MR-guided focused ultrasound application for moving target tumor ablation in abdominal area: coil selection.

BACKGROUND: Magnetic Resonance Imaging (MRI)-guided Focused Ultrasound Surgery (MRgFUS) is a non-invasive thermal ablation method utilizing high-intensity focused ultrasound (HI-FU) energy for tissue ablation under MRI with real-time thermal mapping. Ablating to a dynamic target as in the liver is very challenging, requiring approval. A novel quality-assured liver tumor ablation system has been proposed for clinics. The paper reports the evaluation of conventional and new MR-receiving coils. PURPOSE: To evaluate the suitability of MR coils as part of the MRgFUS treatment system for liver, while simulating breathing motion in pre-clinical settings. MATERIAL AND METHODS: The novel software communicates with the MR scanner and the transducer. To monitor the temperature via proton resonance frequency (PRF) methodology echo planar imaging (EPI) sequence was used while the algorithms of static, static and dynamic tracking were tested with sonications of 100 W for 30 s on tissue-mimicking phantoms. Different coil sets were used to assess the performance of the system for fitness for dynamic thermometry. Finally, in vivo experiments were performed over a porcine model. RESULTS: Single-loop four-channel Duoflex and Gem coils provided adequate signal-to-noise ratio and contrast with consistent thermal readings. Body array coils showed severe loss of signal in dynamic cases since the integration of tracking algorithm causes low efficiency. CONCLUSION: Body array coils are unsuitable for MRgFUS of the liver due to signal loss. The dedicated coil set with a single loop around the FUS transducer combined with four-channel arrays might be the best option for liver treatment using dynamic MRgFUS applications.

Evidence-based cross validation for acoustic power transmission for a novel treatment system.

INTRODUCTION: The novel Trans-Fusimo Treatment System (TTS) is designed to control Magnetic Resonance guided Focused Ultrasound (MRgFUS) therapy to ablate liver tumours under respiratory motion. It is crucial to deliver the acoustic power within tolerance limits for effective liver tumour treatment via MRgFUS. Before application in a clinical setting, evidence of reproducibility and reliability is a must for safe practice. MATERIALS AND METHODS: The TTS software delivers the acoustic power via ExAblate-2100 Conformal Bone System (CBS) transducer. A built-in quality assurance application was developed to measure the force values, using a novel protocol to measure the efficiency for the electrical power values of 100 and 150W for 6s of sonication. This procedure was repeated 30 times by two independent users against the clinically approved ExAblate-2100 CBS for cross-validation. RESULTS: Both systems proved to deliver the power within the accepted efficiency levels (70-90%). Two sample t-tests were used to assess the differences in force values between the ExAblate-2100 CBS and the TTS (p > 0.05). Bland-Altman plots were used to demonstrate the limits of agreement between the two systems falling within the 10% limits of agreement. Two sample t-tests indicated that TTS does not have user dependency (p > 0.05). CONCLUSIONS: The TTS software proved to deliver the acoustic power without exceeding the safety levels. Results provide evidence as a part of ISO13485 regulations for CE marking purposes. The developed methodology could be utilised as a part of quality assurance system in clinical settings; when the TTS is used in clinical practice.

Workflow and intervention times of MR-guided focused ultrasound - Predicting the impact of new techniques.

Magnetic resonance guided focused ultrasound surgery (MRgFUS) has become an attractive, non-invasive treatment for benign and malignant tumours, and offers specific benefits for poorly accessible locations in the liver. However, the presence of the ribcage and the occurrence of liver motion due to respiration limit the applicability MRgFUS. Several techniques are being developed to address these issues or to decrease treatment times in other ways. However, the potential benefit of such improvements has not been quantified. In this research, the detailed workflow of current MRgFUS procedures was determined qualitatively and quantitatively by using observation studies on uterine MRgFUS interventions, and the bottlenecks in MRgFUS were identified. A validated simulation model based on discrete events simulation was developed to quantitatively predict the effect of new technological developments on the intervention duration of MRgFUS on the liver. During the observation studies, the duration and occurrence frequencies of all actions and decisions in the MRgFUS workflow were registered, as were the occurrence frequencies of motion detections and intervention halts. The observation results show that current MRgFUS uterine interventions take on average 213min. Organ motion was detected on average 2.9 times per intervention, of which on average 1.0 actually caused a need for rework. Nevertheless, these motion occurrences and the actions required to continue after their detection consumed on average 11% and up to 29% of the total intervention duration. The simulation results suggest that, depending on the motion occurrence frequency, the addition of new technology to automate currently manual MRgFUS tasks and motion compensation could potentially reduce the intervention durations by 98.4% (from 256h 5min to 4h 4min) in the case of 90% motion occurrence, and with 24% (from 5h 19min to 4h 2min) in the case of no motion. In conclusion, new tools were developed to predict how intervention durations will be affected by future workflow changes and by the introduction of new technology.

