Interactive segmentation framework of the Medical Imaging Interaction Toolkit

Radiomics in CT and MR imaging of the liver and pancreas: tools with potential for clinical application

Radiomics allows the extraction of quantitative imaging features from clinical magnetic resonance imaging (MRI) and computerized tomography (CT) studies. The advantages of radiomics have primarily been exploited in oncological applications, including better characterization and staging of oncological lesions and prediction of patient outcomes and treatment response. The potential introduction of radiomics in the clinical setting requires the establishment of a standardized radiomics pipeline and a quality assurance program. Radiomics and texture analysis of the liver have improved the differentiation of hypervascular lesions such as adenomas, focal nodular hyperplasia, and hepatocellular carcinoma (HCC) during the arterial phase, and in the pretreatment determination of HCC prognostic factors (e.g., tumor grade, microvascular invasion, Ki-67 proliferation index). Radiomics of pancreatic CT and MR images has enhanced pancreatic ductal adenocarcinoma detection and its differentiation from pancreatic neuroendocrine tumors, mass-forming chronic pancreatitis, or autoimmune pancreatitis. Radiomics can further help to better characterize incidental pancreatic cystic lesions, accurately discriminating benign from malignant intrapancreatic mucinous neoplasms. Nonetheless, despite their encouraging results and exciting potential, these tools have yet to be implemented in the clinical setting. This non-systematic review will describe the essential steps in the implementation of the radiomics and feature extraction workflow from liver and pancreas CT and MRI studies for their potential clinical application. A succinct overview of reported radiomics applications in the liver and pancreas and the challenges and limitations of their implementation in the clinical setting is also discussed, concluding with a brief exploration of the future perspectives of radiomics in the gastroenterology field.

Addressing image misalignments in multi-parametric prostate MRI for enhanced computer-aided diagnosis of prostate cancer

Prostate cancer (PCa) diagnosis on multi-parametric magnetic resonance images (MRI) requires radiologists with a high level of expertise. Misalignments between the MRI sequences can be caused by patient movement, elastic soft-tissue deformations, and imaging artifacts. They further increase the complexity of the task prompting radiologists to interpret the images. Recently, computer-aided diagnosis (CAD) tools have demonstrated potential for PCa diagnosis typically relying on complex co-registration of the input modalities. However, there is no consensus among research groups on whether CAD systems profit from using registration. Furthermore, alternative strategies to handle multi-modal misalignments have not been explored so far. Our study introduces and compares different strategies to cope with image misalignments and evaluates them regarding to their direct effect on diagnostic accuracy of PCa. In addition to established registration algorithms, we propose 'misalignment augmentation' as a concept to increase CAD robustness. As the results demonstrate, misalignment augmentations can not only compensate for a complete lack of registration, but if used in conjunction with registration, also improve the overall performance on an independent test set.

PIRET-A Platform for Treatment Planning in Electroporation-Based Therapies

Tissue electroporation is the basis of several therapies. Electroporation is performed by briefly exposing tissues to high electric fields. It is generally accepted that electroporation is effective where an electric field magnitude threshold is overreached. However, it is difficult to preoperatively estimate the field distribution because it is highly dependent on anatomy and treatment parameters.

OBJECTIVE

We developed PIRET, a platform to predict the treatment volume in electroporation-based therapies.

METHODS

The platform seamlessly integrates tools to build patient-specific models where the electric field is simulated to predict the treatment volume. Patient anatomy is segmented from medical images and 3D reconstruction aids in placing the electrodes and setting up treatment parameters.

RESULTS

Four canine patients that had been treated with high-frequency irreversible electroporation were retrospectively planned with PIRET and with a workflow commonly used in previous studies, which uses different general-purpose segmentation (3D Slicer) and modeling software (3Matic and COMSOL Multiphysics). PIRET outperformed the other workflow by 65 minutes (× 1.7 faster), thanks to the improved user experience during treatment setup and model building. Both approaches computed similarly accurate electric field distributions, with average Dice scores higher than 0.93.

CONCLUSION

A platform which integrates all the required tools for electroporation treatment planning is presented. Treatment plan can be performed rapidly with minimal user interaction in a stand-alone platform.

SIGNIFICANCE

This platform is, to the best of our knowledge, the most complete software for treatment planning of irreversible electroporation. It can potentially be used for other electroporation applications.

Quantitative magnetic resonance imaging biomarkers for cortical pathology in multiple sclerosis at 7 T

Substantial cortical gray matter tissue damage, which correlates with clinical disease severity, has been revealed in multiple sclerosis (MS) using advanced magnetic resonance imaging (MRI) methods at 3 T and the use of ultra-high field, as well as in histopathology studies. While clinical assessment mainly focuses on lesions using T 1 - and T 2 -weighted MRI, quantitative MRI (qMRI) methods are capable of uncovering subtle microstructural changes. The aim of this ultra-high field study is to extract possible future MR biomarkers for the quantitative evaluation of regional cortical pathology. Because of their sensitivity to iron, myelin, and in part specifically to cortical demyelination, T 1 , T 2 , R 2 * , and susceptibility mapping were performed including two novel susceptibility markers; in addition, cortical thickness as well as the volumes of 34 cortical regions were computed. Data were acquired in 20 patients and 16 age- and sex-matched healthy controls. In 18 cortical regions, large to very large effect sizes (Cohen's d ≥ 1) and statistically significant differences in qMRI values between patients and controls were revealed compared with only four regions when using more standard MR measures, namely, volume and cortical thickness. Moreover, a decrease in all susceptibility contrasts ( χ , χ + , χ - ) and R 2 * values indicates that the role of cortical demyelination might outweigh inflammatory processes in the form of iron accumulation in cortical MS pathology, and might also indicate iron loss. A significant association between susceptibility contrasts as well as R 2 * of the caudal middle frontal gyrus and disease duration was found (adjusted R² : 0.602, p = 0.0011). Quantitative MRI parameters might be more sensitive towards regional cortical pathology compared with the use of conventional markers only and therefore may play a role in early detection of tissue damage in MS in the future.

Mitochondrial network expansion and dynamic redistribution during islet morphogenesis in zebrafish larvae

Mitochondria, organelles critical for energy production, modify their shape and location in response to developmental state and metabolic demands. Mitochondria are altered in diabetes, but the mechanistic basis is poorly defined, due to difficulties in assessing mitochondria within an intact organism. Here, we use in vivo imaging in transparent zebrafish larvae to demonstrate filamentous, interconnected mitochondrial networks within islet cells. Mitochondrial movements highly resemble what has been reported for human islet cells in vitro, showing conservation in behaviour across species and cellular context. During islet development, mitochondrial content increases with emergence of cell motility, and mitochondria disperse within fine protrusions. Overall, this work presents quantitative analysis of mitochondria within their native environment and provides insights into mitochondrial behaviour during organogenesis.

