Computed Tomography Fusion Research Articles

Step-by-step Stereotactic Radiotherapy Planning of Pituitary Adenoma: A ROSE (Radiation Oncology from Simulation to Execution) Guide to Radiation Oncologists

Introduction Pituitary adenoma accounts for 10%–20% of all intracranial malignancies. The primary modality of treatment is surgery, while pituitary radiation is indicated in residual or recurrent setting post-surgery. Currently, stereotactic radiotherapy (SRT) is one of the main modalities of radiation treatment. The objective of this article is to describe the procedural steps for radiation planning of SRT of pituitary adenoma Methods The step-by-step procedure for stereotactic planning of pituitary adenoma has been described using a clinical scenario of pituitary adenoma. Results The stereotactic radiation planning of pituitary adenoma starts with the basic history and relevant clinical evaluation that is visual testing. Magnetic resonance imaging (MRI) of the brain is the imaging modality of choice. Evaluation of surgical notes and post-operative histopathology confirmation of diagnosis should also be done. The radiation planning of pituitary adenoma starts with Computed tomography (CT) simulation and MRI of brain that should be done in prescribed format to achieve uniformity in radiation planning. After CT and MRI image fusion, contouring of target, organs at risk (OAR) and radiation planning should be done. The plan evaluation includes target and OAR coverage index, conformity, homogeneity and gradient index and beam arrangement. After radiation plan evaluation, treatment is delivered after quality assurance and dry run. Conclusion The article highlights the sequential process of radiation planning for SRT—starting from simulation, planning, evaluation of plan and treatment.

Tomographic assessment of bone changes in atrophic maxilla treated by split-crest technique and dental implants with platelet-rich fibrin and NanoBone® versus platelet-rich fibrin alone: Randomized controlled trial

BackgroundThis study evaluated the clinical benefits of adding NanoBone® with split-crest technique and simultaneous implant placement covered with platelet-rich fibrin membrane in horizontally deficient maxillary ridges in terms of crestal and horizontal bone changes and patient morbidity.MethodsForty patients indicated for maxillary ridge splitting and simultaneous implant placement were assigned randomly to the study groups: control group (Platelet Rich Fibrin membrane) and test group (Platelet Rich Fibrin membrane + Nanobone®). The Cone Beam Computed Tomography Fusion technique was utilized to assess crestal and horizontal bone changes after five months of the surgical procedure. Patient morbidity was recorded for one week post-surgical.ResultsFive months post-surgical, buccal crestal bone resorption was 1.26 ± 0.58 mm for the control group and 1.14 ± 0.63 mm for the test group. Lingual crestal bone resorption was 1.40 ± 0.66 mm for the control group and 1.47 ± 0.68 mm for the test group. Horizontal bone width gain was 1.46 ± 0.44 mm for the control group and 1.29 ± 0.73 mm for the test group. There was no significant statistical difference between study groups regarding crestal and horizontal bone changes and patient morbidity.ConclusionsThe tomographic assessment of NanoBone® addition in this study resulted in no statistically significant difference between study groups regarding crestal and horizontal bone changes and patient morbidity. More randomized controlled clinical trials on gap fill comparing different bone grafting materials versus no grafting should be conducted.Clinicaltrials.gov registration numberNCT02836678, 13th January 2017.

Development of a software system for surgical robots based on multimodal image fusion: study protocol.

Surgical robots are gaining increasing popularity because of their capability to improve the precision of pedicle screw placement. However, current surgical robots rely on unimodal computed tomography (CT) images as baseline images, limiting their visualization to vertebral bone structures and excluding soft tissue structures such as intervertebral discs and nerves. This inherent limitation significantly restricts the applicability of surgical robots. To address this issue and further enhance the safety and accuracy of robot-assisted pedicle screw placement, this study will develop a software system for surgical robots based on multimodal image fusion. Such a system can extend the application range of surgical robots, such as surgical channel establishment, nerve decompression, and other related operations. Initially, imaging data of the patients included in the study are collected. Professional workstations are employed to establish, train, validate, and optimize algorithms for vertebral bone segmentation in CT and magnetic resonance (MR) images, intervertebral disc segmentation in MR images, nerve segmentation in MR images, and registration fusion of CT and MR images. Subsequently, a spine application model containing independent modules for vertebrae, intervertebral discs, and nerves is constructed, and a software system for surgical robots based on multimodal image fusion is designed. Finally, the software system is clinically validated. We will develop a software system based on multimodal image fusion for surgical robots, which can be applied to surgical access establishment, nerve decompression, and other operations not only for robot-assisted nail placement. The development of this software system is important. First, it can improve the accuracy of pedicle screw placement, percutaneous vertebroplasty, percutaneous kyphoplasty, and other surgeries. Second, it can reduce the number of fluoroscopies, shorten the operation time, and reduce surgical complications. In addition, it would be helpful to expand the application range of surgical robots by providing key imaging data for surgical robots to realize surgical channel establishment, nerve decompression, and other operations.

