Dynamic CT Imaging Research Articles

The Utility of Dynamic CT Imaging With Pre- and Post-Valsalva Maneuvers for Confirmation of Suspected Orbital Varices.

The Utility of Dynamic CT Imaging With Pre- and Post-Valsalva Maneuvers for Confirmation of Suspected Orbital Varices.

New full-counts phase-matched data-driven gated (DDG) PET/CT.

Data-driven gated (DDG) PET has gained clinical acceptance and has been shown to match or outperform external-device gated (EDG) PET. However, in most clinical applications, DDG PET is matched with helical CT acquired in free breathing (FB) at a random respiratory phase, leaving registration, and optimal attenuation correction (AC) to chance. Furthermore, DDG PET requires additional scan time to reduce image noise as it only preserves 35%-50% of the PET data at or near the end-expiratory phase of the breathing cycle. A new full-counts, phase-matched (FCPM) DDG PET/CT was developed based on a low-dose cine CT to improve registration between DDG PET and DDG CT, to reduce image noise, and to avoid increasing acquisition times in DDG PET. A new DDG CT was developed for three respiratory phases of CT images from a low dose cine CT acquisition of 1.35mSv for a coverage of about 15.4cm: end-inspiration (EI), average (AVG), and end-expiration (EE) to match with the three corresponding phases of DDG PET data: -10% to 15%; 15% to 30%, and 80% to 90%; and 30% to 80%, respectively. The EI and EE phases of DDG CT were selected based on the physiological changes in lung density and body outlines reflected in the dynamic cine CT images. The AVG phase was derived from averaging of all phases of the cine CT images. The cine CT was acquired over the lower lungs and/or upper abdomen for correction of misregistration between PET and FB CT as well as DDG PET and FB CT. The three phases of DDG CT were used for AC of the corresponding phases of PET. After phase-matched AC of each PET dataset, the EI and AVG PET data were registered to the EE PET data with deformable image registration. The final result was FCPM DDG PET/CT which accounts for all PET data registered at the EE phase. We applied this approach to 14 18F-FDG lung cancer patient studies acquired at 2min/bed position on the GE Discovery MI (25-cm axial FOV) and evaluated its efficacy in improved quantification and noise reduction. Relative to static PET/CT, the SUVmax increases for the EI, AVG, EE, and FCPM DDG PET/CT were 1.67±0.40, 1.50±0.28, 1.64±0.36, and 1.49±0.28, respectively. There were 10.8% and 9.1% average decreases in SUVmax from EI and EE to FCPM DDG PET/CT, respectively. EI, AVG, and EE DDG PET/CT all maintained increased image noise relative to static PET/CT. However, the noise levels of FCPM and static PET were statistically equivalent, suggesting the inclusion of all counts was able to decrease the image noise relative to EI and EE DDG PET/CT. A new FCPM DDG PET/CT has been developed to account for 100% of collected PET data in DDG PET applications. Image noise in FCPM is comparable to static PET, while small decreases in SUVmax were also observed in FCPM when compared to either EI or EE DDG PET/CT.

Dynamic X-ray imaging with screen-printed perovskite CMOS array.

High performance X-ray detector with ultra-high spatial and temporal resolution are crucial for biomedical imaging. This study reports a dynamic direct-conversion CMOS X-ray detector assembled with screen-printed CsPbBr3, whose mobility-lifetime product is 5.2 × 10-4 cm2 V-1 and X-ray sensitivity is 1.6 × 104 µC Gyair-1 cm-2. Samples larger than 5 cm[Formula: see text]10 cm can be rapidly imaged by scanning this detector at a speed of 300 frames per second along the vertical and horizontal directions. In comparison to traditional indirect-conversion CMOS X-ray detector, this perovskite CMOS detector offers high spatial resolution (5.0 lp mm-1) X-ray radiographic imaging capability at low radiation dose (260 nGy). Moreover, 3D tomographic images of a biological specimen are also successfully reconstructed. These results highlight the perovskite CMOS detector's potential in high-resolution, large-area, low-dose dynamic biomedical X-ray and CT imaging, as well as in non-destructive X-ray testing and security scanning.