Next-generation personalized cranioplasty treatment

Decompressive craniectomy (DC) is a surgical procedure, that is followed by cranioplasty surgery. DC is usually performed to treat patients with traumatic brain injury, intracranial hemorrhage, cerebral infarction, brain edema, skull fractures, etc. In many published clinical case studies and systematic reviews, cranioplasty surgery is reported to restore cranial symmetry with good cosmetic outcomes and neurophysiologically relevant functional outcomes in hundreds of patients. In this review article, we present a number of key issues related to the manufacturing of patient-specific implants, clinical complications, cosmetic outcomes, and newer alternative therapies. While discussing alternative therapeutic treatments for cranioplasty, biomolecules and cellular-based approaches have been emphasized. The current clinical practices in the restoration of cranial defects involve 3D printing to produce patient-specific prefabricated cranial implants, that provide better cosmetic outcomes. Regardless of the advancements in image processing and 3D printing, the complete clinical procedure is time-consuming and requires significant costs. To reduce manual intervention and to address unmet clinical demands, it has been highlighted that automated implant fabrication by data-driven methods can accelerate the design and manufacturing of patient-specific cranial implants. The data-driven approaches, encompassing artificial intelligence (machine learning/deep learning) and E-platforms, such as publicly accessible clinical databases will lead to the development of the next generation of patient-specific cranial implants, which can provide predictable clinical outcomes. STATEMENT OF SIGNIFICANCE: Cranioplasty is performed to reconstruct cranial defects of patients who have undergone decompressive craniectomy. Cranioplasty surgery improves the aesthetic and functional outcomes of those patients. To meet the clinical demands of cranioplasty surgery, accelerated designing and manufacturing of 3D cranial implants are required. This review provides an overview of biomaterial implants and bone flap manufacturing methods for cranioplasty surgery. In addition, tissue engineering and regenerative medicine-based approaches to reduce clinical complications are also highlighted. The potential use of data-driven computer applications and data-driven artificial intelligence-based approaches are emphasized to accelerate the clinical protocols of cranioplasty treatment with less manual intervention and shorter intraoperative time.

Anatomically Accurate, High-Resolution Modeling of the Human Index Finger Using In Vivo Magnetic Resonance Imaging

Anatomically accurate models of a human finger can be useful in simulating various disorders. In order to have potential clinical value, such models need to include a large number of tissue types, identified by an experienced professional, and should be versatile enough to be readily tailored to specific pathologies. Magnetic resonance images were acquired at ultrahigh magnetic field (7 T) with a radio-frequency coil specially designed for finger imaging. Segmentation was carried out under the supervision of an experienced radiologist to accurately capture various tissue types (TTs). The final segmented model of the human index finger had a spatial resolution of 0.2 mm and included 6,809,600 voxels. In total, 15 TTs were identified: subcutis, Pacinian corpuscle, nerve, vein, artery, tendon, collateral ligament, volar plate, pulley A4, bone, cartilage, synovial cavity, joint capsule, epidermis and dermis. The model was applied to the conditions of arthritic joint, ruptured tendon and variations in the geometry of a finger. High-resolution magnetic resonance images along with careful segmentation proved useful in the construction of an anatomically accurate model of the human index finger. An example illustrating the utility of the model in biomedical applications is shown. As the model includes a number of tissue types, it may present a solid foundation for future simulations of various musculoskeletal disease processes in human joints.

Prediction of Implant Size Based on Breast Volume Using Mammography with Fully Automated Measurements and Breast MRI

BACKGROUND

Determination of implant size is crucial for patients with breast cancer undergoing one-stage breast reconstruction. The purpose of this study is to predict the implant size based on the breast volume measured by mammography (MG) with a fully automated method, and by breast magnetic resonance imaging (MRI) with a semi-automated method, in breast cancer patients with direct-to-implant reconstruction.

PATIENTS AND METHODS

This retrospective study included 84 patients with breast cancer who underwent direct-to-implant reconstruction after nipple-sparing or skin-sparing mastectomy and preoperative MG and MRI between April 2015 and April 2019. Breast volume was measured using (a) MG with a fully automated commercial software and (b) MRI with an in-house semi-automated software program. Multivariable regression analyses including breast volume and patient weight (P < 0.05 in univariable analysis) were conducted to predict implant size.

RESULTS

MG and MRI breast volume was highly correlated with both implant size (correlation coefficient 0.862 and 0.867, respectively; P values < 0.001) and specimen weight (correlation coefficient 0.802 and 0.852, respectively; P values < 0.001). Mean absolute difference between the MR breast volume and implant size was 160 cc, which was significantly higher than that between the MG breast volume and implant size of 118 cc (P < 0.001). On multivariable analyses, only breast volume measured by both MG and MRI was significantly associated with implant size in any implant type (all P values < 0.001).

CONCLUSION

Breast volume measured by MG and MRI can be used to predict appropriate implant size in breast cancer patients undergoing direct-to-implant reconstruction in an efficient and objective manner.

MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets

Purpose

To introduce a widely applicable workflow for pulmonary lobe segmentation of MR images using a recurrent neural network (RNN) trained with chest CT datasets. The feasibility is demonstrated for 2D coronal ultrafast balanced SSFP (ufSSFP) MRI.

Methods

Lung lobes of 250 publicly accessible CT datasets of adults were segmented with an open‐source CT‐specific algorithm. To match 2D ufSSFP MRI data of pediatric patients, both CT data and segmentations were translated into pseudo‐MR images that were masked to suppress anatomy outside the lung. Network‐1 was trained with pseudo‐MR images and lobe segmentations and then applied to 1000 masked ufSSFP images to predict lobe segmentations. These outputs were directly used as targets to train Network‐2 and Network‐3 with non‐masked ufSSFP data as inputs, as well as an additional whole‐lung mask as input for Network‐2. Network predictions were compared to reference manual lobe segmentations of ufSSFP data in 20 pediatric cystic fibrosis patients. Manual lobe segmentations were performed by splitting available whole‐lung segmentations into lobes.

Results

Network‐1 was able to segment the lobes of ufSSFP images, and Network‐2 and Network‐3 further increased segmentation accuracy and robustness. The average all‐lobe Dice similarity coefficients were 95.0 ± 2.8 (mean ± pooled SD [%]) and 96.4 ± 2.5, 93.0 ± 2.0; and the average median Hausdorff distances were 6.1 ± 0.9 (mean ± SD [mm]), 5.3 ± 1.1, 7.1 ± 1.3 for Network‐1, Network‐2, and Network‐3, respectively.

Conclusion

Recurrent neural network lung lobe segmentation of 2D ufSSFP imaging is feasible, in good agreement with manual segmentations. The proposed workflow might provide access to automated lobe segmentations for various lung MRI examinations and quantitative analyses.

Multiparametric MRI for Characterization of the Basal Ganglia and the Midbrain

Objectives To characterize subcortical nuclei by multi-parametric quantitative magnetic resonance imaging.

Materials and Methods: The following quantitative multiparametric MR data of five healthy volunteers were acquired on a 7T MRI system: 3D gradient echo (GRE) data for the calculation of quantitative susceptibility maps (QSM), GRE sequences with and without off-resonant magnetic transfer pulse for magnetization transfer ratio (MTR) calculation, a magnetization−prepared 2 rapid acquisition gradient echo sequence for T₁ mapping, and (after a coil change) a density-adapted 3D radial pulse sequence for ²³Na imaging. First, all data were co-registered to the GRE data, volumes of interest (VOIs) for 21 subcortical structures were drawn manually for each volunteer, and a combined voxel-wise analysis of the four MR contrasts (QSM, MTR, T₁, ²³Na) in each structure was conducted to assess the quantitative, MR value-based differentiability of structures. Second, a machine learning algorithm based on random forests was trained to automatically classify the groups of multi-parametric voxel values from each VOI according to their association to one of the 21 subcortical structures.

Results The analysis of the integrated multimodal visualization of quantitative MR values in each structure yielded a successful classification among nuclei of the ascending reticular activation system (ARAS), the limbic system and the extrapyramidal system, while classification among (epi-)thalamic nuclei was less successful. The machine learning-based approach facilitated quantitative MR value-based structure classification especially in the group of extrapyramidal nuclei and reached an overall accuracy of 85% regarding all selected nuclei.

Conclusion Multimodal quantitative MR enabled excellent differentiation of a wide spectrum of subcortical nuclei with reasonable accuracy and may thus enable sensitive detection of disease and nucleus-specific MR-based contrast alterations in the future.

