patients with an indication for palliative radiation, treatment planning on a pre-existing recent diagnostic CT scan produces comparable dose distributions without increases in dose to OARs when compared to the use of CT simulation scans, particularly for the treatment of the spine or when a very recent diagnostic CT is available. Bypassing CT simulation in select cases allows for earlier delivery of radiation with less patient and logistical burden. In combination with daily image guidance, this may translate to more timely delivery of radiation, less cost and burden to critically ill patients, and improved palliative benefit.

Prognostic Impact of Myocardial Extracellular Volume Fraction Assessment Using Dual-Energy Computed Tomography in Patients Treated With Aortic Valve Replacement for Severe Aortic Stenosis.

BackgroundMyocardial extracellular volume fraction (ECV), measured by cardiac magnetic resonance imaging, is a useful prognostic marker for patients who have undergone aortic valve replacement (AVR) for aortic stenosis. However, the prognostic significance of ECV measurements based on computed tomography (CT) is unclear. This study evaluated the association between ECV measured with dual‐energy CT and clinical outcomes in patients with aortic stenosis who underwent transcatheter or surgical AVR.Methods and ResultsWe retrospectively enrolled 95 consecutive patients (age, 84.0±5.0 years; 75% women) with severe aortic stenosis who underwent preprocedural CT for transcatheter AVR planning. ECV was measured using iodine density images obtained by delayed enhancement dual‐energy CT. The primary end point was a composite outcome of all‐cause death and hospitalization for heart failure after AVR. The mean ECV measured with CT was 28.1±3.8%. During a median follow‐up of 2.6 years, 22 composite outcomes were observed, including 15 all‐cause deaths and 11 hospitalizations for heart failure. In Kaplan‐Meier analysis, the high ECV group (≥27.8% [median value]) had significantly higher rates of composite outcomes than the low ECV group (<27.8%) (log‐rank test, P=0.012). ECV was the only independent predictor of adverse outcomes on multivariable Cox regression analysis (hazards ratio, 1.25; 95% CI, 1.10‒1.41; P<0.001).ConclusionsMyocardial ECV measured with dual‐energy CT in patients who underwent aortic valve intervention was an independent predictor of adverse outcomes after AVR.

高度貧血を契機に診断されたステントグラフト内挿術後腹部大動脈瘤：十二指腸瘻の1例(Secondary aorto–duodenal fistula following endovascular abdominal aortic aneurysm repair diagnosed by severe anemia)

要旨腹部大動脈ステントグラフト（EVAR）は腹部大動脈瘤（AAA）に対する主な治療として位置づけられ，とくに開腹歴をもつ症例群に対する加療として，低侵襲性の観点で積極的に施行されている。EVAR後に発生するエンドリークは，治療にも関わらず瘤径拡大の主原因であり，周囲臓器との瘻孔や瘤破裂の発生などEVAR関連合併症が発生しうる。EVAR後の大動脈腸管瘻（AEF）の発生は非常に稀であるが，致命的な合併症として知られる。我々は，大腸癌で開腹歴をもつ70歳代女性の拡大傾向のある嚢状AAA対してEVARを施行したが，瘤拡大が持続し十二指腸に穿破した症例を経験した。EVAR術後6か月，16か月後にそれぞれエンドリークによる瘤径拡大に対する追加加療を行ったが，瘤径の制御が困難であった。術後20か月後に高度貧血に対する精査のために施行された上部消化管内視鏡検査の結果，AAAが十二指腸水平脚と交通し出血している所見を認め，AEFの診断となり緊急手術を行った。周術期死亡率の高い本症において，手術侵襲が大きくなることが予想される症例に対して，ステントグラフトを抜去せず瘤縫縮術を選択した1例を報告した。EVAR後の瘤拡大関連イベントに救急医が関わるケースが増えてくることが予想され，AEFの合併を念頭に置くべきである。

A novel view of computed tomography images similar to the visual field of otologic surgeons.