Four-dimensional analysis of aortic root motion in normal population using retrospective multiphase computed tomography.

Aortic root motion is suspected to contribute to proximal aortic dissection. While motion of the aorta in four dimensions can be traced with real-time imaging, displacement and rotation in quantitative terms remain unknown. The hypothesis was to show feasibility of quantification of three-dimensional aortic root motion from dynamic CT imaging. Dynamic CT images of 40 patients for coronary assessment were acquired using a dynamic protocol. Scans were ECG-triggered and segmented in 10 time-stepped phases (0-90%) per cardiac cycle. With identification of the sinotubular junction (STJ), a patient-specific co-ordinate system was created with the z-axis (out-of-plane) parallel to longitudinal direction. The left and right coronary ostia were traced at each time-step to quantify downward motion in reference to the STJ plane, motion within the STJ plane (in-plane), and the degree of rotation. Enrolled individuals had an age of 65 ± 12, and 14 were male (35%). The out-of-plane motion was recorded with the largest displacement of 10.26 ± 2.20 and 8.67 ± 1.69 mm referenced by left and right coronary ostia, respectively. The mean downward movement of aortic root was 9.13 ± 1.86 mm. The largest in-plane motion was recorded at 9.17 ± 2.33 mm and 6.51 ± 1.75 mm referenced by left and right coronary ostia, respectively. The largest STJ in-plane motion was 7.37 ± 1.96 mm, and rotation of the aortic root was 11.8 ± 4.60°. In vivo spatial and temporal displacement of the aortic root can be identified and quantified from multiphase ECG-gated contrast-enhanced CT images. Knowledge of normal 4D motion of the aortic root may help understand its biomechanical impact in patients with aortopathy and pre- and post-surgical or transcatheter aortic valve replacement.

Prediction of preoperative microvascular invasion by dynamic radiomic analysis based on contrast-enhanced computed tomography.

Microvascular invasion (MVI) is a common complication of hepatocellular carcinoma (HCC) surgery, which is an important predictor of reduced surgical prognosis. This study aimed to develop a fully automated diagnostic model to predict pre-surgical MVI based on four-phase dynamic CT images. A total of 140 patients with HCC from two centers were retrospectively included (training set, n = 98; testing set, n = 42). All CT phases were aligned to the portal venous phase, and were then used to train a deep-learning model for liver tumor segmentation. Radiomics features were extracted from the tumor areas of original CT phases and pairwise subtraction images, as well as peritumoral features. Lastly, linear discriminant analysis (LDA) models were trained based on clinical features, radiomics features, and hybrid features, respectively. Models were evaluated by area under curve (AUC), accuracy, sensitivity, specificity, positive and negative predictive values (PPV and NPV). Overall, 86 and 54 patients with MVI- (age, 55.92 ± 9.62 years; 68 men) and MVI+ (age, 53.59 ± 11.47 years; 43 men) were included. Average dice coefficients of liver tumor segmentation were 0.89 and 0.82 in training and testing sets, respectively. The model based on radiomics (AUC = 0.865, 95% CI: 0.725-0.951) showed slightly better performance than that based on clinical features (AUC = 0.841, 95% CI: 0.696-0.936). The classification model based on hybrid features achieved better performance in both training (AUC = 0.955, 95% CI: 0.893-0.987) and testing sets (AUC = 0.913, 95% CI: 0.785-0.978), compared with models based on clinical and radiomics features (p-value < 0.05). Moreover, the hybrid model also provided the best accuracy (0.857), sensitivity (0.875), and NPV (0.917). The classification model based on multimodal intra- and peri-tumoral radiomics features can well predict HCC patients with MVI.