Building Three-Dimensional Intracranial Aneurysm Models from 3D-TOF MRA: a Validation Study

To create realistic three-dimensional (3D) vascular models from 3D time-of-flight magnetic resonance angiography (3D-TOF MRA) of an intracranial aneurysm (IA). Thirty-two IAs in 31 patients were printed using 3D-TOF MRA source images from polylactic acid (PLA) raw material. Two observers measured the maximum IA diameter at the longest width twice separately. A total mean of four measurements as well as each observer's individual average MRA lengths were calculated. After printing, 3D-printed anatomic models (PAM) underwent computed tomography (CT) acquisition and each observer measured them using the same algorithm as applied to MRA. Inter- and intra-observer consistency for the MRA and CT measurements were analyzed using the intraclass correlation coefficient (ICC) and a Bland-Altman plot. The mean maximum aneurysm diameter obtained from four MRA evaluations was 8.49 mm, whereas it was 8.83 mm according to the CT 3D PAM measurement. The Wilcoxon test revealed slightly larger mean CT 3D PAM diameters than the MRA measurements. The Spearman's correlation test yielded a positive correlation between MRA and CT lengths of 3D PAMs. Inter and intra-observer consistency were high in consecutive MRA and CT measurements. According to Bland-Altman analyses, the aneurysmal dimensions obtained from CT were higher for observer 1 and observer 2 (a mean of 0.32 mm and 0.35 mm, respectively) compared to the MRA measurements. CT dimensions were slightly overestimated compared to MRA measurements of the created models. We believe the discrepancy may be related to the Laplacian algorithm applied for surface smoothing and the high slice thickness selection that was used. However, ICC provided high consistency and reproducibility in our cohort. Therefore, it is technically possible to produce 3D intracranial aneurysm models from 3D-TOF MRA images.

Digital three-dimensional visualization of intrabony periodontal defects for regenerative surgical treatment planning

Background

In the regenerative treatment of intrabony periodontal defects, surgical strategies are primarily determined by defect morphologies. In certain cases, however, direct clinical measurements and intraoral radiographs do not provide sufficient information on defect morphologies. Therefore, the application of cone-beam computed tomography (CBCT) has been proposed in specific cases. 3D virtual models reconstructed with automatic thresholding algorithms have already been used for diagnostic purposes. The aim of this study was to utilize 3D virtual models, generated with a semi-automatic segmentation method, for the treatment planning of minimally invasive periodontal surgeries and to evaluate the accuracy of the virtual models, by comparing digital measurements to direct intrasurgical measurements.

Methods

Four patients with a total of six intrabony periodontal defects were enrolled in the present study. Two months following initial periodontal treatment, a CBCT scan was taken. The novel semi-automatic segmentation method was performed in an open-source medical image processing software (3D Slicer) to acquire virtual 3D models of alveolar and dental structures. Intrasurgical and digital measurements were taken, and results were compared to validate the accuracy of the digital models. Defect characteristics were determined prior to surgery with conventional diagnostic methods and 3D virtual models. Diagnostic assessments were compared to the actual defect morphology during surgery.

Results

Differences between intrasurgical and digital measurements in depth and width of intrabony components of periodontal defects averaged 0.31 ± 0.21 mm and 0.41 ± 0.44 mm, respectively. In five out of six cases, defect characteristics could not be assessed precisely with direct clinical measurements and intraoral radiographs. 3D models generated with the presented semi-automatic segmentation method depicted the defect characteristics correctly in all six cases.

Conclusion

It can be concluded that 3D virtual models acquired with the described semi-automatic segmentation method provide accurate information on intrabony periodontal defect morphologies, thus influencing the treatment strategy. Within the limitations of this study, models were found to be accurate; however, further investigation with a standardized validation process on a large number of participants has to be conducted.

The impact of segmentation on whole-lung functional MRI quantification: Repeatability and reproducibility from multiple human observers and an artificial neural network

PURPOSE

To investigate the repeatability and reproducibility of lung segmentation and their impact on the quantitative outcomes from functional pulmonary MRI. Additionally, to validate an artificial neural network (ANN) to accelerate whole-lung quantification.

METHOD

Ten healthy children and 25 children with cystic fibrosis underwent matrix pencil decomposition MRI (MP-MRI). Impaired relative fractional ventilation (R_FV ) and relative perfusion (R_Q ) from MP-MRI were compared using whole-lung segmentation performed by a physician at two time-points (A_t1 and A_t2 ), by an MRI technician (B), and by an ANN (C). Repeatability and reproducibility were assess with Dice similarity coefficient (DSC), paired t-test and Intraclass-correlation coefficient (ICC).

RESULTS

The repeatability within an observer (A_t1 vs A_t2 ) resulted in a DSC of 0.94 ± 0.01 (mean ± SD) and an unsystematic difference of -0.01% for R_FV (P = .92) and +0.1% for R_Q (P = .21). The reproducibility between human observers (A_t1 vs B) resulted in a DSC of 0.88 ± 0.02, and a systematic absolute difference of -0.81% (P < .001) for R_FV and -0.38% (P = .037) for R_Q . The reproducibility between human and the ANN (A_t1 vs C) resulted in a DSC of 0.89 ± 0.03 and a systematic absolute difference of -0.36% for R_FV (P = .017) and -0.35% for R_Q (P = .002). The ICC was >0.98 for all variables and comparisons.

CONCLUSIONS

Despite high overall agreement, there were systematic differences in lung segmentation between observers. This needs to be considered for longitudinal studies and could be overcome by using an ANN, which performs as good as human observers and fully automatizes MP-MRI post-processing.

Toward quantitative neuroimaging biomarkers for Friedreich's ataxia at 7 Tesla: Susceptibility mapping, diffusion imaging, R2 and R1 relaxometry

Friedreich's ataxia (FRDA) is a rare genetic disorder leading to degenerative processes. So far, no effective treatment has been found. Therefore, it is important to assist the development of medication with imaging biomarkers reflecting disease status and progress. Ten FRDA patients (mean age 37 ± 14 years; four female) and 10 age- and sex-matched controls were included. Acquisition of magnetic resonance imaging (MRI) data for quantitative susceptibility mapping, R₁ , R₂ relaxometry and diffusion imaging was performed at 7 Tesla. Results of volume of interest (VOI)-based analyses of the quantitative data were compared with a voxel-based morphometry (VBM) evaluation. Differences between patients and controls were assessed using the analysis of covariance (ANCOVA; p < 0.01) with age and sex as covariates, effect size of group differences, and correlations with disease characteristics with Spearman correlation coefficient. For the VBM analysis, a statistical threshold of 0.001 for uncorrected and 0.05 for corrected p-values was used. Statistically significant differences between FRDA patients and controls were found in five out of twelve investigated structures, and statistically significant correlations with disease characteristics were revealed. Moreover, VBM revealed significant white matter atrophy within regions of the brainstem, and the cerebellum. These regions overlapped partially with brain regions for which significant differences between healthy controls and patients were found in the VOI-based quantitative MRI evaluation. It was shown that two independent analyses provided overlapping results. Moreover, positive results on correlations with disease characteristics were found, indicating that these quantitative MRI parameters could provide more detailed information and assist the search for effective treatments.

