A Within-Subject Multimodal NIRS-EEG Classifier for Infant Data.

Functional Near Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are commonly employed neuroimaging methods in developmental neuroscience. Since they offer complementary strengths and their simultaneous recording is relatively easy, combining them is highly desirable. However, to date, very few infant studies have been conducted with NIRS-EEG, partly because analyzing and interpreting multimodal data is challenging. In this work, we propose a framework to carry out a multivariate pattern analysis that uses an NIRS-EEG feature matrix, obtained by selecting EEG trials presented within larger NIRS blocks, and combining the corresponding features. Importantly, this classifier is intended to be sensitive enough to apply to individual-level, and not group-level data. We tested the classifier on NIRS-EEG data acquired from five newborn infants who were listening to human speech and monkey vocalizations. We evaluated how accurately the model classified stimuli when applied to EEG data alone, NIRS data alone, or combined NIRS-EEG data. For three out of five infants, the classifier achieved high and statistically significant accuracy when using features from the NIRS data alone, but even higher accuracy when using combined EEG and NIRS data, particularly from both hemoglobin components. For the other two infants, accuracies were lower overall, but for one of them the highest accuracy was still achieved when using combined EEG and NIRS data with both hemoglobin components. We discuss how classification based on joint NIRS-EEG data could be modified to fit the needs of different experimental paradigms and needs.

Intracoronary Imaging: Current Practice and Future Perspectives.

Intracoronary imaging has brought new insight in the field of interventional cardiology. Intravascular ultrasound (IVUS) and optical coherence tomography (OCT) are the most commonly used imaging modalities. Regarding their technical characteristics IVUS and OCT have similarities as well as differences, a fact that could have significant clinical implications. Both techniques play an important role in percutaneous coronary intervention (PCI) guidance and demonstrated superiority compared to intravascular coronary angiography (ICA) guidance alone. Furthermore, their use can notably assist coronary plaque evaluation; both provide additional information of plaque characteristics, which can lead to a better understanding of the cause of an acute coronary syndrome (ACS) and better clinical outcomes. However, there is not enough clinical evidence for the superiority of one method compared to the other, something that is, also, reflected in the guidelines. In this review, we aim to compare role of IVUS and OCT in the different aspects of coronary artery disease (CAD), according to the latest scientific data. In addition, we present the future perspectives regarding the IVUS and OCT, with co-registration of the two methods or hybrid OCT-IVUS catheters.

A two-stage cardiac PET and late gadolinium enhancement MRI co-registration method for improved assessment of non-ischemic cardiomyopathies using integrated PET/MR.

PURPOSE: Respiratory motion causes mismatches between PET images of the myocardium and the corresponding cardiac MR images in cardiac integrated PET/MR. The mismatch may affect the attenuation correction and the diagnosis of non-ischemic cardiomyopathies. In this study, we present a two-stage cardiac PET and MR late gadolinium enhancement (LGE) co-registration method, which seeks to improve diagnostic accuracy of non-ischemic cardiomyopathies via better image co-registration using an integrated whole-body PET/MR system. METHODS: The proposed PET and LGE two-stage co-registration method was evaluated through comparison with one-stage direct co-registration and no-registration. One hundred and ninety-one slices of LGE and forty lesions were studied. Two trained nuclear medicine physicians independently assessed the displacement between LGE and PET to qualitatively evaluate the co-registration quality. The changes of the mean SUV in the normal myocardium and the LGE-enhanced lesions before and after image co-registration were measured to quantitatively evaluate the accuracy and value of image co-registration. RESULTS: The two-stage method had an improved image registration score (4.93 ± 0.89) compared with the no-registration method (3.49 ± 0.84, p value < 0.001) and the single-stage method (4.23 ± 0.81, p value < 0.001). Furthermore, the two-stage method led to increased SUV value in the myocardium (3.87 ± 2.56) compared with the no-registration method (3.14 ± 1.92, p value < 0.001) and the single-stage method (3.32 ± 2.16, p value < 0.001). The mean SUV in the LGE lesion significantly increased from 2.51 ± 2.09 to 2.85 ± 2.35 (p value < 0.001) after the two-stage co-registration. CONCLUSION: The proposed two-stage registration method significantly improved the co-registration between PET and LGE in integrated PET/MR imaging. The technique may improve diagnostic accuracy of non-ischemic cardiomyopathies via better image co-registration. REGISTERED NO: DF-2020-085,2020.04.30.