Dynamic CT scanning of the knee: Combining weight bearing with real-time motion acquisition

BackgroundImaging the lower limb during weight-bearing conditions is essential to acquire advanced functional joint information. The horizontal bed position of CT systems however hinders this process. The purpose of this study was to validate and test a device to simulate realistic knee weight-bearing motion in a horizontal position during dynamic CT acquisition and process the acquired images. Methods“Orthostatic squats” was compared to “Horizontal squats” on a device with loads between 35% and 55% of the body weight (%BW) in 20 healthy volunteers. Intraclass Correlation Coefficient (ICC), and standard error of measurement (SEM), were computed as measures of the reliability of curve kinematic and surface EMG (sEMG) data. Afterwards, the device was tested during dynamic CT acquisitions on three healthy volunteers and three patients with patellofemoral pain syndrome. The respective images were processed to extract Tibial-Tuberosity Trochlear-Groove distance, Bisect Offset and Lateral Patellar Tilt metrics. ResultsFor sEMG, the highest average ICCs (SEM) of 0.80 (6.9), was found for the load corresponding to 42%BW. Kinematic analysis showed ICCs were the highest for loads of 42%BW during the eccentric phase (0.79–0.87) and from maximum flexion back to 20° (0.76). The device proved to be safe and reliable during the acquisition of dynamic CT images and the three metrics were computed, showing preliminary differences between healthy and pathological participants. ConclusionsThis device could simulate orthostatic squats in a horizontal position with good reliability. It also successfully provided dynamic CT scan images and kinematic parameters of healthy and pathological knees during weight-bearing movement.

Dynamic CT Imaging in the Laboratory: Characterization of Pore Filling Events in Geological Materials.

Dynamic CT Imaging in the Laboratory: Characterization of Pore Filling Events in Geological Materials.

Low-dose dynamic cerebral perfusion CT reconstruction based on voxel-level TAC correction (VTC)

Dynamic cerebral perfusion computed tomography (DCP-CT) is an advanced imaging technique that helps in the clinical diagnosis of cerebrovascular diseases (CVDs). However, radiation dose deposition during repeated CT scans seriously limits its clinical application. Effective DCP-CT imaging method based on low-dose protocol is needed. A regularized least-squares method with high interpretability based on voxel-level time-attenuation curve (TAC) correction (VTC) is proposed in this study for low-dose DCP-CT image reconstruction. The theory of third-order Hermite interpolation (THI) is applied to voxel-level TAC correction during dynamic images reconstruction. The peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) are used to quantitatively evaluate the proposed method in terms of imaging accuracy and noise reduction, while hemodynamic maps, including cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transition time (MTT), are calculated to validate its ability to restore hemodynamic parameters. It is proven that the proposed VTC method for low-dose DCP-CT imaging has better performance than several state-of-the-art dynamic CT imaging methods. It can be expected that the VTC method can play an important role in the promotion of the clinical application of DCP-CT for the diagnosis of CVD.

Assessing carpal kinematics following scapholunate interosseous ligament injury ex vivo using four-dimensional dynamic computed tomography

BackgroundScapholunate interosseous ligament injuries are prevalent and often challenging to diagnose radiographically. Four-dimensional CT allows visualization of carpal bones during motion. We present a cadaveric model of sequential ligamentous sectionings (“injuries”) to quantify their effects on interosseous proximities at the radioscaphoid joint and scapholunate interval. We hypothesized that injury, wrist position, and their interaction affect carpal arthrokinematics. MethodsEight cadaveric wrists were moved through flexion-extension and radioulnar deviation after injuries. Dynamic CT images of each motion were acquired in each injury condition using a second-generation dual-source CT scanner. Carpal osteokinematics were used to calculate arthrokinematic interosseous proximity distributions during motion. Median interosseous proximities were normalized and categorized by wrist position. Linear mixed-effects models and marginal means tests were used to compare distributions of median interosseous proximities. FindingsThe effect of wrist position was significant for both flexion-extension and radioulnar deviation at the radioscaphoid joint; the effect of injury was significant for flexion-extension at the scapholunate interval; and the effect of their interaction was significant for radioulnar deviation at the scapholunate interval. Across wrist positions, radioscaphoid median interosseous proximities were less able to distinguish injury conditions versus scapholunate proximities. Median interosseous proximities at the scapholunate interval are majoritively able to detect differences between less (Geissler I-III) versus more (Geissler IV) severe injuries when the wrist is flexed, extended, and ulnarly-deviated. InterpretationDynamic CT enhances our understanding of carpal arthrokinematics in a cadaveric model of SLIL injury. Scapholunate median interosseous proximities in flexion, extension, and ulnar deviation best demonstrate ligamentous integrity.

