George C. Kagadis

Automatic vessel lumen segmentation and stent strut detection in intravascular optical coherence tomography

PURPOSE Optical coherence tomography (OCT) is a catheter-based imaging method that employs near-infrared light to produce high-resolution cross-sectional intravascular images. The authors propose a segmentation technique for automatic lumen area extraction and stent strut detection in intravascular OCT images for the purpose of quantitative analysis of neointimal hyperplasia (NIH). METHODS A clinical dataset of frequency-domain OCT scans of the human femoral artery was analyzed. First, a segmentation method based on the Markov random field (MRF) model was employed for lumen area identification. Second, textural and edge information derived from local intensity distribution and continuous wavelet transform (CWT) analysis were integrated to extract the inner luminal contour. Finally, the stent strut positions were detected via the introduction of each strut wavelet response across scales into a feature extraction and classification scheme in order to optimize the strut position detection. RESULTS The inner lumen contour and the position of stent strut were extracted with very high accuracy. Compared with manual segmentation by an expert vascular physician the automatic segmentation had an average overlap value of 0.937 ± 0.045 for all OCT images included in the study. The strut detection accuracy had an area under the curve (AUC) value of 0.95, together with sensitivity and specificity average values of 0.91 and 0.96, respectively. CONCLUSIONS A robust automatic segmentation technique integrating textural and edge information for vessel lumen border extraction and strut detection in intravascular OCT images was designed and presented. The proposed algorithm may be employed for automated quantitative morphological analysis of in-stent neointimal hyperplasia.

Cloud computing in medical imaging

Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.

Current status and future perspectives of in vivo small animal imaging using radiolabeled nanoparticles.

Small animal molecular imaging is a rapidly expanding efficient tool to study biological processes non-invasively. The use of radiolabeled tracers provides non-destructive, imaging information, allowing time related phenomena to be repeatedly studied in a single animal. In the last decade there has been an enormous progress in related technologies and a number of dedicated imaging systems overcome the limitations that the size of small animal possesses. On the other hand, nanoparticles (NPs) gain increased interest, due to their unique properties, which make them perfect candidates for biological applications. Over the past 5 years the two fields seem to cross more and more often; radiolabeled NPs have been assessed in numerous pre-clinical studies that range from oncology, till HIV treatment. In this article the current status in the tools, applications and trends of radiolabeled NPs reviewed.

A dose point kernel database using GATE Monte Carlo simulation toolkit for nuclear medicine applications: Comparison with other Monte Carlo codes

PURPOSE GATE is a Monte Carlo simulation toolkit based on the Geant4 package, widely used for many medical physics applications, including SPECT and PET image simulation and more recently CT image simulation and patient dosimetry. The purpose of the current study was to calculate dose point kernels (DPKs) using GATE, compare them against reference data, and finally produce a complete dataset of the total DPKs for the most commonly used radionuclides in nuclear medicine. METHODS Patient-specific absorbed dose calculations can be carried out using Monte Carlo simulations. The latest version of GATE extends its applications to Radiotherapy and Dosimetry. Comparison of the proposed method for the generation of DPKs was performed for (a) monoenergetic electron sources, with energies ranging from 10 keV to 10 MeV, (b) beta emitting isotopes, e.g., (177)Lu, (90)Y, and (32)P, and (c) gamma emitting isotopes, e.g., (111)In, (131)I, (125)I, and (99m)Tc. Point isotropic sources were simulated at the center of a sphere phantom, and the absorbed dose was stored in concentric spherical shells around the source. Evaluation was performed with already published studies for different Monte Carlo codes namely MCNP, EGS, FLUKA, ETRAN, GEPTS, and PENELOPE. A complete dataset of total DPKs was generated for water (equivalent to soft tissue), bone, and lung. This dataset takes into account all the major components of radiation interactions for the selected isotopes, including the absorbed dose from emitted electrons, photons, and all secondary particles generated from the electromagnetic interactions. RESULTS GATE comparison provided reliable results in all cases (monoenergetic electrons, beta emitting isotopes, and photon emitting isotopes). The observed differences between GATE and other codes are less than 10% and comparable to the discrepancies observed among other packages. The produced DPKs are in very good agreement with the already published data, which allowed us to produce a unique DPKs dataset using GATE. The dataset contains the total DPKs for (67)Ga, (68)Ga, (90)Y, (99m)Tc, (111)In, (123)I, (124)I, (125)I, (131)I, (153)Sm, (177)Lu (186)Re, and (188)Re generated in water, bone, and lung. CONCLUSIONS In this study, the authors have checked GATEs reliability for absorbed dose calculation when transporting different kind of particles, which indicates its robustness for dosimetry applications. A novel dataset of DPKs is provided, which can be applied in patient-specific dosimetry using analytical point kernel convolution algorithms.