Patterns of relapse and long-term outcome in patients treated with a curative intent for advanced Hodgkin lymphoma.

BACKGROUND: Consolidation radiotherapy for advanced Hodgkin lymphoma (AHL) is controversial. Precise knowledge of the most likely relapse location is crucial for radiotherapy planning. We performed detailed patterns of relapse analyses and evaluated if initial bulky disease, initial 18F-fluoro-deoxy-glucose (FDG)-avidity and/or a residual mass on computed tomography (CT)-scan after chemotherapy are sites with a high risk of relapse. This information could provide guidance for optimal use of radiotherapy in AHL. MATERIAL AND METHODS: We included 133 patients treated with curatively intended chemotherapy for AHL. 23 patients received consolidation radiotherapy. For relapsed patients, imaging from diagnosis, response evaluation, relapse, and any radiotherapy planning, were retrieved and co-registered to determine the exact site(s) of relapse relative to initial site(s), residual mass(es) and to any irradiated volumes. Size and FDG-avidity of initial sites with later relapse, and residual CT-abnormalities after chemotherapy in these sites were registered. Survival analyses were done using the Kaplan-Meier method. RESULTS: Nine (6.8%) patients relapsed, eight in initially involved sites. One relapse was in an initially irradiated site (as well as other sites). Initial bulky disease, high initial FDG-uptake, and/or residual masses on CT-scan after chemotherapy did not predict sites with a high risk of relapse. Overall survival was 79.6% (95% CI, 72.7-86.5%) and 70.6% (95% CI, 62.4-78.8%) at 5 and 10 years, respectively. Time to progression analysis showed 91.8% (95% CI, 86.9-96.7%) and 90.7% (95% CI, 85.4-96.0%) without progression at 5 and 10 years, respectively. CONCLUSION: Current treatment strategies for AHL provide excellent disease control. Neither initial bulk, high initial FDG-uptake, nor a residual CT-abnormality post-chemotherapy seem to indicate sites with a high risk of relapse.

UAV-Based Hyperspectral Monitoring Using Push-Broom and Snapshot Sensors: A Multisite Assessment for Precision Viticulture Applications.

Hyperspectral aerial imagery is becoming increasingly available due to both technology evolution and a somewhat affordable price tag. However, selecting a proper UAV + hyperspectral sensor combo to use in specific contexts is still challenging and lacks proper documental support. While selecting an UAV is more straightforward as it mostly relates with sensor compatibility, autonomy, reliability and cost, a hyperspectral sensor has much more to be considered. This note provides an assessment of two hyperspectral sensors (push-broom and snapshot) regarding practicality and suitability, within a precision viticulture context. The aim is to provide researchers, agronomists, winegrowers and UAV pilots with dependable data collection protocols and methods, enabling them to achieve faster processing techniques and helping to integrate multiple data sources. Furthermore, both the benefits and drawbacks of using each technology within a precision viticulture context are also highlighted. Hyperspectral sensors, UAVs, flight operations, and the processing methodology for each imaging type' datasets are presented through a qualitative and quantitative analysis. For this purpose, four vineyards in two countries were selected as case studies. This supports the extrapolation of both advantages and issues related with the two types of hyperspectral sensors used, in different contexts. Sensors' performance was compared through the evaluation of field operations complexity, processing time and qualitative accuracy of the results, namely the quality of the generated hyperspectral mosaics. The results shown an overall excellent geometrical quality, with no distortions or overlapping faults for both technologies, using the proposed mosaicking process and reconstruction. By resorting to the multi-site assessment, the qualitative and quantitative exchange of information throughout the UAV hyperspectral community is facilitated. In addition, all the major benefits and drawbacks of each hyperspectral sensor regarding its operation and data features are identified. Lastly, the operational complexity in the context of precision agriculture is also presented.

Calibration and Localization of Optically Pumped Magnetometers Using Electromagnetic Coils.