Mapping the human brainstem: Brain nuclei and fiber tracts at 3 T and 7 T

Structural high-resolution imaging of the brainstem can be of high importance in clinical practice. However, ultra-high field magnetic resonance imaging (MRI) is still restricted in use due to limited availability. Therefore, quantitative MRI techniques (quantitative susceptibility mapping [QSM], relaxation measurements [ R2* , R₁ ], diffusion tensor imaging [DTI]) and T₂ - and proton density (PD)-weighted imaging in the human brainstem at 3 T and 7 T are compared. Five healthy volunteers (mean age: 21.5 ± 1.9 years) were measured at 3 T and 7 T using multi-echo gradient echo sequences for susceptibility mapping and R2* relaxometry, magnetization-prepared 2 rapid acquisition gradient echo sequences for R₁ relaxometry, turbo-spin echo sequences for PD- and T₂ -weighted imaging and readout-segmented echo planar sequences for DTI. Susceptibility maps were computed using Laplacian-based phase unwrapping, V-SHARP for background field removal and the streaking artifact reduction for QSM algorithm for dipole inversion. Contrast-to-noise ratios (CNRs) were determined at 3 T and 7 T in ten volumes of interest (VOIs). Data acquired at 7 T showed higher CNR. However, in four VOIs, lower CNR was observed for R2* at 7 T. QSM was shown to be the contrast with which the highest number of structures could be identified. The depiction of very fine tracts such as the medial longitudinal fasciculus throughout the brainstem was only possible in susceptibility maps acquired at 7 T. DTI effectively showed the main tracts (crus cerebri, transverse pontine fibers, corticospinal tract, middle and superior cerebellar peduncle, pontocerebellar tract, and pyramid) at both field strengths. Assessing the brainstem with quantitative MRI methods such as QSM, R2* , as well as PD- and T₂ -weighted imaging with great detail, is also possible at 3 T, especially when using susceptibility mapping calculated from a gradient echo sequence with a wide range of echo times from 10.5 to 52.5 ms. However, tracing smallest structures strongly benefits from imaging at ultra-high field.

Water Jet Applicator for Interface Tissue Removal in Minimally Invasive Hip Refixation: Testing the Principle and Design of Prototype

Mechanical loosening of implants is in the majority accompanied with a periprosthetic interface membrane, which has to be removed during revision surgery. The same is true if a minimal invasive (percutaneous) refixation of a loose implant is done. We describe the requirements for a waterjet applicator for interface tissue removal for this percutaneous hip refixation technique. The technical requirements were either obtained from a literature review, a theoretical analysis, or by experimental setup. Based on the requirements, a waterjet applicator is designed which is basically a flexible tube (outer diameter 3 mm) with two channels. One channel for the water supply (diameter 0.9 mm) and one for suction to evacuate water and morcellated interface tissue from the periprosthetic cavity. The applicator has a rigid tip (length 6 mm), which directs the water flow to create two waterjets (diameter 0.2 mm), both focused into the suction channel. The functionality of this new applicator is demonstrated by testing a prototype of the applicator tip in an in vitro experimental setup. This testing has shown that the designed applicator for interface tissue removal will eliminate the risk of water pressure buildup; the ejected water was immediately evacuated from the periprosthetic cavity. Blocking of the suction opening was prevented because the jets cut through interface tissue that gets in front of the suction channel. Although further development of the water applicator is necessary, the presented design of the applicator is suitable for interface tissue removal in a minimally invasive hip refixation procedure.

Shape-based interpolation method in measuring intracranial volume for pre- and post-operative decompressive craniectomy using open source software

INTRODUCTION

Intracranial volume (ICV) is an important tool in the management of patients undergoing decompressive craniectomy (DC) surgery. The aim of this study was to validate ICV measurement applying the shape-based interpolation (SBI) method using open source software on computed tomography (CT) images.

METHODS

The pre- and post-operative CT images of 55 patients undergoing DC surgery were analyzed. The ICV was measured by segmenting every slice of the CT images, and compared with estimated ICV calculated using the 1-in-10 sampling strategy and processed using the SBI method. An independent t test was conducted to compare the ICV measurements between the two different methods. The calculation using this method was repeated three times for reliability analysis using the intraclass correlations coefficient (ICC). The Bland-Altman plot was used to measure agreement between the methods for both pre- and post-operative ICV measurements.

RESULTS

The mean ICV (±SD) were 1341.1±122.1ml (manual) and 1344.11±122.6ml (SBI) for the preoperative CT data. The mean ICV (±SD) were 1396.4±132.4ml (manual) and 1400.53±132.1ml (SBI) for the post-operative CT data. No significant difference was found in ICV measurements using the manual and the SBI methods (p=.983 for pre-op, and p=.960 for post-op). The intrarater ICC showed a significant correlation; ICC=1.00. The Bland-Altman plot showed good agreement between the manual and the SBI method.

CONCLUSION

The shape-based interpolation method with 1-in-10 sampling strategy gave comparable results in estimating ICV compared to manual segmentation. Thus, this method could be used in clinical settings for rapid, reliable and repeatable ICV estimations.

Modeling Left Atrial Flow, Energy, Blood Heating Distribution in Response to Catheter Ablation Therapy

Introduction: Atrial fibrillation (AF) is a widespread cardiac arrhythmia that commonly affects the left atrium (LA), causing it to quiver instead of contracting effectively. This behavior is triggered by abnormal electrical impulses at a specific site in the atrial wall. Catheter ablation (CA) treatment consists of isolating this driver site by burning the surrounding tissue to restore sinus rhythm (SR). However, evidence suggests that CA can concur to the formation of blood clots by promoting coagulation near the heat source and in regions with low flow velocity and blood stagnation.

Methods: A patient-specific modeling workflow was created and applied to simulate thermal-fluid dynamics in two patients pre- and post-CA. Each model was personalized based on pre- and post-CA imaging datasets. The wall motion and anatomy were derived from SSFP Cine MRI data, while the trans-valvular flow was based on Doppler ultrasound data. The temperature distribution in the blood was modeled using a modified Pennes bioheat equation implemented in a finite-element based Navier-Stokes solver. Blood particles were also classified based on their residence time in the LA using a particle-tracking algorithm.

Results: SR simulations showed multiple short-lived vortices with an average blood velocity of 0.2-0.22 m/s. In contrast, AF patients presented a slower vortex and stagnant flow in the LA appendage, with the average blood velocity reduced to 0.08–0.14 m/s. Restoration of SR also increased the blood kinetic energy and the viscous dissipation due to the presence of multiple vortices. Particle tracking showed a dramatic decrease in the percentage of blood remaining in the LA for longer than one cycle after CA (65.9 vs. 43.3% in patient A and 62.2 vs. 54.8% in patient B). Maximum temperatures of 76° and 58°C were observed when CA was performed near the appendage and in a pulmonary vein, respectively.

Conclusion: This computational study presents novel models to elucidate relations between catheter temperature, patient-specific atrial anatomy and blood velocity, and predict how they change from SR to AF. The models can quantify blood flow in critical regions, including residence times and temperature distribution for different catheter positions, providing a basis for quantifying stroke risks.

Ventilation and perfusion assessed by functional MRI in children with CF: reproducibility in comparison to lung function

BACKGROUND

Chronic lung diseases such as cystic fibrosis (CF) can be monitored by imaging and lung function modalities. Magnetic resonance imaging (MRI) techniques such as matrix pencil (MP) decomposition allows for evaluation of regional impairment of fractional ventilation (R_FV) and relative perfusion (R_Q). However, reproducibility of MP MRI outcomes in children with CF is unknown. We examined short-term variability of ventilation and perfusion impairment from MP MRI and compared this to lung function outcomes.

METHOD

Twenty-threeCF and 12 healthy school-aged children underwent MRI and lung function tests on the same day on two occasions 24 h apart. Global ventilation inhomogeneity was assessed by the lung clearance index (LCI) from nitrogen-multiple breath washout (N₂-MBW) technique. Intra-class-coefficient (ICC), percentage change, and Bland-Altman limits of agreement were evaluated to assess reproducibility.