Impact of wall displacements on the large-scale flow coherence in ascending aorta

In the context of aortic hemodynamics, uncertainties affecting blood flow simulations hamper their translational potential as supportive technology in clinics. Computational fluid dynamics (CFD) simulations under rigid-walls assumption are largely adopted, even though the aorta contributes markedly to the systemic compliance and is characterized by a complex motion. To account for personalized wall displacements in aortic hemodynamics simulations, the moving-boundary method (MBM) has been recently proposed as a computationally convenient strategy, although its implementation requires dynamic imaging acquisitions not always available in clinics.In this study we aim to clarify the real need for introducing aortic wall displacements in CFD simulations to accurately capture the large-scale flow structures in the healthy human ascending aorta (AAo). To do that, the impact of wall displacements is analyzed using subject-specific models where two CFD simulations are performed imposing (1) rigid walls, and (2) personalized wall displacements adopting a MBM, integrating dynamic CT imaging and a mesh morphing technique based on radial basis functions. The impact of wall displacements on AAo hemodynamics is analyzed in terms of large-scale flow patterns of physiological significance, namely axial blood flow coherence (quantified applying the Complex Networks theory), secondary flows, helical flow and wall shear stress (WSS).From the comparison with rigid-wall simulations, it emerges that wall displacements have a minor impact on the AAo large-scale axial flow, but they can affect secondary flows and WSS directional changes. Overall, helical flow topology is moderately affected by aortic wall displacements, whereas helicity intensity remains almost unchanged. We conclude that CFD simulations with rigid-wall assumption can be a valid approach to study large-scale aortic flows of physiological significance.

The feasibility of early response evaluation using superb microvascular imaging one day after transcatheter arterial chemoembolization for hepatocellular carcinoma.

The purpose of this study was to determine the feasibility of early Superb microvascular imaging (SMI) for prediction of the effect of HCC treatment after transcatheter arterial chemoembolization (TACE). A total of 96 HCCs (70 patients) treated with TACE between September 2021 and May 2022 were included in this study. SMI, Color Doppler imaging (CDI), and Power Doppler imaging (PDI) were performed the day after TACE for evaluation of intratumoral vascularity of the lesion using an Aplio500 ultrasound scanner (Toshiba Medical Systems, Corporation, Tochigi, Japan). Grading of the vascular presence was performed using a five-point scale. A dynamic CT image taken after 29-42 days was used for comparison of sensitivity, specificity, and accuracy for detection of tumor vascularity between SMI, CDI, and PDI. Univariate and multivariate analysis were performed for assessment of factors affecting intratumoral vascularity. Fifty-eight lesions (60%) showed complete remission (CR) and 38 lesions (40%) showed partial response (PR) or no response at 29-42 days on Multi-detector Computed Tomography (MDCT) after TACE. SMI showed sensitivity of 86.84% for detection of intratumoral flow, which was significantly higher compared with that of CDI (10.53%, p< 0.001) and PDI (36.84%, p< 0.001). The results of multivariate analysis indicated that tumor size was a significant factor in detection of blood flow using the SMI technique. Early SMI may be utilized as an adjunctive diagnostic test for evaluation of treated lesions after TACE, particularly when the location of the tumor is in an area of the liver where a suitable sonic window can be identified.