In this paper, we propose a method to estimate the position, orientation, and gain of a magnetic field sensor using a set of (large) electromagnetic coils. We apply the method for calibrating an array of optically pumped magnetometers (OPMs) for magnetoencephalography (MEG). We first measure the magnetic fields of the coils at multiple known positions using a well-calibrated triaxial magnetometer, and model these discreetly sampled fields using vector spherical harmonics (VSH) functions. We then localize and calibrate an OPM by minimizing the sum of squared errors between the model signals and the OPM responses to the coil fields. We show that by using homogeneous and first-order gradient fields, the OPM sensor parameters (gain, position, and orientation) can be obtained from a set of linear equations with pseudo-inverses of two matrices. The currents that should be applied to the coils for approximating these low-order field components can be determined based on the VSH models. Computationally simple initial estimates of the OPM sensor parameters follow. As a first test of the method, we placed a fluxgate magnetometer at multiple positions and estimated the RMS position, orientation, and gain errors of the method to be 1.0 mm, 0.2°, and 0.8%, respectively. Lastly, we calibrated a 48-channel OPM array. The accuracy of the OPM calibration was tested by using the OPM array to localize magnetic dipoles in a phantom, which resulted in an average dipole position error of 3.3 mm. The results demonstrate the feasibility of using electromagnetic coils to calibrate and localize OPMs for MEG.

Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection.

We present a workflow for seamless real-time navigation and 3D thermal mapping in combined indoor and outdoor environments in a global reference frame. The automated workflow and partly real-time capabilities are of special interest for inspection tasks and also for other time-critical applications. We use a hand-held integrated positioning system (IPS), which is a real-time capable visual-aided inertial navigation technology, and augment it with an additional passive thermal infrared camera and global referencing capabilities. The global reference is realized through surveyed optical markers (AprilTags). Due to the sensor data's fusion of the stereo camera and the thermal images, the resulting georeferenced 3D point cloud is enriched with thermal intensity values. A challenging calibration approach is used to geometrically calibrate and pixel-co-register the trifocal camera system. By fusing the terrestrial dataset with additional geographic information from an unmanned aerial vehicle, we gain a complete building hull point cloud and automatically reconstruct a semantic 3D model. A single-family house with surroundings in the village of Morschenich near the city of Jülich (German federal state North Rhine-Westphalia) was used as a test site to demonstrate our workflow. The presented work is a step towards automated building information modeling.

Synchronization of acquisition devices in neuroimaging: An application using co-registration of eye movements and electroencephalography.

Interest in applications for the simultaneous acquisition of data from different devices is growing. In neuroscience for example, co-registration complements and overcomes some of the shortcomings of individual methods. However, precise synchronization of the different data streams involved is required before joint data analysis. Our article presents and evaluates a synchronization method which maximizes the alignment of information across time. Synchronization through common triggers is widely used in all existing methods, because it is very simple and effective. However, this solution has been found to fail in certain practical situations, namely for the spurious detection of triggers and/or when the timestamps of triggers sampled by each acquisition device are not jointly distributed linearly for the entire duration of an experiment. We propose two additional mechanisms, the "Longest Common Subsequence" algorithm and a piecewise linear regression, in order to overcome the limitations of the classical method of synchronizing common triggers. The proposed synchronization method was evaluated using both real and artificial data. Co-registrations of electroencephalographic signals (EEG) and eye movements were used for real data. We compared the effectiveness of our method to another open source method implemented using EYE-EEG toolbox. Overall, we show that our method, implemented in C++ as a DOS application, is very fast, robust and fully automatic.

Natural oscillation frequencies in the two lateral prefrontal cortices induced by Transcranial Magnetic Stimulation.