RESULTS

Sixty-nine measurements from MP MRI and N₂-MBW were performed. The ICC between two visits for R_FV, R_Q and LCI ranged between 0.60 and 0.90 in individuals with CF and healthy controls. In individuals with CF, percentage of change between the visits was 0.02% for R_FV, -1.11% for R_Q and 2.91% for LCI and limits of agreement between visits were - 4.3% and 3.9% for R_FV, -4.4% and 3.7% for R_Q, and -2.6 and 3.0 for LCI.

CONCLUSIONS

Functional imaging is reproducible and short-term changes in R_FV and R_Q greater than ±4.4% can be considered clinical meaningful. Very good short-term reproducibility, and easy application without the need for breathing maneuvers or contrast agent, makes MP MRI a promising surveillance method for CF.

Mask-Adapted Background Field Removal for Artifact Reduction in Quantitative Susceptibility Mapping of the Prostate

We propose an alternative processing method for quantitative susceptibility mapping of the prostate that reduces artifacts and enables better visibility and quantification of calcifications and other lesions. Three-dimensional gradient-echo magnetic resonance data were obtained from 26 patients at 3 T who previously received a planning computed tomography of the prostate. Phase images were unwrapped using Laplacian-based phase unwrapping. The background field was removed with the V-SHARP method using tissue masks for the entire abdomen (Method 1) and masks that excluded bone and the rectum (Method 2). Susceptibility maps were calculated with the iLSQR method. The quality of susceptibility maps was assessed by one radiologist and two physicists who rated the data for visibility of lesions and data quality on a scale from 1 (poor) to 4 (good). The readers rated susceptibility maps computed with Method 2 to be, on average, better for visibility of lesions with a score of 2.9 ± 1.1 and image quality with a score of 2.8 ± 0.8 compared with maps computed with Method 1 (2.4 ± 1.2/2.3 ± 1.0). Regarding strong artifacts, these could be removed using adapted masks, and the susceptibility values seemed less biased by the artifacts. Thus, using an adapted mask for background field removal when calculating susceptibility maps of the prostate from phase data reduces artifacts and improves visibility of lesions.

MITK Diffusion Imaging

Background: Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of tissue structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop the algorithmic tools necessary to cope with the complexity of the datasets.

Objectives: This work illustrates our strategy that encompasses the development of a modularized and open software tool for data processing, visualization and interactive exploration in diffusion imaging research and aims at reinforcing sustainable evaluation and progress in the field.

Methods: In this paper, the usability and capabilities of a new application and toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITKDI, are demonstrated using in-vivo datasets.

Results: MITK-DI provides a comprehensive software framework for high-performance data processing, analysis and interactive data exploration, which is designed in a modular, extensible fashion (using CTK) and in adherence to widely accepted coding standards (e.g. ITK, VTK). MITK-DI is available both as an open source software development toolkit and as a ready-to-use in stallable application.

Conclusions: The open source release of the modular MITK-DI tools will increase verifiability and comparability within the research community and will also be an important step towards bringing many of the current techniques towards clinical application.

Dynamic and steady-state oxygen-dependent lung relaxometry using inversion recovery ultra-fast steady-state free precession imaging at 1.5 T

PURPOSE

To demonstrate the feasibility of oxygen-dependent relaxometry in human lung using an inversion recovery ultra-fast steady-state free precession (IR-ufSSFP) technique.

METHODS

Electrocardiogram-triggered pulmonary relaxometry with IR-ufSSFP was performed in 7 healthy human subjects at 1.5 T. The data were acquired under both normoxic and hyperoxic conditions. In a single breath-hold of less than 9 seconds, 30 transient state IR-ufSSFP images were acquired, yielding longitudinal (T1) and transversal (T2) relaxometry parameter maps using voxel-wise nonlinear fitting. Possible spatial misalignments between consecutive IR-ufSSFP parameter maps were corrected using elastic image registration. Furthermore, dynamic relaxometry oxygen wash-in and wash-out scans were performed in one volunteer. From this, T₁ -related wash-in and wash-out time constants (τ_wi , τ_wo ) were calculated voxel-wise on registered maps using an exponential fitting model.

RESULTS

For healthy lung, observed T1 values were 1399 ± 77 and 1290 ± 76 ms under normoxic and hyperoxic conditions, respectively. Oxygen-related reduction of T1 was statistically significant in every volunteer. No statistically significant change, however, was observed in T2, with normoxic and hyperoxic T2 values of 55 ± 16 and 56 ± 17 ms, respectively. The observed average τ_wi was 87.0 ± 28.7 seconds, whereas the average τ_wo was 73.5 ± 21.6 seconds.

CONCLUSION

IR-ufSSFP allows fast, steady-state, and dynamic oxygen-dependent relaxometry of the human lung. Magn Reson Med 79:839-845, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Postoperative liver volume was accurately predicted by a medical image three dimensional visualization system in hepatectomy for liver cancer

BACKGROUND

Liver cancer is the second most common cause of cancer death worldwide. The hepatectomy is the most effective and the only potentially curative treatment for patients with resectable neoplasm. Precisely preoperative assessment of remnant liver volume is essential in preventing postoperative liver failure. The aim of our study is to report our experience of using a medical image three dimensional (3D) visualization system (MI-3DVS), which was developed by our team, in assisting hepatectomy for patients with liver cancer.

METHODS

Between January 2010 and June 2016, 69 patients with liver cancer underwent hepatic resection based on the MI-3DVS were enrolled in this study. All patients underwent CT scan 5 days before the surgery and within 5 days after resection. CT images were reconstructed with the MI-3DVS to assist to perform hepatectomy. Simple linear regression, intra-class correlation coefficient (ICC) and Bland-Altman analysis were used to evaluate the relationship and agreement between actual excisional liver volume (AELV) and predicted excisional liver volume (PELV).

RESULTS

Among 69 patients in this study, 62(89.85%) of them were diagnosed with hepatocellular carcinoma by histopathologic examination, and 41(59.42%) underwent major hepatectomy. The average AELV was 330.13 cm³ and the average PELV was 287.67 cm³. The simple regression equation is AELV = 1.016 × PELV+30.39(r = 0.966; p < 0.0003). PELV (ICC = 0.964) achieved an excellent agreement with AELV with statistical significance (p < 0.001). 65 of 69 dots are in the range of 95% confidence interval in Bland-Altman analyses.

CONCLUSIONS

The MI-3DVS has advantages of simple usage and convenient hold. It is accurate in assessment of postoperative liver volume and improve safety in liver resection.

Comparison of liver volumetry on contrast-enhanced CT images: one semiautomatic and two automatic approaches

This study was to evaluate the accuracy, consistency, and efficiency of three liver volumetry methods- one interactive method, an in-house-developed 3D medical Image Analysis (3DMIA) system, one automatic active shape model (ASM)-based segmentation, and one automatic probabilistic atlas (PA)-guided segmentation method on clinical contrast-enhanced CT images. Forty-two datasets, including 27 normal liver and 15 space-occupying liver lesion patients, were retrospectively included in this study. The three methods - one semiautomatic 3DMIA, one automatic ASM-based, and one automatic PA-based liver volumetry - achieved an accuracy with VD (volume difference) of -1.69%, -2.75%, and 3.06% in the normal group, respectively, and with VD of -3.20%, -3.35%, and 4.14% in the space-occupying lesion group, respectively. However, the three methods achieved an efficiency of 27.63 mins, 1.26 mins, 1.18 mins on average, respectively, compared with the manual volumetry, which took 43.98 mins. The high intraclass correlation coefficient between the three methods and the manual method indicated an excel-lent agreement on liver volumetry. Significant differences in segmentation time were observed between the three methods (3DMIA, ASM, and PA) and the manual volumetry (p < 0.001), as well as between the automatic volumetries (ASM and PA) and the semiautomatic volumetry (3DMIA) (p < 0.001). The semiautomatic interactive 3DMIA, automatic ASM-based, and automatic PA-based liver volum-etry agreed well with manual gold standard in both the normal liver group and the space-occupying lesion group. The ASM- and PA-based automatic segmentation have better efficiency in clinical use.