99mTc-labeled aminosilane-coated iron oxide nanoparticles for molecular imaging of ανβ3-mediated tumor expression and feasibility for hyperthermia treatment

HYPOTHESIS Dual-modality imaging agents, such as radiolabeled iron oxide nanoparticles (IO-NPs), are promising candidates for cancer diagnosis and therapy. We developed and evaluated aminosilane coated Fe3O4 (10±2nm) as a tumor imaging agent in nuclear medicine through 3-aminopropyltriethoxysilane (APTES) functionalization. We evaluated this multimeric system of targeted (99m)Tc-labeled nanoparticles (NPs) conjugated with a new RGD derivate (cRGDfK-Orn3-CGG), characterized as NPs-RGD as a potential thermal therapy delivery vehicle. EXPERIMENTS Transmission Electron Microscopy (TEM) and spectroscopy techniques were used to characterize the IO-NPs indicating their functionalization with peptides. Radiolabeled IO-NPs (targeted, non-targeted) were evaluated with regard to their radiochemical, radiobiological and imaging characteristics. In vivo studies were performed in normal and ανβ3-positive tumor (U87MG glioblastoma) bearing mice. We also demonstrated that this system could reach ablative temperatures in vivo. FINDINGS Both radiolabeled IO-NPs were obtained in high radiochemical yield (>98%) and proved stable in vitro. The in vivo studies for both IO-NPs have shown significant liver and spleen uptake at all examined time points in normal and U87MG glioblastoma tumor-bearing mice, due to their colloidal nature. We have confirmed through in vivo biodistribution studies that the non-targeted (99m)Tc-NPs poorly internalized in the tumor, while the targeted (99m)Tc-NPs-RGD, present 9-fold higher tumor accumulation at 1h p.i. Accumulation of both IO-NPs in other organs was negligible. Blocking experiments indicated target specificity for integrin receptors in U87MG glioblastoma cells. The preliminary in vivo study of applied alternating magnetic field showed that the induced hyperthermia is feasible due to the aid of IO-NPs.

Emerging technologies for image guidance and device navigation in interventional radiology.

Recent developments in image-guidance and device navigation, along with emerging robotic technologies, are rapidly transforming the landscape of interventional radiology (IR). Future state-of-the-art IR procedures may include real-time three-dimensional imaging that is capable of visualizing the target organ, interventional tools, and surrounding anatomy with high spatial and temporal resolution. Remote device actuation is becoming a reality with the introduction of novel magnetic-field enabled instruments and remote robotic steering systems. Robots offer several degrees of freedom and unprecedented accuracy, stability, and dexterity during device navigation, propulsion, and actuation. Optimization of tracking and navigation of interventional tools inside the human body will be critical in converting IR suites into the minimally invasive operating theaters of the future with increased safety and unsurpassed therapeutic efficacy. In the not too distant future, individual image guidance modalities and device tracking methods could merge into autonomous, multimodality, multiparametric platforms that offer real-time data of anatomy, morphology, function, and metabolism along with on-the-fly computational modeling and remote robotic actuation. The authors provide a concise overview of the latest developments in image guidance and device navigation, while critically envisioning what the future might hold for 2020 IR procedures.