Different cortical regions respond with distinct rhythmic patterns of neural oscillations to Transcranial Magnetic Stimulation (TMS). We investigated natural frequencies induced by TMS in left and right homologous dorsolateral prefrontal cortices (DLPFC) and related hemispheric differences. In 12 healthy young adults, single-pulse TMS was delivered in different blocks close to F3 and F4 channels to target left and right DLPFC. An occipital site near PO3 was stimulated as control. TMS-related spectral perturbation analyses were performed on recorded EEG data. A widespread unspecific increase in theta power was observed for all stimulation sites. However, occipital TMS induced greater alpha activity and a 10.58 Hz natural frequency, while TMS over the left and right DLPFC resulted in similar beta band modulations and a natural frequency of 18.77 and 18.5 Hz, respectively. In particular, TMS-related specific increase in beta activity was stronger for the right than the left DLPFC. The right DLPFC is more specifically tuned to its natural beta frequency when it is directly stimulated by TMS than with TMS over the left counterpart (or a posterior region), while the left DLPFC increases its beta activity more similarly irrespective of whether it is directly stimulated or through right homologous stimulation. These results yield important implications for both basic neuroscience research on inter-hemispheric prefrontal interactions and clinical applications.

Accuracy of electroanatomical mapping-guided cardiac radiotherapy for ventricular tachycardia: pitfalls and solutions.

AIMS: To analyse and optimize the interobserver agreement for gross target volume (GTV) delineation on cardiac computed tomography (CCT) based on electroanatomical mapping (EAM) data acquired to guide radiotherapy for ventricular tachycardia (VT). METHODS AND RESULTS: Electroanatomical mapping data were exported and merged with the segmented CCT using manual registration by two observers. A GTV was created by both observers for predefined left ventricular (LV) areas based on preselected endocardial EAM points indicating a two-dimensional (2D) surface area of interest. The influence of (interobserver) registration accuracy and availability of EAM data on the final GTV and 2D surface location within each LV area was evaluated. The median distance between the CCT and EAM after registration was 2.7 mm, 95th percentile 6.2 mm for observer #1 and 3.0 mm, 95th percentile 7.6 mm for observer #2 (P = 0.9). Created GTVs were significantly different (8 vs. 19 mL) with lowest GTV overlap (35%) for lateral wall target areas. Similarly, the highest shift between 2D surfaces was observed for the septal LV (6.4 mm). The optimal surface registration accuracy (2.6 mm) and interobserver agreement (Δ interobserver EAM surface registration 1.3 mm) was achieved if at least three cardiac chambers were mapped, including high-quality endocardial LV EAM. CONCLUSION: Detailed EAM of at least three chambers allows for accurate co-registration of EAM data with CCT and high interobserver agreement to guide radiotherapy of VT. However, the substrate location should be taken in consideration when creating a treatment volume margin.

CT and MRI Image Fusion Error: An Analysis of Co-Registration Error Using Commercially Available Deep Brain Stimulation Surgical Planning Software.

INTRODUCTION: During deep brain stimulation (DBS) surgery, computed tomography (CT) and magnetic resonance imaging (MRI) scans need to be co-registered or fused. Image fusion is associated with the error that can distort the location of anatomical structures. Co-registration in DBS surgery is usually performed automatically by proprietary software; the amount of error during this process is not well understood. Here, our goal is to quantify the error during automated image co-registration with FrameLink™, a commonly used software for DBS planning and clinical research. METHODS: This is a single-center retrospective study at a quaternary care referral center, comparing CT and MR imaging co-registration for a consecutive series of patients over a 12-month period. We collected CT images and MRI scans for 22 patients with Parkinson's disease requiring placement of DBS. Anatomical landmarks were located on CT images and MRI scans using a novel image analysis algorithm that included a method for capturing the potential error inherent in the image standardization step of the analysis. The distance between the anatomical landmarks was measured, and the error was found by averaging the distances across all patients. RESULTS: The average error during co-registration was 1.25 mm. This error was significantly larger than the error resulting from image standardization (0.19 mm) and was worse in the anterior-posterior direction. CONCLUSIONS: The image fusion errors found in this analysis were nontrivial. Although the estimated error may be inflated, it is sig-nificant enough that users must be aware of this potential inaccuracy, and developers of proprietary software should provide details about the magnitude and direction of co-registration errors.

On-scalp MEG sensor localization using magnetic dipole-like coils: A method for highly accurate co-registration.