Pulmonary relaxometry with inversion recovery ultra-fast steady-state free precession at 1.5T

PURPOSE

To present a technique for simultaneous mapping of T₁ , T₂ , and relative spin density (M₀ ) in human lung using inversion recovery ultra-fast steady-state free precession (IR-ufSSFP) imaging.

METHODS

Pulmonary relaxometry with IR-ufSSFP is based on an interleaved time series acquisition of 2D images acquired at 1.5T. The technique was tested in a phantom and in four healthy volunteers using breath-hold and electrocardiogram triggering. Typically, 30 transient state images were acquired in a single breath-hold within < 10 s. From the signal time course, voxel-wise nonlinear fitting yielded T₁ , T₂ , and M₀ parameter maps. Furthermore, off-resonance and B1 effects were investigated in a phantom.

RESULTS

In the phantom, the observed T₁ of 829 ± 2 ms and T₂ of 105 ± 4 ms were in agreement with the reference T₁ of 858 ± 1 ms and T₂ of 104 ± 1 ms using spin echo methods. In volunteers, the average T₁ of 1375 ± 102 ms and T₂ of 66 ± 26 ms of lung tissue were in good agreement with the literature and were observed to be independent of the respiratory phase. Overall, high reproducibility was shown in a volunteer, yielding coefficient of variations of 0.03 for M₀ , 0.004 for T₁ , and 0.04 for T₂ measurements.

CONCLUSION

IR-ufSSFP allows for fast and simultaneous quantitative mapping of the human lung. Magn Reson Med 77:74-82, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Automatic Segmentation of Wrist Bones in CT Using a Statistical Wrist Shape + Pose Model

Segmentation of the wrist bones in CT images has been frequently used in different clinical applications including arthritis evaluation, bone age assessment and image-guided interventions. The major challenges include non-uniformity and spongy textures of the bone tissue as well as narrow inter-bone spaces. In this work, we propose an automatic wrist bone segmentation technique for CT images based on a statistical model that captures the shape and pose variations of the wrist joint across 60 example wrists at nine different wrist positions. To establish the correspondences across the training shapes at neutral positions, the wrist bone surfaces are jointly aligned using a group-wise registration framework based on a Gaussian Mixture Model. Principal component analysis is then used to determine the major modes of shape variations. The variations in poses not only across the population but also across different wrist positions are incorporated in two pose models. An intra-subject pose model is developed by utilizing the similarity transforms at all wrist positions across the population. Further, an inter-subject pose model is used to model the pose variations across different wrist positions. For segmentation of the wrist bones in CT images, the developed model is registered to the edge point cloud extracted from the CT volume through an expectation maximization based probabilistic approach. Residual registration errors are corrected by application of a non-rigid registration technique. We validate the proposed segmentation method by registering the wrist model to a total of 66 unseen CT volumes of average voxel size of 0.38 mm. We report a mean surface distance error of 0.33 mm and a mean Jaccard index of 0.86.

Potential of quantitative susceptibility mapping for detection of prostatic calcifications

PURPOSE

To evaluate whether quantitative susceptibility (QSM) may be used as an alternative to computed tomography (CT) to detect calcification in prostate cancer patients.

MATERIALS AND METHODS

Susceptibility map calculation was performed using 3D gradient echo magnetic resonance imaging (MRI) data from 26 patients measured at 3T who previously received a planning CT of the prostate. Phase images were unwrapped using Laplacian-based phase unwrapping, the background field was removed with the V-SHARP method, and susceptibility maps were calculated with the iLSQR method. Two blinded readers were asked to identify peri- and intraprostatic calcifications.

RESULTS

Average mean and minimum susceptibility values (referenced to iliopsoas muscle) of calcifications were -0.249 ± 0.179 ppm and -0.551 ± 0.323 ppm, and average mean and maximum intensities in CT images were 319 ± 164 HU and 679 ± 392 HU. Twenty-one and 17 out of 22 prostatic calcifications were identified using susceptibility maps and magnitude images, respectively, as well as more than half of periprostatic phleboliths depicted by CT. Calcifications in the prostate and its periphery were quantitatively differentiable from noncalcified prostate tissue in CT (mean values for calcifications / for noncalcified tissue: 71 to 649 / -1 to 83 HU) and in QSM (mean values for calcifications / for noncalcified tissue: -0.641 to 0.063 / -0.046 to 0.181 ppm). Moreover, there was a significant correlation between susceptibility values and CT image intensities for calcifications (P < 0.004).

CONCLUSION

Prostatic calcifications could be well identified with QSM. Susceptibility maps can be easily obtained from clinical prostate MR protocols that include a 3D gradient echo sequence, rendering it a promising technique for detection and quantification of intraprostatic calcifications.

LEVEL OF EVIDENCE

1 J. Magn. Reson. Imaging 2017;45:889-898.

MR Angiography at 7T to Visualize Cerebrovascular Territories

BACKGROUND

There is considerable amount of interindividual variability in the size and location of the vascular territories of the major brain arteries. More data are needed to assess the amount of variability and the possible implications for further research and patient care. Arterial spin labeling (ASL) magnetic resonance imaging has been applied in various forms to facilitate noninvasive imaging of cerebrovascular flow territories, but it requires the definition of the flow territory of interest prior to image acquisition.

OBJECTIVE

Assessing the vascular territories of the major brain territories by using ultra-high-field time-of-flight (TOF) magnetic resonance angiography.

METHODS

We have developed an alternative method to ASL by simulating cerebrovascular dye injections. Following bias field normalization and segmentation of the vessels from 7 Tesla TOF imaging, a virtual model of the arterial vessel tree was generated and a simulation of dye dispersion into the brain tissue was performed.

RESULTS

The results provided by our method are consistent with the data obtained by autoptic dye injection studies in 23 human beings by van der Zwan in 1993.

CONCLUSION

Further technical improvements in imaging and segmentation techniques will improve the accuracy of the method and will facilitate the delineation of flow territories after image acquisition on even smaller subtrees of the cerebral vasculature.

Registration of a statistical model to intraoperative ultrasound for scaphoid screw fixation

PURPOSE

Volar percutaneous scaphoid fracture fixation is conventionally performed under fluoroscopy-based guidance, where surgeons need to mentally determine a trajectory for the insertion of the screw and its depth based on a series of 2D projection images. In addition to challenges associated with mapping 2D information to a 3D space, the process involves exposure to ionizing radiation. Three-dimensional ultrasound has been suggested as an alternative imaging tool for this procedure; however, it has not yet been integrated into clinical routine since ultrasound only provides a limited view of the scaphoid and its surrounding anatomy.

METHODS

We propose a registration of a statistical wrist shape + scale + pose model to a preoperative CT and intraoperative ultrasound to derive a patient-specific 3D model for guiding scaphoid fracture fixation. The registered model is then used to determine clinically important intervention parameters, including the screw length and the trajectory of screw insertion in the scaphoid bone.

RESULTS

Feasibility experiments are performed using 13 cadaver wrists. In 10 out of 13 cases, the trajectory of screw suggested by the registered model meets all clinically important intervention parameters. Overall, an average 94 % of maximum allowable screw length is obtained based on the measurements from gold standard CT. Also, we obtained an average 92 % successful volar accessibility, which indicates that the trajectory is not obstructed by the surrounding trapezium bone.

CONCLUSIONS

These promising results indicate that determining clinically important screw insertion parameters for scaphoid fracture fixation is feasible using 3D ultrasound imaging. This suggests the potential of this technology in replacing fluoroscopic guidance for this procedure in future applications.