Deep Learning-Based Image Registration in Dynamic Myocardial Perfusion CT Imaging.

Registration of dynamic CT image sequences is a crucial preprocessing step for clinical evaluation of multiple physiological determinants in the heart such as global and regional myocardial perfusion. In this work, we present a deformable deep learning-based image registration method for quantitative myocardial perfusion CT examinations, which in contrast to previous approaches, takes into account some unique challenges such as low image quality with less accurate anatomical landmarks, dynamic changes of contrast agent concentration in the heart chambers and tissue, and misalignment caused by cardiac stress, respiration, and patient motion. The introduced method uses a recursive cascade network with a ventricle segmentation module, and a novel loss function that accounts for local contrast changes over time. It was trained and validated on a dataset of n = 118 patients with known or suspected coronary artery disease and/or aortic valve insufficiency. Our results demonstrate that the proposed method is capable of registering dynamic cardiac perfusion sequences by reducing local tissue displacements of the left ventricle (LV), whereas contrast changes do not affect the registration and image quality, in particular the absolute CT (HU) values of the entire CT sequence. In addition, the deep learning-based approach presented reveals a short processing time of a few seconds compared to conventional image registration methods, demonstrating its application potential for quantitative CT myocardial perfusion measurements in daily clinical routine.

Dynamic cone-beam CT reconstruction using spatial and temporal implicit neural representation learning (STINR)

Objective. Dynamic cone-beam CT (CBCT) imaging is highly desired in image-guided radiation therapy to provide volumetric images with high spatial and temporal resolutions to enable applications including tumor motion tracking/prediction and intra-delivery dose calculation/accumulation. However, dynamic CBCT reconstruction is a substantially challenging spatiotemporal inverse problem, due to the extremely limited projection sample available for each CBCT reconstruction (one projection for one CBCT volume). Approach. We developed a simultaneous spatial and temporal implicit neural representation (STINR) method for dynamic CBCT reconstruction. STINR mapped the unknown image and the evolution of its motion into spatial and temporal multi-layer perceptrons (MLPs), and iteratively optimized the neuron weightings of the MLPs via acquired projections to represent the dynamic CBCT series. In addition to the MLPs, we also introduced prior knowledge, in the form of principal component analysis (PCA)-based patient-specific motion models, to reduce the complexity of the temporal mapping to address the ill-conditioned dynamic CBCT reconstruction problem. We used the extended-cardiac-torso (XCAT) phantom and a patient 4D-CBCT dataset to simulate different lung motion scenarios to evaluate STINR. The scenarios contain motion variations including motion baseline shifts, motion amplitude/frequency variations, and motion non-periodicity. The XCAT scenarios also contain inter-scan anatomical variations including tumor shrinkage and tumor position change. Main results. STINR shows consistently higher image reconstruction and motion tracking accuracy than a traditional PCA-based method and a polynomial-fitting-based neural representation method. STINR tracks the lung target to an average center-of-mass error of 1–2 mm, with corresponding relative errors of reconstructed dynamic CBCTs around 10%. Significance. STINR offers a general framework allowing accurate dynamic CBCT reconstruction for image-guided radiotherapy. It is a one-shot learning method that does not rely on pre-training and is not susceptible to generalizability issues. It also allows natural super-resolution. It can be readily applied to other imaging modalities as well.

Fully automatic extraction of knee kinematics from dynamic CT imaging; normative tibiofemoral and patellofemoral kinematics of 100 healthy volunteers