Source modelling in magnetoencephalography (MEG) requires precise co-registration of the sensor array and the anatomical structure of the measured individual's head. In conventional MEG, the positions and orientations of the sensors relative to each other are fixed and known beforehand, requiring only localization of the head relative to the sensor array. Since the sensors in on-scalp MEG are positioned on the scalp, locations of the individual sensors depend on the subject's head shape and size. The positions and orientations of on-scalp sensors must therefore be measured at every recording. This can be achieved by inverting conventional head localization, localizing the sensors relative to the head - rather than the other way around. In this study we present a practical method for localizing sensors using magnetic dipole-like coils attached to the subject's head. We implement and evaluate the method in a set of on-scalp MEG recordings using a 7-channel on-scalp MEG system based on high critical temperature superconducting quantum interference devices (high-Tc SQUIDs). The method allows individually localizing the sensor positions, orientations, and responsivities with high accuracy using only a short averaging time (≤ 2 â€‹mm, < 3° and < 3%, respectively, with 1-s averaging), enabling continuous sensor localization. Calibrating and jointly localizing the sensor array can further improve the accuracy of position and orientation (< 1 â€‹mm and < 1°, respectively, with 1-s coil recordings). We demonstrate source localization of on-scalp recorded somatosensory evoked activity based on co-registration with our method. Equivalent current dipole fits of the evoked responses corresponded well (within 4.2 â€‹mm) with those based on a commercial, whole-head MEG system.

Stepwise manipulation of cardiac computed tomography multi-planar reconstruction to mimic transesophageal echocardiography.

Cardiac computed tomography (CT) is increasingly used to plan transcatheter structural heart interventions. However, intraoperative guidance relies on transesophageal echocardiography (TEE) and fluoroscopy. This study sought to develop a stepwise CT multi-planar reconstruction manipulation method to mimic TEE, bridging the gap between preoperative planning and intraoperative guidance tools. This CT manipulation reproduced similar configurations as TEE views in the mid-esophageal left ventricle (LV) views, transgastric LV 2-chamber views for mitral apparatus, and other miscellaneous views. Stepwise cardiac CT manipulation to mimic TEE is the final piece of the puzzle in the mental co-registration of these three crucial imaging modalities. Now, we can predict the TEE images and fluoroscopy projections in a preoperative rehearsal, thus improving the intraoperative accuracy of interventions.

Rigorous Co-Registration of KOMPSAT-3 Multispectral and Panchromatic Images for Pan-Sharpening Image Fusion.

KOMPSAT-3, a Korean earth observing satellite, provides the panchromatic (PAN) band and four multispectral (MS) bands. They can be fused to obtain a pan-sharpened image of higher resolution in both the spectral and spatial domain, which is more informative and interpretative for visual inspection. In KOMPSAT-3 Advanced Earth Imaging Sensor System (AEISS) uni-focal camera system, the precise sensor alignment is a prerequisite for the fusion of MS and PAN images because MS and PAN Charge-Coupled Device (CCD) sensors are installed with certain offsets. In addition, exterior effects associated with the ephemeris and terrain elevation lead to the geometric discrepancy between MS and PAN images. Therefore, we propose a rigorous co-registration of KOMPSAT-3 MS and PAN images based on physical sensor modeling. We evaluated the impacts of CCD line offsets, ephemeris, and terrain elevation on the difference in image coordinates. The analysis enables precise co-registration modeling between MS and PAN images. An experiment with KOMPSAT-3 images produced negligible geometric discrepancy between MS and PAN images.

The impact of improved MEG-MRI co-registration on MEG connectivity analysis.