A fluoroscopy-based planning and guidance software tool for minimally invasive hip refixation by cement injection

Purpose

In orthopaedics, minimally invasive injection of bone cement is an established technique. We present HipRFX, a software tool for planning and guiding a cement injection procedure for stabilizing a loosening hip prosthesis. HipRFX works by analysing a pre-operative CT and intraoperative C-arm fluoroscopic images.

Methods

HipRFX simulates the intraoperative fluoroscopic views that a surgeon would see on a display panel. Structures are rendered by modelling their X-ray attenuation. These are then compared to actual fluoroscopic images which allow cement volumes to be estimated. Five human cadaver legs were used to validate the software in conjunction with real percutaneous cement injection into artificially created periprothetic lesions.

Results

Based on intraoperatively obtained fluoroscopic images, our software was able to estimate the cement volume that reached the pre-operatively planned targets. The actual median target lesion volume was 3.58 ml (range 3.17–4.64 ml). The median error in computed cement filling, as a percentage of target volume, was 5.3 % (range 2.2–14.8 %). Cement filling was between 17.6 and 55.4 % (median 51.8 %).

Conclusions

As a proof of concept, HipRFX was capable of simulating intraoperative fluoroscopic C-arm images. Furthermore, it provided estimates of the fraction of injected cement deposited at its intended target location, as opposed to cement that leaked away. This level of knowledge is usually unavailable to the surgeon viewing a fluoroscopic image and may aid in evaluating the success of a percutaneous cement injection intervention.

Towards markerless navigation for percutaneous needle insertions

PURPOSE

Percutaneous needle insertions are increasingly used for diagnosis and treatment of abdominal lesions. The challenging part of computed tomography (CT)-guided punctures is the transfer of the insertion trajectory planned in the CT image to the patient. Conventionally, this often results in several needle repositionings and control CT scans. To address this issue, several navigation systems for percutaneous needle insertions have been presented; however, none of them has thus far become widely accepted in clinical routine. Their benefit for the patient could not exceed the additional higher costs and the increased complexity in terms of bulky tracking systems and specialized markers for registration and tracking.

METHODS

We present the first markerless and trackerless navigation concept for real-time patient localization and instrument guidance. It has specifically been designed to be integrated smoothly into the clinical workflow and does not require markers or an external tracking system. The main idea is the utilization of a range imaging device that allows for contactless and radiation-free acquisition of both range and color information used for patient localization and instrument guidance.

RESULTS

A first feasibility study in phantom and porcine models yielded a median targeting accuracy of 6.9 and 19.4 mm, respectively.

CONCLUSIONS

Although system performance remains to be improved for clinical use, expected advances in camera technology as well as consideration of respiratory motion and automation of the individual steps will make this approach an interesting alternative for guiding percutaneous needle insertions.

Bone enhancement in ultrasound using local spectrum variations for guiding percutaneous scaphoid fracture fixation procedures

PURPOSE

The scaphoid bone is the most frequently fractured bone in the wrist. When fracture fixation is indicated, a screw is inserted into the bone either in an open surgical procedure or percutaneously under fluoroscopic guidance. Due to the complex geometry of the wrist, fracture fixation is a challenging task. Fluoroscopic guidance exposes both the patient and the physician to ionizing radiation. Ultrasound-based guidance has been suggested as a real-time, radiation-free alternative. The main challenge of using ultrasound is the difficulty in interpreting the images due to the low contrast and noisy nature of the data.

METHODS

We propose a bone enhancement method that exploits local spectrum features of the ultrasound image. These features are utilized to design a set of quadrature band-pass filters and subsequently estimate the local phase symmetry, where high symmetry is expected at the bone locations. We incorporate the shadow information below the bone surfaces to further enhance the bone responses. The extracted bone surfaces are then used to register a statistical wrist model to ultrasound volumes, allowing the localization and interpretation of the scaphoid bone in the volumes.

RESULTS

Feasibility experiments were performed using phantom and in vivo data. For phantoms, we obtain a surface distance error 1.08 mm and an angular deviation from the main axis of the scaphoid bone smaller than 5°, which are better compared to previously presented approaches.

CONCLUSION

The results are promising for further development of a surgical guidance system to enable accurate anatomy localization for guiding percutaneous scaphoid fracture fixations.

Pancreatic Atrophy in Hepatocellular Carcinoma Patients Receiving Long-Term Treatment with Sorafenib

OBJECTIVE

To date, sorafenib is the only approved systemic therapy for advanced hepatocellular carcinoma (HCC). Pancreatic atrophy has recently been reported in 2 patients as a novel side effect after long-term sorafenib treatment.

METHODS

We retrospectively analyzed clinical and radiological data of patients with advanced HCC with long-term treatment of sorafenib (median 279 days, range 153-826 days). Pancreata were semi-manually segmented section by section to calculate the pancreas volumes before and under sorafenib treatment.

RESULTS

Sorafenib reduced pancreatic volume in 18/19 (95%) HCC patients with a mean pancreatic volume loss of 25% (p = 0.002). Pancreatic volume loss depended on the dose (r = 0.36) and exposure time of sorafenib (r = 0.35) and was detectable as early as after 3 months of sorafenib treatment and already after a cumulative sorafenib dose of <100 g. Median overall survival was 13.2 months (range 7.8-31.3 months) but did not correlate with sorafenib-induced pancreatic volume reduction (hazard ratio 1.002, 95% confidence interval 0.981-1.060, p = 0.24).

CONCLUSION

We could confirm pancreatic atrophy as a novel adverse event of sorafenib therapy in HCC patients, correlating with sorafenib dose and exposure time.

The NifTK software platform for image-guided interventions: platform overview and NiftyLink messaging

PURPOSE

To perform research in image-guided interventions, researchers need a wide variety of software components, and assembling these components into a flexible and reliable system can be a challenging task. In this paper, the NifTK software platform is presented. A key focus has been high-performance streaming of stereo laparoscopic video data, ultrasound data and tracking data simultaneously.

METHODS

A new messaging library called NiftyLink is introduced that uses the OpenIGTLink protocol and provides the user with easy-to-use asynchronous two-way messaging, high reliability and comprehensive error reporting. A small suite of applications called NiftyGuide has been developed, containing lightweight applications for grabbing data, currently from position trackers and ultrasound scanners. These applications use NiftyLink to stream data into NiftyIGI, which is a workstation-based application, built on top of MITK, for visualisation and user interaction. Design decisions, performance characteristics and initial applications are described in detail. NiftyLink was tested for latency when transmitting images, tracking data, and interleaved imaging and tracking data.

RESULTS

NiftyLink can transmit tracking data at 1,024 frames per second (fps) with latency of 0.31 milliseconds, and 512 KB images with latency of 6.06 milliseconds at 32 fps. NiftyIGI was tested, receiving stereo high-definition laparoscopic video at 30 fps, tracking data from 4 rigid bodies at 20-30 fps and ultrasound data at 20 fps with rendering refresh rates between 2 and 20 Hz with no loss of user interaction.

CONCLUSION

These packages form part of the NifTK platform and have proven to be successful in a variety of image-guided surgery projects. Code and documentation for the NifTK platform are available from http://www.niftk.org . NiftyLink is provided open-source under a BSD license and available from http://github.com/NifTK/NiftyLink . The code for this paper is tagged IJCARS-2014.

Percutaneous bone cement refixation of aseptically loose hip prostheses: the effect of interface tissue removal on injected cement volumes

OBJECTIVE

To quantify whether injected cement volumes differed between two groups of patients who underwent experimental minimally invasive percutaneous cement injection procedures to stabilize aseptically loose hip prostheses. One patient group was preoperatively treated using gene-directed enzyme prodrug therapy to remove fibrous interface tissue, while the other group received no preoperative treatment. It was hypothesized that cement penetration may have been inhibited by the presence of fibrous interface tissue in periprosthetic lesions.