Porous Cage Macro-Topography Improves Early Fusion Rates in Anterior Cervical Discectomy and Fusion.

Anterior cervical discectomy and fusion (ACDF) aims to improve pain, relieve neural compression, achieve rapid solid bony arthrodesis, and restore cervical alignment. Bony fusion occurs as early as 3 months and up to 24 months after ACDF. The correlations between bony fusion and clinical outcomes after ACDF remain unclear. Macro-topographic and porous features have been introduced to interbody cage technology, aiming to improve the strength of the bone-implant interface to promote early fusion. In this study, we aimed to compare clinical outcomes and CT-evaluated fusion rates in patients undergoing ACDF using one of two different interbody cages: traditional NanoMetalene™ (NM) cages and NM cages with machined porous features (NMRT). This was a prospective, observational, nonrandomised, cohort study of consecutive patients undergoing ACDF. The NM cage cohort was enrolled first, then the NMRT cohort second. The visual analogue scale, neck disability index, and 12-item Short Form Survey scores were evaluated preoperatively and at 6 weeks, 3 months, and 6 months. The minimum clinical follow-up period was 12 months. Plain radiographs were obtained on postoperative day 2 to assess instrumentation positioning, and computed tomography (CT) was performed at 3 and 6 months postoperatively to assess interbody fusion (Bridwell grade). Eighty-nine (52% male) patients with a mean age of 62 ± 10.5 years were included in this study. Forty-one patients received NM cages, and 48 received NMRT cages. All clinical outcomes improved significantly from baseline to 6 months. By 3 months, the NMRT group had significantly higher CT fusion rates than the NM group (79% vs 56%, p=0.02). By 6 months, there were no significant differences in fusion rates between the NMRT and NM groups (83% vs 78%, p=0.69). The mean Bridwell grade at 6 months was 1.4 ± 0.7 in the NMRT group and 1.8 ± 1.0 in the NM group (p=0.08). With both NM and NMRT cages, serial improvements in postoperative clinical outcomes were associated with fusion progression on CT. NMRT cages demonstrated significantly better fusion at 3 months and a trend toward higher quality of fusion at 6 months compared with NM cages, suggesting earlier cage integration with NMRT. An early 3-month postoperative CT is adequate for fusion assessment in almost 80% of patients undergoing ACDF with an NMRT cage, permitting an earlier return to activity.

Advanced hybrid attention-based deep learning network with heuristic algorithm for adaptive CT and PET image fusion in lung cancer detection

Lung cancer is one of the most deadly diseases in the world. Lung cancer detection can save the patient's life. Despite being the best imaging tool in the medical sector, clinicians find it challenging to interpret and detect cancer from Computed Tomography (CT) scan data. One of the most effective ways for the diagnosis of certain malignancies like lung tumours is Positron Emission Tomography (PET) imaging. So many diagnosis models have been implemented nowadays to diagnose various diseases. Early lung cancer identification is very important for predicting the severity level of lung cancer in cancer patients. To explore the effective model, an image fusion-based detection model is proposed for lung cancer detection using an improved heuristic algorithm of the deep learning model. Firstly, the PET and CT images are gathered from the internet. Further, these two collected images are fused for further process by using the Adaptive Dilated Convolution Neural Network (AD-CNN), in which the hyperparameters are tuned by the Modified Initial Velocity-based Capuchin Search Algorithm (MIV-CapSA). Subsequently, the abnormal regions are segmented by influencing the TransUnet3+. Finally, the segmented images are fed into the Hybrid Attention-based Deep Networks (HADN) model, encompassed with Mobilenet and Shufflenet. Therefore, the effectiveness of the novel detection model is analyzed using various metrics compared with traditional approaches. At last, the outcome evinces that it aids in early basic detection to treat the patients effectively.