ObjectivesIn preparation for endoscopic sinus surgery (ESS), the most important computed tomography (CT) image for otolaryngologists is the coronal plane image because it has a viewpoint similar to that of the surgical visual field. Contrastingly, otologic surgeons refer to axial and coronal plane images before ear surgery and must imagine the anatomical structure of the temporal bone by reconstructing three‐dimensional (3D) images in their minds. We propose a “surgical position view (SPV) image,” a novel viewpoint of CT images that enables otologic surgeons to see a perspective similar to the surgical visual field.MethodSagittal plane CT images of the temporal bone were created from axial plane images with multi‐planar reconstruction (MPR). Then, the SPV image was obtained by rotating it 90° to the supine position. The entire process can be performed anywhere in the hospital within 1 minute using the electronic medical record computer's image viewer.ResultsSPV images show anatomical structures of the temporal bone, external ear canal, mastoid cavity, sigmoid vein, facial nerve, ossicles, and cochlea, in a similar view to the actual ear surgery. Soft tissue such as cholesteatoma is depicted in the same concentration as the normal CT image.ConclusionThe SPV image enables an otologic surgeon to see the temporal bone CT image from the actual ear surgery viewpoint simply and quickly. It helps to visualize the 3D anatomical structure of the temporal bone and can be useful for ear surgery planning.Level of evidence5

Integrated Custom Composite Polyetheretherketone/Carbon fiber (PEEK/CF) Vertebral Body Replacement (VBR) in the Treatment of Bone Tumors of the Spine: A Preliminary Report From a Multicenter Study.

Retrospective, multicenter chart, and radiologic review. To present the first case series of bone tumors of the spine surgically reconstructed with a new custom, fully radiolucent, polyetheretherketone/carbon fiber (PEEK/CF) vertebral body replacement (VBR) integrated system. Surgical resections of spinal tumors result in large defects and local recurrence remains a concern. Current titanium-based implants adversely affects postoperative imaging, directly affects ability to identify tumor recurrence, and for delivery of radiotherapy treatments. PEEK/CF spinal implants allows for improved tumor surveillance, precise pre-radiation Computed Tomography planning, and reduces interference with post-reconstructive adjuvant radiotherapy. Thirteen patients with spinal tumors underwent vertebral body resection and reconstruction with an integrated, fully radiolucent, custom PEEK/CF vertebral body replacement, and radiolucent posterior PEEK/CF screw-rod system and/or radiolucent anterior PEEK/CF plate system. Clinical and radiographic data were tabulated. Need for adjuvant radiotherapy determined based on final tissue histology and extent of surgical margins. Postoperative surveillance imaging were reviewed for local tumor recurrence. The ability to integrate the PEEK/CF VBR connected to either the posterior screw-rod system, or anterior plate system provided immediate stability. The VBR was placed directly on cancellous vertebral body surface in 46.2% of cases. Loosening of the distal, or proximal, aspect of posterior system was seen in 15.4% of cases. There was no clinical or radiographic evidence of VBR migration and subsidence at latest follow up. Local recurrence occurred in one (7.7%) patient. This is the first series to describe the use of a fully-radiolucent, integrated, PEEK/CF implant system for spinal tumor reconstruction. The use of a PEEK/CF VBR system integrated to either the anterior plate, or posterior screw-rod system is feasible and allows for superior postoperative surveillance imaging and effective delivery of postoperative adjuvant radiotherapy.Level of Evidence: 4.

Radiogenomic and Deep Learning Network Approaches to Predict KRAS Mutation from Radiotherapy Plan CT.

We aimed to investigate the role of radiogenomic and deep learning approaches in predicting the KRAS mutation status of a tumor using radiotherapy planning computed tomography (CT) images in patients with locally advanced rectal cancer. After surgical resection, 30 (27.3%) of 110 patients were found to carry a KRAS mutation. For the radiogenomic model, a total of 378 texture features were extracted from the boost clinical target volume (CTV) in the radiotherapy planning CT images. For the deep learning model, we constructed a simple deep learning network that received a three-dimensional input from the CTV. The predictive ability of the radiogenomic score model revealed an AUC of 0.73 for KRAS mutation, whereas the deep learning model demonstrated worse performance, with an AUC of 0.63. The radiogenomic score model was a more feasible approach to predict KRAS status than the deep learning model.