2D and 3D MALDI-imaging: conceptual strategies for visualization and data mining.

3D imaging has a significant impact on many challenges in life sciences, because biology is a 3-dimensional phenomenon. Current 3D imaging-technologies (various types MRI, PET, SPECT) are labeled, i.e. they trace the localization of a specific compound in the body. In contrast, 3D MALDI mass spectrometry-imaging (MALDI-MSI) is a label-free method imaging the spatial distribution of molecular compounds. It complements 3D imaging labeled methods, immunohistochemistry, and genetics-based methods. However, 3D MALDI-MSI cannot tap its full potential due to the lack of statistical methods for analysis and interpretation of large and complex 3D datasets. To overcome this, we established a complete and robust 3D MALDI-MSI pipeline combined with efficient computational data analysis methods for 3D edge preserving image denoising, 3D spatial segmentation as well as finding colocalized m/z values, which will be reviewed here in detail. Furthermore, we explain, why the integration and correlation of the MALDI imaging data with other imaging modalities allows to enhance the interpretation of the molecular data and provides visualization of molecular patterns that may otherwise not be apparent. Therefore, a 3D data acquisition workflow is described generating a set of 3 different dimensional images representing the same anatomies. First, an in-vitro MRI measurement is performed which results in a three-dimensional image modality representing the 3D structure of the measured object. After sectioning the 3D object into N consecutive slices, all N slices are scanned using an optical digital scanner, enabling for performing the MS measurements. Scanning the individual sections results into low-resolution images, which define the base coordinate system for the whole pipeline. The scanned images conclude the information from the spatial (MRI) and the mass spectrometric (MALDI-MSI) dimension and are used for the spatial three-dimensional reconstruction of the object performed by image registration techniques. Different strategies for automatic serial image registration applied to MS datasets are outlined in detail. The third image modality is histology driven, i.e. a digital scan of the histological stained slices in high-resolution. After fusion of reconstructed scan images and MRI the slice-related coordinates of the mass spectra can be propagated into 3D-space. After image registration of scan images and histological stained images, the anatomical information from histology is fused with the mass spectra from MALDI-MSI. As a result of the described pipeline we have a set of 3 dimensional images representing the same anatomies, i.e. the reconstructed slice scans, the spectral images as well as corresponding clustering results, and the acquired MRI. Great emphasis is put on the fact that the co-registered MRI providing anatomical details improves the interpretation of 3D MALDI images. The ability to relate mass spectrometry derived molecular information with in vivo and in vitro imaging has potentially important implications. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

An integrated model-based software for FUS in moving abdominal organs.

Focused ultrasound surgery (FUS) is a non-invasive method for tissue ablation that has the potential for complete and controlled local tumour destruction with minimal side effects. The treatment of abdominal organs such as the liver, however, requires particular technological support in order to enable a safe, efficient and effective treatment. As FUS is applied from outside the patient's body, suitable imaging methods, such as magnetic resonance imaging or diagnostic ultrasound, are needed to guide and track the procedure. To facilitate an efficient FUS procedure in the liver, the organ motion during breathing and the partial occlusion by the rib cage need to be taken into account in real time, demanding a continuous patient-specific adaptation of the treatment configuration. Modelling the patient's respiratory motion and combining this with tracking data improves the accuracy of motion predictions. Modelling and simulation of the FUS effects within the body allows the use of treatment planning and has the potential to be used within therapy to increase knowledge about the patient status. This article describes integrated model-based software for patient-specific modelling and prediction for FUS treatments of moving abdominal organs.

Exploring three-dimensional matrix-assisted laser desorption/ionization imaging mass spectrometry data: three-dimensional spatial segmentation of mouse kidney.