Multimodal fusion of liquid biopsy and CT enhances differential diagnosis of early-stage lung adenocarcinoma

This research explores the potential of multimodal fusion for the differential diagnosis of early-stage lung adenocarcinoma (LUAD) (tumor sizes < 2 cm). It combines liquid biopsy biomarkers, specifically extracellular vesicle long RNA (evlRNA) and the computed tomography (CT) attributes. The fusion model achieves an impressive area under receiver operating characteristic curve (AUC) of 91.9% for the four-classification of adenocarcinoma, along with a benign-malignant AUC of 94.8% (sensitivity: 89.1%, specificity: 94.3%). These outcomes outperform the diagnostic capabilities of the single-modal models and human experts. A comprehensive SHapley Additive exPlanations (SHAP) is provided to offer deep insights into model predictions. Our findings reveal the complementary interplay between evlRNA and image-based characteristics, underscoring the significance of integrating diverse modalities in diagnosing early-stage LUAD.

Investigation of Medical Image Technology Based on Big Data Neuroscience in Exercise Rehabilitation.

The purpose of this article is to combine the functional information of CT images with the anatomical and soft tissue information of MRI through image fusion technology, providing more detailed information for rehabilitation treatment and thus providing a scientific basis for clinical applications and better training plans. In this paper, functional brain imaging technology combining CT (computed tomography) and MRI (magnetic resonance imaging) was used for image fusion, and SURF (accelerated robust feature) feature points of images were extracted. In this study, 40 patients with mild and moderate closed traumatic brain injury admitted to the rehabilitation department of a rehabilitation center from 2018 to 2022 were selected as the research objects. Compared with using only CT images and MRI images for brain injury diagnosis, the fusion image had a higher detection rate of abnormal brain injury diagnosis, with a detection rate of 97.5%. When using fused images for the diagnosis of abnormal brain injury, the patient's exercise rehabilitation effect was better. CT and MRI image fusion technology had a high diagnostic accuracy for brain injury, which could timely guide doctors in determining exercise rehabilitation plans and help improve the effectiveness of patient exercise rehabilitation.

Targeted Nanotheransotics: Integration of Preclinical MRI and CT in the Molecular Imaging and Therapy of Advanced Diseases.

The integration of preclinical magnetic resonance imaging (MRI) and computed tomography (CT) methods has significantly enhanced the area of therapy and imaging of targeted nanomedicine. Nanotheranostics, which make use of nanoparticles, are a significant advancement in MRI and CT imaging. In addition to giving high-resolution anatomical features and functional information simultaneously, these multifunctional agents improve contrast when used. In addition to enabling early disease detection, precise localization, and personalised therapy monitoring, they also enable early disease detection. Fusion of MRI and CT enables precise in vivo tracking of drug-loaded nanoparticles. MRI, which provides real-time monitoring of nanoparticle distribution, accumulation, and release at the cellular and tissue levels, can be used to assess the efficacy of drug delivery systems. The precise localization of nanoparticles within the body is achievable through the use of CT imaging. This technique enhances the capabilities of MRI by providing high-resolution anatomical information. CT also allows for quantitative measurements of nanoparticle concentration, which is essential for evaluating the pharmacokinetics and biodistribution of nanomedicine. In this article, we emphasize the integration of preclinical MRI and CT into molecular imaging and therapy for advanced diseases.

The Application of Ultrasonography–Computed Tomography Fusion Navigation Technology in Complex Bone Tumor Biopsy: A Randomized Double-Blind Controlled Trial

PurposeThis study aims to investigate the clinical application value of ultrasound-CT fusion navigation technology in bone tumor biopsy surgery. MethodsA total of thirty patients with bone tumors requiring biopsy surgery were randomly assigned to either the U-C group (ultrasound-CT group, n=15) or the control group (n=15). The U-C group utilized ultrasound-CT fusion navigation technology for real-time localization of the biopsy needle, while the control group relied on intraoperative C-arm fluoroscopy for localization. The success rate of the surgeries, the number of radiation exposures during the procedure, surgical time, and intraoperative blood loss were compared between the two groups. ResultsNumber of intraoperative radiation exposure in the U-C group was 2 versus 7 in the control group (P<0.05), showing significant differences between the 2 groups. The success rate of biopsies in the U-C group and control group was 100%(P＞0.05), the mean operative time was 45±9min versus 42±13min (P＞0.05), and intraoperative bleeding volume was 10±4ml versus 11±5ml(P＞0.05), all showing no significant differences between the 2 groups. ConclusionThe real-time localization of the biopsy needle in bone tumor biopsy surgery using ultrasound-CT fusion navigation technology can significantly reduce intraoperative radiation exposure for both patients and surgeons during the procedure. Consequently, this technique holds certain clinical applicability.