MATERIALS AND METHODS

We analyzed 17 patients (14 female, 3 male, ages 72-91, ASA categories 2-4) who were treated at our institution. Osteolytic lesions and injected cement were manually delineated using 3D CT image segmentation, and the deposition of injected cement was quantified.

RESULTS

Patients who underwent preoperative gene-directed enzyme therapy to remove fibrous tissue exhibited larger injected cement volumes than those who did not. The observed median increase in injected cement volume was 6.8 ml. Higher cement leakage volumes were also observed for this group.

CONCLUSION

We conclude that prior removal of periprosthetic fibrous interface tissue may enable better cement flow and penetration. This might lead to better refixation of aseptically loosened prostheses.

Towards a fast and efficient approach for modelling the patient-specific ventricular haemodynamics

Computer modelling of the heart has emerged over the past decade as a powerful technique to explore the cardiovascular pathophysiology and inform clinical diagnosis. The current state-of-the-art in biophysical modelling requires a wealth of, potentially invasive, clinical data for the parametrisation and validation of the models, a process that is still too long and complex to be compatible with the clinical decision-making time. Therefore, there remains a need for models that can be quickly customised to reconstruct physical processes difficult to measure directly in patients. In this paper, we propose a less resource-intensive approach to modelling, whereby computational fluid-dynamics (CFD) models are constrained exclusively by boundary motion derived from imaging data through a validated wall tracking algorithm. These models are generated and parametrised based solely on ultrasound data, whose acquisition is fast, inexpensive and routine in all patients. To maximise the time and computational efficiency, a semi-automated pipeline is embedded in an image processing workflow to personalise the models. Applying this approach to two patient cases, we demonstrate this tool can be directly used in the clinic to interpret and complement the available clinical data by providing a quantitative indication of clinical markers that cannot be easily derived from imaging, such as pressure gradients and the flow energy.

Planning of hepatectomy for tumor resection: resection surface construction and optimization

An interactive liver surgery planning system has been developed to construct and optimize the resection plan. With this system, the segmentation results of the liver and its components (such as tumors and vessels) are comprehensively visualized for surgeons to have an intuitive understanding of the internal anatomical structure of the liver. This system will also allow surgeons to interactively create and modify a resection plan on the virtual liver model. The resection surface, whose boundary is a closed curve, will be automatically constructed with the safe resection margins of tumors. Different from other systems, our developed system is able to generate the safety margins to all tumors. During surgery, a larger resection surface may cause potentially more bleeding and other complications. Therefore, area minimization is applied during the resection surface construction by adopting the minimal area mesh, which is a smooth surface with minimal area. After these virtual modifications, the resultant resection surface indicates the route to cut the liver for tumor removal. The volumes for both resected liver and residual liver are calculated for clinical decision making.

Regular three-dimensional presentations improve in the identification of surgical liver anatomy - a randomized study

BACKGROUND

Three-dimensional (3D) presentations enhance the understanding of complex anatomical structures. However, it has been shown that two dimensional (2D) "key views" of anatomical structures may suffice in order to improve spatial understanding. The impact of real 3D images (3Dr) visible only with 3D glasses has not been examined yet. Contrary to 3Dr, regular 3D images apply techniques such as shadows and different grades of transparency to create the impression of 3D.This randomized study aimed to define the impact of both the addition of key views to CT images (2D+) and the use of 3Dr on the identification of liver anatomy in comparison with regular 3D presentations (3D).

METHODS

A computer-based teaching module (TM) was used. Medical students were randomized to three groups (2D+ or 3Dr or 3D) and asked to answer 11 anatomical questions and 4 evaluative questions. Both 3D groups had animated models of the human liver available to them which could be moved in all directions.

RESULTS

156 medical students (57.7% female) participated in this randomized trial. Students exposed to 3Dr and 3D performed significantly better than those exposed to 2D+ (p < 0.01, ANOVA). There were no significant differences between 3D and 3Dr and no significant gender differences (p > 0.1, t-test). Students randomized to 3D and 3Dr not only had significantly better results, but they also were significantly faster in answering the 11 anatomical questions when compared to students randomized to 2D+ (p < 0.03, ANOVA). Whether or not "key views" were used had no significant impact on the number of correct answers (p > 0.3, t-test).

CONCLUSION

This randomized trial confirms that regular 3D visualization improve the identification of liver anatomy.

Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: initial investigation of a combined model- and image-driven approach

PURPOSE

Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (<10 mm diameter) during surgery presents a major challenge that is likely to increase as more early-stage disease is detected incidentally and in low-dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT-fluoroscopy), the authors propose the use of intraoperative cone-beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video-assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy.

METHODS

The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model-driven stage followed by a finer image-driven stage. The model-driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image-driven stage. The image-driven stage employs an intensity-corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT-guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross-correlation. Variations of the algorithm were investigated to study the behavior of the model- and image-driven stages by modifying individual algorithmic steps and examining the effect in comparison to the nominal process.

RESULTS

The combined model- and image-driven registration process demonstrated accuracy consistent with the requirements of minimally invasive VATS in both target localization (∼3-5 mm within the target wedge) and critical structure avoidance (∼1-2 mm). The model-driven stage initialized the registration to within a median TRE of 1.9 mm (95% confidence interval (CI) maximum = 5.0 mm), while the subsequent image-driven stage yielded higher accuracy localization with 0.6 mm median TRE (95% CI maximum = 4.1 mm). The variations assessing the individual algorithmic steps elucidated the role of each step and in some cases identified opportunities for further simplification and improvement in computational speed.

CONCLUSIONS

The initial studies show the proposed registration method to successfully register CBCT images of the inflated and deflated lung. Accuracy appears sufficient to localize the target and adjacent critical anatomy within ∼1-2 mm and guide localization under conditions in which the target cannot be discerned directly in CBCT (e.g., subtle, nonsolid tumors). The ability to directly localize tumors in the operating room could provide a valuable addition to the VATS arsenal, obviate the cost, logistics, and morbidity of preoperative tagging, and improve patient safety. Future work includes in vivo testing, optimization of workflow, and integration with a CBCT image guidance system.

A novel tool for segmenting 3D medical images based on generalized cylinders and active surfaces

Three-dimensional (3D) medical imaging has been incorporated in routine clinical practice, since the required infrastructure has become increasingly affordable. New algorithms and applications are needed to serve the additional image processing and analysis functions in 3D space. In this work we propose a system for semi-automatic modeling and segmentation of elongated salient and anatomical objects in 3D medical images. The proposed methodology is based on a novel mathematical formalization of a well-known class of geometric primitives, namely generalized cylinders (GCs), which exhibits advantages over the existing parametric definition. Since the anatomical objects have to be modeled by their intersection with the transverse image planes, the proposed methodology includes also a new seeded region growing (SRG) segmentation algorithm for ellipse detection in 2D images, based on a priori shape knowledge. Finally, the resulting GC model is used to initialize an active surface (AS) segmentation method, in order to accurately delineate the required object. In this work we present the proposed algorithms in detail, along with the evaluation of the accuracy of the model-based segmentation by experts. Results show that elongated objects like the aorta and the trachea may be segmented with sensitivity between 90% and 95%. The proposed SRG-ellipse detector requires minimal user-initialization and its executions requires only few seconds for each image slice on an average laptop. The evolution of the AS requires less than one second per iteration for a typical CT image. Comparisons are provided with state of the art semi-automatic medical image processing software, which validate the merit of the proposed work.