Three-dimensional (3D) imaging has a significant impact on many challenges of life sciences. Three-dimensional matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) is an emerging label-free bioanalytical technique capturing the spatial distribution of hundreds of molecular compounds in 3D by providing a MALDI mass spectrum for each spatial point of a 3D sample. Currently, 3D MALDI-IMS cannot tap its full potential due to the lack efficient computational methods for constructing, processing, and visualizing large and complex 3D MALDI-IMS data. We present a new pipeline of efficient computational methods, which enables analysis and interpretation of a 3D MALDI-IMS data set. Construction of a MALDI-IMS data set was done according to the state-of-the-art protocols and involved sample preparation, spectra acquisition, spectra preprocessing, and registration of serial sections. For analysis and interpretation of 3D MALDI-IMS data, we applied the spatial segmentation approach which is well-accepted in analysis of two-dimensional (2D) MALDI-IMS data. In line with 2D data analysis, we used edge-preserving 3D image denoising prior to segmentation to reduce strong and chaotic spectrum-to-spectrum variation. For segmentation, we used an efficient clustering method, called bisecting k-means, which is optimized for hierarchical clustering of a large 3D MALDI-IMS data set. Using the proposed pipeline, we analyzed a central part of a mouse kidney using 33 serial sections of 3.5 µm thickness after the PAXgene tissue fixation and paraffin embedding. For each serial section, a 2D MALDI-IMS data set was acquired following the standard protocols with the high spatial resolution of 50 µm. Altogether, 512 495 mass spectra were acquired that corresponds to approximately 50 gigabytes of data. After registration of serial sections into a 3D data set, our computational pipeline allowed us to reveal the 3D kidney anatomical structure based on mass spectrometry data only. Finally, automated analysis discovered molecular masses colocalized with major anatomical regions. In the same way, the proposed pipeline can be used for analysis and interpretation of any 3D MALDI-IMS data set in particular of pathological cases.

Landmark-based evaluation of a deformable motion correction for DCE-MRI of the liver.

PURPOSE: Annotation of meaningful landmark ground truth on DCE-MRI is difficult and laborious. Motion correction methods applied to DCE-MRI of the liver are thus mostly evaluated using qualitative or indirect measures. We propose a novel landmark annotation scheme that facilitates the generation of landmark ground truth on larger clinical datasets. METHODS: In our annotation scheme, landmarks are equally distributed over all time points of all available dataset cases and annotated by multiple observers on a per-pair basis. The scheme is used to annotate 26 DCE-MRI of the liver. A subset of the ground truth is used to optimize parameters of a deformable motion correction. Several variants of the motion correction are evaluated on the remaining cases with respect to distances of corresponding landmarks after registration, deformation field properties, and qualitative measures. RESULTS: A landmark ground truth on 26 cases could be generated in under 12 h per observer with a mean inter-observer distance below the mean voxel diagonal. Furthermore, the landmarks are spatially well distributed within the liver. Parameter optimization significantly improves the performance of the motion correction, and landmark distance after registration is 2 mm. Qualitative evaluation of the motion correction reflects the quantitative results. CONCLUSIONS: The annotation scheme makes a landmark-based evaluation of motion corrections for hepatic DCE-MRI practically feasible for larger clinical datasets. The comparably large number of cases enables both optimization and evaluation of motion correction methods.

Methodology on quantification of sonication duration for safe application of MR guided focused ultrasound for liver tumour ablation.

BACKGROUND AND OBJECTIVE: Magnetic Resonance Guided Focused Ultrasound (MRgFUS) for liver tumour ablation is a challenging task due to motion caused by breathing and occlusion due the ribcage between the transducer and the tumour. To overcome these challenges, a novel system for liver tumour ablation during free breathing has been designed. METHODS: The novel TRANS-FUSIMO Treatment System (TTS, EUFP7) interacts with a Magnetic Resonance (MR) scanner and a focused ultrasound transducer to sonicate to a moving target in liver. To meet the requirements of ISO 13485; a quality management system for medical device design, the system needs to be tested for certain process parameters. The duration of sonication and, the delay after the sonication button is activated, are among the parameters that need to be quantified for efficient and safe ablation of tumour tissue. A novel methodology is developed to quantify these process parameters. A computerised scope is programmed in LabVIEW to collect data via hydrophone; where the coordinates of fiber-optic sensor assembly was fed into the TRANS-FUSIMO treatment software via Magnetic Resonance Imaging (MRI) to sonicate to the tip of the sensor, which is synchronised with the clock of the scope, embedded in a degassed water tank via sensor assembly holder. The sonications were executed for 50 W, 100 W, 150 W for 10 s to quantify the actual sonication duration and the delay after the emergency stop by two independent operators for thirty times. The deviation of the system from the predefined specs was calculated. Student's-T test was used to investigate the user dependency. RESULTS: The duration of sonication and the delay after the sonication were quantified successfully with the developed method. TTS can sonicate with a maximum deviation of 0.16 s (Std 0.32) from the planned duration and with a delay of 14 ms (Std 0.14) for the emergency stop. Student's T tests indicate that the results do not depend on operators (p > .05). CONCLUSION: The evidence obtained via this protocol is crucial for translation- of-research into the clinics for safe application of MRgFUS. The developed protocol could be used for system maintenance in compliance with quality systems in clinics for daily quality assurance routines.

A focused ultrasound treatment system for moving targets (part I): generic system design and in-silico first-stage evaluation.