A three-layer decomposition method based on structural texture perception for fusion of CT and MRI images

The fusion of computed tomography (CT) images and magnetic resonance imaging (MRI) images has made essential contribution to clinical diagnosis because of its ability of complementary visual information enhancement and redundancy elimination. However, some methods that involve upsampling and downsampling operations may lose information during image processing, which affects the fusion results. In this paper, a medical image fusion algorithm based on structural texture perception is proposed. The proposed method demonstrates enhanced performance in preserving both detailed texture information and energy information of source images. First, the source image is decomposed into a signal strength layer, a base layer, and a texture layer based on the proposed three-layer decomposition framework. Then, the signal strength layers are fused using a saliency detection method based on iterative least squares. The texture layer is fused using the principle of spatial frequency maximization. For the fusion of the base layer, a non-linear function is designed to calculate the fusion weights. Finally, the final fusion result is obtained through image reconstruction. The proposed algorithm is compared with nine state-of-the-art fusion algorithms to verify its superiority. Experimental results show that the proposed method can effectively preserve the intensity information of CT images and the detailed texture of MRI images.

CT and MRI fusion based on generative adversarial network and convolutional neural networks under image enhancement

Aiming at the problems of missing important features, inconspicuous details and unclear textures in the fusion of multimodal medical images, this paper proposes a method of computed tomography (CT) image and magnetic resonance imaging (MRI) image fusion using generative adversarial network (GAN) and convolutional neural network (CNN) under image enhancement. The generator aimed at high-frequency feature images and used double discriminators to target the fusion images after inverse transform; Then high-frequency feature images were fused by trained GAN model, and low-frequency feature images were fused by CNN pre-training model based on transfer learning. Experimental results showed that, compared with the current advanced fusion algorithm, the proposed method had more abundant texture details and clearer contour edge information in subjective representation. In the evaluation of objective indicators, Q AB/F, information entropy (IE), spatial frequency (SF), structural similarity (SSIM), mutual information (MI) and visual information fidelity for fusion (VIFF) were 2.0%, 6.3%, 7.0%, 5.5%, 9.0% and 3.3% higher than the best test results, respectively. The fused image can be effectively applied to medical diagnosis to further improve the diagnostic efficiency.

Using computed tomography fusion imaging as learning data for sonographer training in identification of left ventricular endocardial boundaries

BackgroundWe hypothesized that if computed tomography (CT) images were used as learning data, we could overcome volume underestimation by echocardiography, improving the accuracy of left ventricular (LV) volume measurements. MethodsWe utilized a fusion imaging modality consisting of echocardiography with superimposed CT images for 37 consecutive patients to identify the endocardial boundary. We compared LV volumes obtained with and without CT learning trace-lines (TLs). Furthermore, 3D echocardiography was used to compare LV volumes obtained with and without CT learning for endocardial identification. The mean difference between the echocardiography and CT-derived LV volumes and the coefficient of variation were compared pre- and post-learning. Bland–Altman analysis was used to assess the differences in LV volume (mL) obtained from the 2D pre-learning TL and 3D post-learning TL. ResultsThe post-learning TL was located closer to the epicardium than the pre-learning TL. This trend was particularly pronounced in the lateral and the anterior wall. The post-learning TL was along the inner side of the high echoic layer in the basal-lateral wall in the four-chamber view. CT fusion imaging determined that the difference in LV volume between 2D echocardiography and CT was small (−25.6 ± 14.4 mL before learning, −6.9 ± 11.5 mL after learning) and that CT learning improved the coefficient of variation (10.9 % before learning, 7.8 % after learning). Significant improvements were observed during 3D echocardiography; the difference in LV volume between 3D echocardiography and CT was slight (−20.5 ± 15.1 mL before learning, 3.8 ± 15.7 mL after learning), and the coefficient of variation improved (11.5 % before learning, 9.3 % after learning). ConclusionsDifferences between the LV volumes obtained using CT and echocardiography either disappeared or were reduced after CT fusion imaging. Fusion imaging is useful in training regimens for accurate LV volume quantification using echocardiography and may contribute to quality control.