BackgroundAccurate assessment of knee kinematics is important in the diagnosis and quantification of knee disorders and to determine the effect of orthopaedic interventions. Despite previous studies showing the usefulness of dynamic imaging and providing valuable insights in knee kinematics, dynamic imaging is not widely used in clinics due to a variety of causes. In this study normative knee kinematics of 100 healthy subjects is established using a fully automatic workflow feasible for use in the clinic. MethodsOne-hundred volunteers were recruited and a dynamic CT scan was made during a flexion extension movement. Image data was automatically segmented and dynamic and static images were superimposed using image registration. Coordinate systems for the femur, patella and tibia were automatically calculated as well as their dynamic position and orientation. ResultsDynamic CT scans weremade withan effective radiation dose of 0.08 mSv. The median tibial internal rotation was 4° and valgus rotation is 5° at full flexion. Femoral rollback of the lateral condyle was 7 mm versus 2 mm of the medial condyle. The median patella flexion reached 65% of tibiofemoral flexion and the median tilt and rotation were 5° and 0° at full flexion, respectively. The median mediolateral translation of the patella was 3 mm (medially) in the first 30° of flexion. ConclusionThe current study presents TF and PF kinematic data of 97 healthy individuals, providing a unique dataset of normative knee kinematics. The short scanning time, simple motion and, automatic analysis make the methods presented suitable for daily clinical practice.

The use of dynamic CT imaging for tracking mandibular movements in a phantom

Purpose. The objective of this study was to analyse the possibilities of using 4D CT scanning for the tracking of patients’ mandibles. Methods. A clinical 256-slice Revolution CT was used in obtaining 4D CT scans without table movement, with a novel mandibular phantom, mounted on a programmable six degrees-of-freedom Stewart Platform in motion. The phantom was used to simulate mandibular motions which are combinations of rotations with translations (depression, elevation, protrusion, retrusion and laterotrusion). The phantom was scanned five times during identical motion patterns with a dynamic CT acquisition protocol. An image processing workflow consisting of a pairwise rigid registration and semi-automatic segmentation was developed to extract kinematic parameters (cardan angles and point-of-interest displacements) from the dynamic sequences. Reproducibility was investigated by the 95% confidence interval and the absorbed organ dose to organs of interest in the primary beam were also estimated and compared to those of a standard CT scan of the brain Results. The maximum average 95% confidence interval for the displacement across all time points for the five repetitions was 0.61 mm (Y axis). In terms of rotations, the maximum average 95% confidence interval across all time points for the five repetitions was 1.39° (X axis). The effective dose for the dynamic scan was found to be 1.3 mSv, for a CTDIvol of 63.95 mGy and a DLP of 1023.14 mGycm. The absorbed organ doses were similar to organ doses during a clinical head CT scan. Conclusions. A framework is proposed to use 4D CT scanning as a possible methodology to evaluate the motion of the temporomandibular joint. The scanning protocol allows to visualise the motion by applying a semi-automated segmentation and registration. A graphical representation of all displacements in the three spatial dimensions can depict multiple points-of-interest at once during the same acquisition. A novel type of phantom was also introduced which simulates mandibular movement with six degrees-of-freedom (three translations and three rotations).

Diagnostic Accuracy of a Convolutional Neural Network Assessment of Solitary Pulmonary Nodules Compared With PET With CT Imaging and Dynamic Contrast-Enhanced CT Imaging Using Unenhanced and Contrast-Enhanced CT Imaging