Investigation of realistic PET simulations incorporating tumor patient's specificity using anthropomorphic models: Creation of an oncology database

PURPOSE The GATE Monte Carlo simulation toolkit is used for the implementation of realistic PET simulations incorporating tumor heterogeneous activity distributions. The reconstructed patient images include noise from the acquisition process, imaging systems performance restrictions and have limited spatial resolution. For those reasons, the measured intensity cannot be simply introduced in GATE simulations, to reproduce clinical data. Investigation of the heterogeneity distribution within tumors applying partial volume correction (PVC) algorithms was assessed. The purpose of the present study was to create a simulated oncology database based on clinical data with realistic intratumor uptake heterogeneity properties. METHODS PET/CT data of seven oncology patients were used in order to create a realistic tumor database investigating the heterogeneity activity distribution of the simulated tumors. The anthropomorphic models (NURBS based cardiac torso and Zubal phantoms) were adapted to the CT data of each patient, and the activity distribution was extracted from the respective PET data. The patient-specific models were simulated with the Monte Carlo Geant4 application for tomography emission (GATE) in three different levels for each case: (a) using homogeneous activity within the tumor, (b) using heterogeneous activity distribution in every voxel within the tumor as it was extracted from the PET image, and (c) using heterogeneous activity distribution corresponding to the clinical image following PVC. The three different types of simulated data in each case were reconstructed with two iterations and filtered with a 3D Gaussian postfilter, in order to simulate the intratumor heterogeneous uptake. Heterogeneity in all generated images was quantified using textural feature derived parameters in 3D according to the ground truth of the simulation, and compared to clinical measurements. Finally, profiles were plotted in central slices of the tumors, across lines with heterogeneous activity distribution for visual assessment. RESULTS The accuracy of the simulated database was assessed against the original clinical images. The PVC simulated images matched the clinical ones best. Local, regional, and global features extracted from the PVC simulated images were closest to the clinical measurements, with the exception of the size zone variability and the mean intensity values, where heterogeneous tumors showed better reproducibility. The profiles on PVC simulated tumors after postfiltering seemed to represent the more realistic heterogeneous regions with respect to the clinical reference. CONCLUSIONS In this study, the authors investigated the input activity map heterogeneity in the GATE simulations of tumors with heterogeneous activity distribution. The most realistic heterogeneous tumors were obtained by inserting PVC activity distributions from the clinical image into the activity map of the simulation. Partial volume effect (PVE) can play a crucial role in the quantification of heterogeneity within tumors and have an important impact on applications such as patient follow-up during treatment and assessment of tumor response to therapy. The development of such a database incorporating patient anatomical and functional variability can be used to evaluate new image processing or analysis algorithms, while providing control of the ground truth, which is not available when dealing with clinical datasets. The database includes all images used and generated in this study, as well as the sinograms and the attenuation phantoms for further investigation. It is freely available to the interested reader of the journal at http://www.med.upatras.gr/oncobase/.

Automatic quantitative analysis of in-stent restenosis using FD-OCT in vivo intra-arterial imaging