Brain Tumor Classification Using Image Fusion and EFPA-SVM Classifier

An accurate and early diagnosis of brain tumors based on medical imaging modalities is of great interest because brain tumors are a harmful threat to a person’s health worldwide. Several medical imaging techniques have been used to analyze brain tumors, including computed tomography (CT) and magnetic resonance imaging (MRI). CT provides information about dense tissues, whereas MRI gives information about soft tissues. However, the fusion of CT and MRI images has little effect on enhancing the accuracy of the diagnosis of brain tumors. Therefore, machine learning methods have been adopted to diagnose brain tumors in recent years. This paper intends to develop a novel scheme to detect and classify brain tumors based on fused CT and MRI images. The proposed approach starts with preprocessing the images to reduce the noise. Then, fusion rules are applied to get the fused image, and a segmentation algorithm is employed to isolate the tumor region from the background to isolate the tumor region. Finally, a machine learning classifier classified the brain images into benign and malignant tumors. Computing statistical measures evaluate the classification potential of the proposed scheme. Experimental outcomes are provided, and the Enhanced Flower Pollination Algorithm (EFPA) system shows that it outperforms other brain tumor classification methods considered for comparison.

Localization and surgical approach to mediastinal parathyroid glands

BackgroundHyperactive parathyroid glands (PTGs) are in the mediastinum 4.3% of the time. Historically, localization and resection of these glands can be challenging.MethodsWe searched all operative notes involving a thoracic surgeon and a preoperative diagnosis of hyperparathyroidism from 2001 to 2019.ResultsEighty-five cases were reviewed, of which 63 were included. Only 14 patients (22%) had de novo hyperparathyroid operations. Seventeen patients (27%) had single-photon emission computed tomography with computed tomography fusion (SPECT-CT) as the only preoperative localization test (excluding chest radiography and ultrasound), and all were resected successfully. The initial surgical approach was transcervical for 16 (27%) patients, however only 7 remained transcervical. 4 (6%) patients had an exploration in which the target lesion was resected but it was not parathyroid tissue.ConclusionMost patients presenting with mediastinal PTG have had prior HPT surgery. The trend toward more focused HPT surgery may mean more de novo mediastinal PTG resections. An unambiguous functional and anatomic localization test, such as a spect-ct scan, is the best predictor of a successful resection. Ambiguous or discordant scans should be approached cautiously, and additional confirmatory tests are recommended. For suspected PTG located in the thymus, the thoracic surgeon should choose the most familiar approach to achieve complete thymectomy.

Step-by-Step Stereotactic Radiotherapy Planning of Glomus Jugulare: A Guide to Radiation Oncologists—Dr Kanhu’s ROSE (Radiation Oncology from Simulation to Execution)

Background Glomus jugulare is a rare, slow-growing tumor that arise within the jugular foramen of the temporal bone. In the past, surgery was the primary modality of treatment for glomus Jugulare, but it leads to many complications and increased mortality. Radiotherapy was indicated in adjuvant setting in post-operative residual disease. But, with the advent of highly conformal radiation planning, stereotactic radiosurgery (SRS), is now one of the main modalities of radiation treatment in glomus jugulare. Objective To describe the procedural steps for radiation planning of SRS of glomus jugulare. Methods The step-by-step procedure for stereotactic planning of glomus jugulare has been described using a clinical scenario of glomus jugulare. Results The stereotactic radiation planning of glomus jugulare starts with the basic history and relevant clinical evaluation, that is, visual testing. Computed tomography (CT) scan and magnetic resonance imaging (MRI) of the brain is the imaging modality of choice. The radiation planning of glomus jugulare starts with CT simulation. MRI of brain should be done in the prescribed format to achieve uniformity in radiation planning. After CT and MRI image fusion, contouring of target, organs at risk (OAR) and radiation planning should be done. The plan evaluation includes target and OAR coverage index, conformity, homogeneity and gradient index, and beam arrangement. After radiation plan evaluation, treatment is delivered after quality assurance and dry run. Conclusion The paper highlights the sequential process of radiation planning for SRS in glomus jugulare—starting from simulation, planning, evaluation of plan, and treatment.