Solitary pulmonary nodules (SPNs) measuring 8 to 30mm in diameter require further workup to determine the likelihood of malignancy. What is the diagnostic performance of a lung cancer prediction convolutional neural network (LCP-CNN) in SPNs using unenhanced and contrast-enhanced CT imaging compared with the current clinical workup? This was a post hoc analysis of the Single Pulmonary Nodule Investigation: Accuracy and Cost-Effectiveness of Dynamic Contrast Enhanced Computed Tomography in the Characterisation of Solitary Pulmonary Nodules trial, a prospective multicenter study comparing the diagnostic accuracy of dynamic contrast-enhanced (DCE) CT imaging with PET imaging in SPNs. The LCP-CNN was designed and validated in an external cohort. LCP-CNN-generated risk scores were created from the noncontrast and contrast-enhanced CT scan images from the DCE CT imaging. The gold standard was histologic analysis or 2 years of follow-up. The area under the receiver operating characteristic curves (AUC) were calculated using LCP-CNN score, maximum standardized uptake value, and DCE CT scan maximum enhancement and were compared using the DeLong test. Two hundred seventy participants (mean ± SD age, 68.3 ± 8.8 years; 49%women) underwent PET with CT scan imaging and DCE CT imaging with CT scan data available centrally for LCP-CNN analysis. The accuracy of the LCP-CNN on the noncontrast images (AUC, 0.83; 95%CI, 0.79-0.88) was superior to that of DCE CT imaging (AUC, 0.76; 95%CI, 0.69-0.82; P= .03) and equal to that of PET with CT scan imaging (AUC, 0.86; 95%CI, 0.81-0.90; P= .35). The presence of contrast resulted in a small reduction in diagnostic accuracy, with the AUC falling from 0.83 (95%CI, 0.79-0.88) on the noncontrast images to 0.80 to 0.83 after contrast (P< .05 for 240s after contrast only). An LCP-CNN algorithm provides an AUC equivalent to PET with CT scan imaging in the diagnosis of solitary pulmonary nodules. ClinicalTrials.gov Identifier; No.: NCT02013063.

Association between coronary plaque volume and myocardial ischemia detected by dynamic perfusion CT imaging

IntroductionWe aimed to evaluate the relationship between quantitative plaque metrics derived from coronary CT angiography (CTA) and segmental myocardial ischemia using dynamic perfusion CT (DPCT).MethodsIn a prospective single-center study, patients with > 30% stenosis on rest CTA underwent regadenoson stress DPCT. 480 myocardium segments of 30 patients were analyzed. Quantitative plaque assessment included total plaque volume (PV), area stenosis, and remodeling index (RI). High-risk plaque (HRP) was defined as low-attenuation plaque burden > 4% or RI > 1.1. Absolute myocardial blood flow (MBF) and relative MBF (MBFi: MBF/75th percentile of all MBF values) were quantified. Linear and logistic mixed models correcting for intra-patient clustering and clinical factors were used to evaluate the association between total PV, area stenosis, HRP and MBF or myocardial ischemia (MBF < 101 ml/100 g/min).ResultsMedian MBF and MBFi were 111 ml/100 g/min and 0.94, respectively. The number of ischemic segments were 164/480 (34.2%). Total PV of all feeding vessels of a given myocardial territory differed significantly between ischemic and non-ischemic myocardial segments (p = 0.001). Area stenosis and HRP features were not linked to MBF or MBFi (all p > 0.05). Increase in PV led to reduced MBF and MBFi after adjusting for risk factors including hypertension, diabetes, and statin use (per 10 mm3; β = −0.035, p < 0.01 for MBF; β = −0.0002, p < 0.01 for MBFi). Similarly, using multivariate logistic regression total PV was associated with ischemia (OR = 1.01, p = 0.033; per 10 mm3) after adjustments for clinical risk factors, area stenosis and HRP.ConclusionTotal PV was independently associated with myocardial ischemia based on MBF, while area stenosis and HRP were not.

438 The Association Between Coronary Plaque Volume And Myocardial Ischemia As Detected By Dynamic Perfusion CT Imaging

Introduction: Cardiac CT can assess both plaque morphology and the functional relevance of coronary lesions. We aimed to further elucidate the association between quantitative atherosclerotic plaque metrics derived from coronary computed tomography (CCTA) and segmental myocardial ischemia detected using dynamic perfusion CT (DPCT) images.