PURPOSE A new segmentation technique is implemented for automatic lumen area extraction and stent strut detection in intravascular optical coherence tomography (OCT) images for the purpose of quantitative analysis of in-stent restenosis (ISR). In addition, a user-friendly graphical user interface (GUI) is developed based on the employed algorithm toward clinical use. METHODS Four clinical datasets of frequency-domain OCT scans of the human femoral artery were analyzed. First, a segmentation method based on fuzzy C means (FCM) clustering and wavelet transform (WT) was applied toward inner luminal contour extraction. Subsequently, stent strut positions were detected by utilizing metrics derived from the local maxima of the wavelet transform into the FCM membership function. RESULTS The inner lumen contour and the position of stent strut were extracted with high precision. Compared to manual segmentation by an expert physician, the automatic lumen contour delineation had an average overlap value of 0.917 ± 0.065 for all OCT images included in the study. The strut detection procedure achieved an overall accuracy of 93.80% and successfully identified 9.57 ± 0.5 struts for every OCT image. Processing time was confined to approximately 2.5 s per OCT frame. CONCLUSIONS A new fast and robust automatic segmentation technique combining FCM and WT for lumen border extraction and strut detection in intravascular OCT images was designed and implemented. The proposed algorithm integrated in a GUI represents a step forward toward the employment of automated quantitative analysis of ISR in clinical practice.PURPOSE A new segmentation technique is implemented for automatic lumen area extraction and stent strut detection in intravascular optical coherence tomography (OCT) images for the purpose of quantitative analysis of in-stent restenosis (ISR). In addition, a user-friendly graphical user interface (GUI) is developed based on the employed algorithm toward clinical use. METHODS Four clinical datasets of frequency-domain OCT scans of the human femoral artery were analyzed. First, a segmentation method based on fuzzy C means (FCM) clustering and wavelet transform (WT) was applied toward inner luminal contour extraction. Subsequently, stent strut positions were detected by utilizing metrics derived from the local maxima of the wavelet transform into the FCM membership function. RESULTS The inner lumen contour and the position of stent strut were extracted with high precision. Compared to manual segmentation by an expert physician, the automatic lumen contour delineation had an average overlap value of 0.917 ± 0.065 for all OCT images included in the study. The strut detection procedure achieved an overall accuracy of 93.80% and successfully identified 9.57 ± 0.5 struts for every OCT image. Processing time was confined to approximately 2.5 s per OCT frame. CONCLUSIONS A new fast and robust automatic segmentation technique combining FCM and WT for lumen border extraction and strut detection in intravascular OCT images was designed and implemented. The proposed algorithm integrated in a GUI represents a step forward toward the employment of automated quantitative analysis of ISR in clinical practice.

An introduction to molecular imaging in radiation oncology: A report by the AAPM Working Group on Molecular Imaging in Radiation Oncology (WGMIR)

Molecular imaging is the direct or indirect noninvasive monitoring and recording of the spatial and temporal distribution of in vivo molecular, genetic, and/or cellular processes for biochemical, biological, diagnostic, or therapeutic applications. Molecular images that indicate the presence of malignancy can be acquired using optical, ultrasonic, radiologic, radionuclide, and magnetic resonance techniques. For the radiation oncology physicist in particular, these methods and their roles in molecular imaging of oncologic processes are reviewed with respect to their physical bases and imaging characteristics, including signal intensity, spatial scale, and spatial resolution. Relevant molecular terminology is defined as an educational assist. Current and future clinical applications in oncologic diagnosis and treatment are discussed. National initiatives for the development of basic science and clinical molecular imaging techniques and expertise are reviewed, illustrating research opportunities in as well as the importance of this growing field.

Real-time tumor ablation simulation based on the dynamic mode decomposition method

PURPOSE The dynamic mode decomposition (DMD) method is used to provide a reliable forecasting of tumor ablation treatment simulation in real time, which is quite needed in medical practice. To achieve this, an extended Pennes bioheat model must be employed, taking into account both the water evaporation phenomenon and the tissue damage during tumor ablation. METHODS A meshless point collocation solver is used for the numerical solution of the governing equations. The results obtained are used by the DMD method for forecasting the numerical solution faster than the meshless solver. The procedure is first validated against analytical and numerical predictions for simple problems. The DMD method is then applied to three-dimensional simulations that involve modeling of tumor ablation and account for metabolic heat generation, blood perfusion, and heat ablation using realistic values for the various parameters. RESULTS The present method offers very fast numerical solution to bioheat transfer, which is of clinical significance in medical practice. It also sidesteps the mathematical treatment of boundaries between tumor and healthy tissue, which is usually a tedious procedure with some inevitable degree of approximation. The DMD method provides excellent predictions of the temperature profile in tumors and in the healthy parts of the tissue, for linear and nonlinear thermal properties of the tissue. CONCLUSIONS The low computational cost renders the use of DMD suitable for in situ real time tumor ablation simulations without sacrificing accuracy. In such a way, the tumor ablation treatment planning is feasible using just a personal computer thanks to the simplicity of the numerical procedure used. The geometrical data can be provided directly by medical image modalities used in everyday practice.