Reduction of Inter-Observer Variability Using MRI and CT Fusion in Delineating of Primary Tumor for Radiotherapy in Lung Cancer with Atelectasis

<h3>Purpose/Objective(s)</h3> To compare the difference between magnetic resonance imaging (MRI) and computed tomography (CT) in delineating the target area of lung cancer with atelectasis. Accurately identify the outline volume of the tumor and reduce the probability of normal tissue complications. <h3>Materials/Methods</h3> Retrospective analysis was performed on 15 patients with lung cancer accompanied by atelectasis. All patients were scanned with MRI and CT in the same supine position within one week. All positioning images were transferred to treatment planning systems. According to the anatomy of sternum, rib, vertebral body, pulmonary artery and tumor, each MRI sequence (T1WI, T1WI+C, T1WI+C Delay, T1WI+C 10 minutes, T2WI, DWI) was automatically registered with CT through the planning system, and the fusion stability was increased by manual correction. Five radiation oncologists with rich clinical experience delineate tumor boundary to obtain the gross tumor volume (GTV). The boundary between tumor and atelectasis was determined by referring to CT structure, coronal and sagittal MRI images when drawing CT-MRI fusion images. The target areas of CT and MRI images were sketched on the same day. Consistence index (CI) and dice coefficient (DC) were used to measure differences among observers. <h3>Results</h3> The differences of delineation mean volumes, CI and DC among CT and MRI were significant. Multiple comparisons were made between MRI sequences and CT. The mean volume of DWI, T2WI, T1WI + C 10 minutes sequence in the target area is significantly smaller than that on CT sequence, but the consistency is higher than that of CT sequences. <h3>Conclusion</h3> The recognition of atelectasis by MRI was better than that by CT, which could reduce inter-observer variability of primary tumor delineation in lung cancer with atelectasis. Among them, DWI, T2WI, T1WI+C 10 minutes may be a better choice to improve the GTV delineation of lung cancer patients with atelectasis. Abbreviations: CT: Computed tomography; GTV: Gross tumor volume; MRI: Magnetic resonance imaging; T1WI: WATER:BH AX LAVA-Flex; T1WI+C: WATER:BH AX LAVA-Flex-C; T1WI+C Delay: WATER:BH AX LAVA-Flex-C delay; T1WI+C 10 minutes: WATER:BH AX LAVA-Flex-C 10min; T2WI:RTr Ax T2 fs Propeller; CI: Consistence index; DC: Dice coefficient.

Long-Term Follow-Up of Hindfoot and Ankle Arthrodesis Procedures Supplemented with an Autologous Bone Graft Alternative (rhPDGF)

Category: Hindfoot; Ankle Introduction/Purpose: Recombinant human platelet-derived growth factor (rhPDGF) is commonly used in hindfoot and ankle arthrodesis as an alternative to autologous bone graft, the current gold standard grafting material. The largest randomized controlled trial ever conducted in foot and ankle arthrodesis showed that rhPDGF was associated with similar successful radiographic and clinical outcomes to those of autologous bone graft at 24 months. The objective of this study was to determine if outcomes remained similar for these two grafting materials at long-term follow-up. Methods: All 37 sites (414 subjects) from the previously conducted randomized controlled trial examining outcomes for hindfoot and ankle arthrodesis supplemented with either rhPDGF or autologous bone graft (randomized 2:1) were invited to return for a single visit occurring at a minimum follow-up of 60 months. All returning subjects who provided consent were evaluated with computed tomography (CT) scans, American Orthopaedic Foot &amp; Ankle Society (AOFAS) Scores, Foot Pain and Disability (FFI) Scores, and visual analog scores (VAS) assessing fusion site, weight bearing, and graft harvest site pain. Because final fusion status was dependent upon the status exiting the original trial, maintenance or improvement of fusion status was the key focus of the study. The change in baseline from all other outcomes measures were also compared between the two groups. Results: A total of 169 subjects (109 rhPDGF, 60 autologous) from 26 sites completed a follow-up visit at a mean 9.1 years (7.7- 10.9).The rate of maintenance or improvement of CT fusion status was statistically noninferior for subjects in the rhPDGF group compared to the autologous bone graft group (92.7% vs. 95.0%,p=0.021), Total AOFAS Scores (74.9+16.7 vs. 77.2+13.9, p&lt;0.001), FFI Scores (22.7+21.7 vs. 16.5+12.0, p&lt;0.001), weight bearing pain change from baseline (-46.0+33.4 vs. -51.0+33.1, p=0.002), and fusion site pain change from baseline (-34.0+33.6 vs. -34.0+32.4, p&lt;0.001). There were no differences in secondary surgical interventions with the most common reasons being hardware complications (7.3% vs. 8.3%) and non-union (4.6% vs. 1.7%). There were no significant differences in the rates of medically relevant adverse events. In the autologous bone graft group, 3 (5%) subjects continued to experience clinically relevant pain (VAS&gt;20) at their graft harvest site. Conclusion: The outcomes of rhPDGF in hindfoot or ankle arthrodesis were statistically noninferior to those of autologous bone graft at a mean follow-up of 9.1 years. Over 92% of rhPDGF subjects maintained or improved their fusion status. Similarly, the baseline change for all VAS and functional outcomes were non-inferior for the two groups. The exception was clinically significant graft harvest site pain, which only existed in the autologous bone graft group. The results of this study demonstrate that rhPDGF used in hindfoot and ankle arthrodesis is associated with similar long-term radiographic, functional, and clinical outcomes as autologous bone.