Poster 228: Comparison of Isometric Properties Between the Medial Patellofemoral Complex Fibers

Objectives:The medial patellofemoral complex (MPFC) has a broad attachment on the patella and quadriceps tendon. Recent anatomic studies have demonstrated a corresponding elongated footprint on the medial femur in which the proximal fibers constitute the MQTFL and the distal fibers form the MPFL. Reconstruction of the MPFL and MQTFL have traditionally been described using the midpoint of the femoral footprint (Schottle’s point) while varying the graft’s position on the patella or quadriceps tendon. The purpose of this study was to compare graft isometry of MPFL, MQTFL, and MPFC reconstruction when using a standard femoral tunnel versus the corresponding anatomic femoral tunnel, and to identify the morphologic risk factors that influence each reconstruction technique.Methods:3D digital knee models were created from dynamic CT images of asymptomatic knees of patients with contralateral patellar instability. Knee models were grouped into 10° intervals and graft length, or distance between the defined points on the femur and extensor mechanism were measured in the following conditions: 1) standard MQTFL (sMQTFL), between the midpoint of the femoral footprint and the quadriceps tendon attachment, 2) anatomic MQTFL (aMQTFL), between the proximal femoral footprint and quadriceps tendon attachment, 3) standard MPFL (sMPFL), between the femoral footprint midpoint and the patellar attachment, 4) anatomic MPFL (aMPFL), between the distal femoral footprint and patellar attachment, and 5) MPFC, between the midpoints of the femoral and quadriceps tendon/patellar attachments. Changes in graft length between 0°and 40° flexion were compared for each reconstruction technique and assessed for their relationship to morphologic risk factors using stepwise multiple regression analyses.Results:12 knees were included in this study (3M, 9F; mean age 23.1+/-8.0y). Mean graft length was significantly greater at 0° than 40° in all reconstructive techniques (p<0.001 to p=0.045). Graft length changes showed no significant differences between reconstructive techniques when using corresponding anatomic femoral tunnels (aMQTFL, aMPFL, aMPFC). When compared to aMPFC (8.8mm), graft length changes were greater in sMQTFL (11.3, p=0.005) and smaller in sMPFL (6.9, p=0.037); however 2/12 (16.7%) of the sMPFL had unfavorable length change patterns that were tighter in flexion than extension. Overall, proximal reconstructions (aMQTFL and sMQTFL) were the most sensitive to the presence of morphologic risk factors (R=.933, R2=0.87 and R=0.898,R2=0.81, respectively) with patella alta having the greatest effect. In contrast, the distal reconstructions (aMPFL and sMPFL) did not have a significant relationship with risk factors but trended toward a significant relationship with TTTG distance (p=0.072 and 0.064, respectively).Conclusions:For MQTFL and MPFL reconstructions, using the corresponding anatomic femoral attachment showed more favorable length change patterns over using the currently described standard femoral tunnel. Overall, graft length changes in proximal (quadriceps tendon) reconstructions were more sensitive to the presence of patella alta, while distal (patellar) reconstructions were influenced by TTTG distance. Further studies are needed to identify the optimal reconstructive technique based on each patient-specific morphologic patterns in the treatment of patellar instability.

Image Features of Dynamic Enhanced Computed Tomography Scanning Combined with Digestive Endoscopy in the Treatment of Gastroesophageal Varices and Nursing of Esophagogastric Gastric Varices Bleeding.

The objective of this study was to investigate the application of dynamic contrast-enhanced CT images in the nursing of patients with gastroesophageal varices (GOV) treated by digestive endoscopy and its role in relieving bleeding symptoms. A total of 60 patients with liver cirrhosis and GOV were selected as the research objects. According to whether CT was used to evaluate the position of tissue adhesion embolism, the patients were divided into the control group (24 cases) and the observation group (36 cases). The treatment effect and bleeding situation of patients in the two groups were analyzed and compared. The results showed that the main portal vein pressure (17.24 ± 1.02 cmH2O), liver function recovery effect (2.84 ± 0.45 points), and total effective rate (100%) in observation group were better than those in control group (9.70 ± 1.22 cmH2O, 0.95 ± 0.72 points, and 79.17%, respectively) (P < 0.05). In addition, the bleeding rate in observation group (0%) was significantly lower than that in control group (16.67%) (P < 0.05). In conclusion, dynamically enhanced CT scan images combined with digestive endoscopy can help improve the therapeutic effect of GOV and reduce postoperative bleeding, which was worthy of clinical application and promotion.