BACKGROUND: Focused ultrasound (FUS) is entering clinical routine as a treatment option. Currently, no clinically available FUS treatment system features automated respiratory motion compensation. The required quality standards make developing such a system challenging. METHODS: A novel FUS treatment system with motion compensation is described, developed with the goal of clinical use. The system comprises a clinically available MR device and FUS transducer system. The controller is very generic and could use any suitable MR or FUS device. MR image sequences (echo planar imaging) are acquired for both motion observation and thermometry. Based on anatomical feature tracking, motion predictions are estimated to compensate for processing delays. FUS control parameters are computed repeatedly and sent to the hardware to steer the focus to the (estimated) target position. All involved calculations produce individually known errors, yet their impact on therapy outcome is unclear. This is solved by defining an intuitive quality measure that compares the achieved temperature to the static scenario, resulting in an overall efficiency with respect to temperature rise. To allow for extensive testing of the system over wide ranges of parameters and algorithmic choices, we replace the actual MR and FUS devices by a virtual system. It emulates the hardware and, using numerical simulations of FUS during motion, predicts the local temperature rise in the tissue resulting from the controls it receives. RESULTS: With a clinically available monitoring image rate of 6.67 Hz and 20 FUS control updates per second, normal respiratory motion is estimated to be compensable with an estimated efficiency of 80%. This reduces to about 70% for motion scaled by 1.5. Extensive testing (6347 simulated sonications) over wide ranges of parameters shows that the main source of error is the temporal motion prediction. A history-based motion prediction method performs better than a simple linear extrapolator. CONCLUSIONS: The estimated efficiency of the new treatment system is already suited for clinical applications. The simulation-based in-silico testing as a first-stage validation reduces the efforts of real-world testing. Due to the extensible modular design, the described approach might lead to faster translations from research to clinical practice.

Automatic lung segmentation method for MRI-based lung perfusion studies of patients with chronic obstructive pulmonary disease.

PURPOSE: A novel fully automatic lung segmentation method for magnetic resonance (MR) images of patients with chronic obstructive pulmonary disease (COPD) is presented. The main goal of this work was to ease the tedious and time-consuming task of manual lung segmentation, which is required for region-based volumetric analysis of four-dimensional MR perfusion studies which goes beyond the analysis of small regions of interest. METHODS: The first step in the automatic algorithm is the segmentation of the lungs in morphological MR images with higher spatial resolution than corresponding perfusion MR images. Subsequently, the segmentation mask of the lungs is transferred to the perfusion images via nonlinear registration. Finally, the masks for left and right lungs are subdivided into a user-defined number of partitions. Fourteen patients with two time points resulting in 28 perfusion data sets were available for the preliminary evaluation of the developed methods. RESULTS: Resulting lung segmentation masks are compared with reference segmentations from experienced chest radiologists, as well as with total lung capacity (TLC) acquired by full-body plethysmography. TLC results were available for thirteen patients. The relevance of the presented method is indicated by an evaluation, which shows high correlation between automatically generated lung masks with corresponding ground-truth estimates. CONCLUSION: The evaluation of the developed methods indicates good accuracy and shows that automatically generated lung masks differ from expert segmentations about as much as segmentations from different experts.

MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation.

MALDI imaging mass spectrometry (MALDI-imaging) has emerged as a spatially-resolved label-free bioanalytical technique for direct analysis of biological samples and was recently introduced for analysis of 3D tissue specimens. We present a new experimental and computational pipeline for molecular analysis of tissue specimens which integrates 3D MALDI-imaging, magnetic resonance imaging (MRI), and histological staining and microscopy, and evaluate the pipeline by applying it to analysis of a mouse kidney. To ensure sample integrity and reproducible sectioning, we utilized the PAXgene fixation and paraffin embedding and proved its compatibility with MRI. Altogether, 122 serial sections of the kidney were analyzed using MALDI-imaging, resulting in a 3D dataset of 200GB comprised of 2million spectra. We show that elastic image registration better compensates for local distortions of tissue sections. The computational analysis of 3D MALDI-imaging data was performed using our spatial segmentation pipeline which determines regions of distinct molecular composition and finds m/z-values co-localized with these regions. For facilitated interpretation of 3D distribution of ions, we evaluated isosurfaces providing simplified visualization. We present the data in a multimodal fashion combining 3D MALDI-imaging with the MRI volume rendering and with light microscopic images of histologically stained sections. BIOLOGICAL SIGNIFICANCE: Our novel experimental and computational pipeline for 3D MALDI-imaging can be applied to address clinical questions such as proteomic analysis of the tumor morphologic heterogeneity. Examining the protein distribution as well as the drug distribution throughout an entire tumor using our pipeline will facilitate understanding of the molecular mechanisms of carcinogenesis.