Intraoperative Fusion Imaging During Transcarotid Artery Revascularization

BackgroundTranscarotid artery revascularization (TCAR) with reverse-flow neuroprotection has emerged as an alternative to transfemoral carotid artery stenting and carotid endarterectomy. However, it requires fluoroscopic guidance, exposing patient and surgeon to radiation. Although computed tomography (CT) fusion-guided EVAR has been demonstrated to significantly decrease this radiation risk, not much is known about similar outcomes for TCAR. The purpose of this study is to evaluate outcomes at a single institution utilizing CT fusion-guided imaging during TCAR compared to regional TCAR cases in the Vascular Quality Initiative (VQI) registry without CT fusion imaging.MethodsA retrospective analysis was conducted of data collected from all patients undergoing TCAR with CT fusion-guided imaging (TCAR-F) at our hospital (Figure) and TCAR patients within the VQI database. Primary outcomes included total operative time, dose area product, fluoroscopy time, contrast use, and flow-reversal time. Demographics and preoperative risk factors were also assessed in both groups. Continuous outcomes were compared using Welch’s t test. Categorical outcomes were compared using Fisher’s exact test.ResultsA total of 30 TCAR-F cases (January 2019 to May 2022) at our institution were compared against the regional VQI dataset (n = 2,535). TCAR-F cases had lower dose area product (5.67 Gy.cm2 vs 93.1 Gy.cm2; P < .0001), fluoroscopic time (8.07 minutes vs 16.4 minutes; P < .0001), and contrast use (13.49 mL vs 76.7 mL; P < .0001) as compared to regional averages of the same. TCAR-F cases had longer total operative time (117.3 minutes vs 80.9 minutes; P < .0001) and flow-reversal time (14.4 minutes vs 11.7 minutes; P = .025) than regional cases.Conclusions BackgroundTranscarotid artery revascularization (TCAR) with reverse-flow neuroprotection has emerged as an alternative to transfemoral carotid artery stenting and carotid endarterectomy. However, it requires fluoroscopic guidance, exposing patient and surgeon to radiation. Although computed tomography (CT) fusion-guided EVAR has been demonstrated to significantly decrease this radiation risk, not much is known about similar outcomes for TCAR. The purpose of this study is to evaluate outcomes at a single institution utilizing CT fusion-guided imaging during TCAR compared to regional TCAR cases in the Vascular Quality Initiative (VQI) registry without CT fusion imaging. Transcarotid artery revascularization (TCAR) with reverse-flow neuroprotection has emerged as an alternative to transfemoral carotid artery stenting and carotid endarterectomy. However, it requires fluoroscopic guidance, exposing patient and surgeon to radiation. Although computed tomography (CT) fusion-guided EVAR has been demonstrated to significantly decrease this radiation risk, not much is known about similar outcomes for TCAR. The purpose of this study is to evaluate outcomes at a single institution utilizing CT fusion-guided imaging during TCAR compared to regional TCAR cases in the Vascular Quality Initiative (VQI) registry without CT fusion imaging. MethodsA retrospective analysis was conducted of data collected from all patients undergoing TCAR with CT fusion-guided imaging (TCAR-F) at our hospital (Figure) and TCAR patients within the VQI database. Primary outcomes included total operative time, dose area product, fluoroscopy time, contrast use, and flow-reversal time. Demographics and preoperative risk factors were also assessed in both groups. Continuous outcomes were compared using Welch’s t test. Categorical outcomes were compared using Fisher’s exact test. A retrospective analysis was conducted of data collected from all patients undergoing TCAR with CT fusion-guided imaging (TCAR-F) at our hospital (Figure) and TCAR patients within the VQI database. Primary outcomes included total operative time, dose area product, fluoroscopy time, contrast use, and flow-reversal time. Demographics and preoperative risk factors were also assessed in both groups. Continuous outcomes were compared using Welch’s t test. Categorical outcomes were compared using Fisher’s exact test. ResultsA total of 30 TCAR-F cases (January 2019 to May 2022) at our institution were compared against the regional VQI dataset (n = 2,535). TCAR-F cases had lower dose area product (5.67 Gy.cm2 vs 93.1 Gy.cm2; P < .0001), fluoroscopic time (8.07 minutes vs 16.4 minutes; P < .0001), and contrast use (13.49 mL vs 76.7 mL; P < .0001) as compared to regional averages of the same. TCAR-F cases had longer total operative time (117.3 minutes vs 80.9 minutes; P < .0001) and flow-reversal time (14.4 minutes vs 11.7 minutes; P = .025) than regional cases. A total of 30 TCAR-F cases (January 2019 to May 2022) at our institution were compared against the regional VQI dataset (n = 2,535). TCAR-F cases had lower dose area product (5.67 Gy.cm2 vs 93.1 Gy.cm2; P < .0001), fluoroscopic time (8.07 minutes vs 16.4 minutes; P < .0001), and contrast use (13.49 mL vs 76.7 mL; P < .0001) as compared to regional averages of the same. TCAR-F cases had longer total operative time (117.3 minutes vs 80.9 minutes; P < .0001) and flow-reversal time (14.4 minutes vs 11.7 minutes; P = .025) than regional cases. Conclusions