A Deep Unsupervised Learning Model for Artifact Correction of Pelvis Cone-Beam CT.

PurposeIn recent years, cone-beam computed tomography (CBCT) is increasingly used in adaptive radiation therapy (ART). However, compared with planning computed tomography (PCT), CBCT image has much more noise and imaging artifacts. Therefore, it is necessary to improve the image quality and HU accuracy of CBCT. In this study, we developed an unsupervised deep learning network (CycleGAN) model to calibrate CBCT images for the pelvis to extend potential clinical applications in CBCT-guided ART.MethodsTo train CycleGAN to generate synthetic PCT (sPCT), we used CBCT and PCT images as inputs from 49 patients with unpaired data. Additional deformed PCT (dPCT) images attained as CBCT after deformable registration are utilized as the ground truth before evaluation. The trained uncorrected CBCT images are converted into sPCT images, and the obtained sPCT images have the characteristics of PCT images while keeping the anatomical structure of CBCT images unchanged. To demonstrate the effectiveness of the proposed CycleGAN, we use additional nine independent patients for testing.ResultsWe compared the sPCT with dPCT images as the ground truth. The average mean absolute error (MAE) of the whole image on testing data decreased from 49.96 ± 7.21HU to 14.6 ± 2.39HU, the average MAE of fat and muscle ROIs decreased from 60.23 ± 7.3HU to 16.94 ± 7.5HU, and from 53.16 ± 9.1HU to 13.03 ± 2.63HU respectively.ConclusionWe developed an unsupervised learning method to generate high-quality corrected CBCT images (sPCT). Through further evaluation and clinical implementation, it can replace CBCT in ART.

Understanding the Aorta-Spine Relation in Idiopathic Scoliosis: Value of Noncontrast CT-Derived Curved Coronal Reformats and 3D Volume Images.

Investigating axial position and longitudinal bending of the aorta in relation to spine curvature in adolescent idiopathic scoliosis patients could help surgeons in planning of spine surgeries. Noncontrast computed tomography (CT) scans of 27 consecutive patients with adolescent idiopathic scoliosis (19 right and 8 left curves) and 16 control subjects were retrospectively reviewed. Using semiautomated software, centerline was drawn along the descending aorta, and curved reformat was generated. Aorta tortuosity index (TI) was calculated as (centerline length/straight line distance) - 1 × 100. The spine centerline was drawn from T1 to L5, and curve index (CI) was similarly calculated. The aorta centerline angle was measured. Apical vertebral-rotation angle and multilevel aorto-vertebral angles were measured on axial CT. Three-dimensional volume-rendered images of the aorta were generated using a manual region grow function. Mean (± standard deviation) Cobb's angle was 63.8 ± 34.6°. The spine CI of patients (9.7 ± 7.11) was significantly higher than controls (0.28 ± 0.22), P = .00001. Aorta TI in scoliosis was significantly higher than controls (6.4 ± 7.2 versus 0.6 ± 0.5, P = .0001). The aorta centerline angle was steeper in scoliosis than controls (140 ± 26.8° versus 170 ± 3.6°). Correlations were excellent between the aorta TI and each of Cobb's angle, spine CI, and vertebral rotation angle (r = 0.851 to 0.867, all P < .001). Aorto-vertebral angles were significantly different between right scoliosis and left scoliosis patients and control groups at T6, T7, T8, L2, and L3 levels. Aortic curvature increases in proportion to the degree of scoliosis. The aorta follows the concavity of scoliosis in right and left curves. In the axial CT plane, the aorta in both right and left scoliosis is maximally rotated away from its normal position at T7 and is closest to its normal position at T11 to T12. Quantitative evaluation of aortic curvature combined with preoperative reconstructed CT images could be beneficial for surgeons in planning of spine surgeries.