Dual-layer spectral CT fusion imaging for lung biopsies: more accurate targets, diagnostic samplings, and biomarker information?

The increasingly widespread use of computed tomography (CT) has increased the number of detected lung lesions, which are then subjected to needle biopsy to obtain histopathological diagnosis. Obtaining high-quality biopsy specimens is fundamental for diagnosis and biomolecular characterisation that guide therapy decision-making. In order to obtain samples with high diagnostic potential, fusion imaging techniques, such as fusion between positron emission tomography and CT, have been introduced to target the biopsy where there more viable neoplastic cells can be sampled. Nowadays, dual-layer spectral CT represents a novel technology enabling an increased tissue characterisation. In particular, Z-effective images, i.e., colour-coded images based on the effective atomic number of tissue components, provide a higher level of discrimination than usual imaged based on x-ray attenuation in Hounsfield units and offer the potential of a better tissue characterisation. Our hypothesis is based on the future use of data provided by spectral CT, in particular by Z-effective images, as a guide for appropriate biopsy sampling for histopathological and biomolecular characterisation in the era of patient tailored-therapy.

Reduction of inter-observer variability using MRI and CT fusion in delineating of primary tumor for radiotherapy in lung cancer with atelectasis

PurposeTo compare the difference between magnetic resonance imaging (MRI) and computed tomography (CT) in delineating the target area of lung cancer with atelectasis.MethodA retrospective analysis was performed on 15 patients with lung cancer accompanied by atelectasis. All positioning images were transferred to Eclipse treatment planning systems (TPSs). Six MRI sequences (T1WI, T1WI+C, T1WI+C Delay, T1WI+C 10 minutes, T2WI, DWI) were registered with positioning CT. Five radiation oncologists delineated the tumor boundary to obtain the gross tumor volume (GTV). Conformity index (CI) and dice coefficient (DC) were used to measure differences among observers.ResultsThe differences in delineation mean volumes, CI, and DC among CT and MRIs were significant. Multiple comparisons were made between MRI sequences and CT. Among them, DWI, T2WI, and T1WI+C 10 minutes sequences were statistically significant with CT in mean volumes, DC, and CI. The mean volume of DWI, T2WI, and T1WI+C 10 minutes sequence in the target area is significantly smaller than that on the CT sequence, but the consistency is higher than that of CT sequences.ConclusionsThe recognition of atelectasis by MRI was better than that by CT, which could reduce interobserver variability of primary tumor delineation in lung cancer with atelectasis. Among them, DWI, T2WI, T1WI+C 10 minutes may be a better choice to improve the GTV delineation of lung cancer patients with atelectasis.