Co-registration between structural head images and functional MEG data is needed for anatomically-informed MEG data analysis. Despite the efforts to minimize the co-registration error, conventional landmark- and surface-based strategies for co-registering head and MEG device coordinates achieve an accuracy of typically 5-10 mm. Recent advances in instrumentation and technical solutions, such as the development of hybrid ultra-low-field (ULF) MRI-MEG devices or the use of 3D-printed individualized foam head-casts, promise unprecedented co-registration accuracy, i.e., 2 mm or better. In the present study, we assess through simulations the impact of such an improved co-registration on MEG connectivity analysis. We generated synthetic MEG recordings for pairs of connected cortical sources with variable locations. We then assessed the capability to reconstruct source-level connectivity from these recordings for 0-15-mm co-registration error, three levels of head modeling detail (one-, three- and four-compartment models), two source estimation techniques (linearly constrained minimum-variance beamforming and minimum-norm estimation MNE) and five separate connectivity metrics (imaginary coherency, phase-locking value, amplitude-envelope correlation, phase-slope index and frequency-domain Granger causality). We found that beamforming can better take advantage of an accurate co-registration than MNE. Specifically, when the co-registration error was smaller than 3 mm, the relative error in connectivity estimates was down to one-third of that observed with typical co-registration errors. MNE provided stable results for a wide range of co-registration errors, while the performance of beamforming rapidly degraded as the co-registration error increased. Furthermore, we found that even moderate co-registration errors (>6 mm, on average) essentially decrease the difference of four- and three- or one-compartment models. Hence, a precise co-registration is important if one wants to take full advantage of highly accurate head models for connectivity analysis. We conclude that an improved co-registration will be beneficial for reliable connectivity analysis and effective use of highly accurate head models in future MEG connectivity studies.

Data-driven model optimization for optically pumped magnetometer sensor arrays.

Optically pumped magnetometers (OPMs) have reached sensitivity levels that make them viable portable alternatives to traditional superconducting technology for magnetoencephalography (MEG). OPMs do not require cryogenic cooling and can therefore be placed directly on the scalp surface. Unlike cryogenic systems, based on a well-characterised fixed arrays essentially linear in applied flux, OPM devices, based on different physical principles, present new modelling challenges. Here, we outline an empirical Bayesian framework that can be used to compare between and optimise sensor arrays. We perturb the sensor geometry (via simulation) and with analytic model comparison methods estimate the true sensor geometry. The width of these perturbation curves allows us to compare different MEG systems. We test this technique using simulated and real data from SQUID and OPM recordings using head-casts and scanner-casts. Finally, we show that given knowledge of underlying brain anatomy, it is possible to estimate the true sensor geometry from the OPM data themselves using a model comparison framework. This implies that the requirement for accurate knowledge of the sensor positions and orientations a priori may be relaxed. As this procedure uses the cortical manifold as spatial support there is no co-registration procedure or reliance on scalp landmarks.

Region-by-region analysis of PET, MRI, and histology in en bloc-resected oligodendrogliomas reveals intra-tumoral heterogeneity.

PURPOSE: Oligodendrogliomas are heterogeneous tumors in terms of imaging appearance, and a deeper understanding of the histopathological tumor characteristics in correlation to imaging parameters is needed. We used PET-to-MRI-to-histology co-registration with the aim of studying intra-tumoral 11C-methionine (MET) uptake in relation to tumor perfusion and the protein expression of histological cell markers in corresponding areas. METHODS: Consecutive histological sections of four tumors covering the entire en bloc-removed tumor were immunostained with antibodies against IDH1-mutated protein (tumor cells), Ki67 (proliferating cells), and CD34 (blood vessels). Software was developed for anatomical landmarks-based co-registration of subsequent histological images, which were overlaid on corresponding MET PET scans and MRI perfusion maps. Regions of interest (ROIs) on PET were selected throughout the entire tumor volume, covering hot spot areas, areas adjacent to hot spots, and tumor borders with infiltrating zone. Tumor-to-normal tissue (T/N) ratios of MET uptake and mean relative cerebral blood volume (rCBV) were measured in the ROIs and protein expression of histological cell markers was quantified in corresponding regions. Statistical correlations were calculated between MET uptake, rCBV, and quantified protein expression. RESULTS: A total of 84 ROIs were selected in four oligodendrogliomas. A significant correlation (p < 0.05) between MET uptake and tumor cell density was demonstrated in all tumors separately. In two tumors, MET correlated with the density of proliferating cells and vessel cell density. There were no significant correlations between MET uptake and rCBV, and between rCBV and histological cell markers. CONCLUSIONS: The MET uptake in hot spots, outside hotspots, and in infiltrating tumor edges unanimously reflects tumor cell density. The correlation between MET uptake and vessel density and density of proliferating cells is less stringent in infiltrating tumor edges and is probably more susceptible to artifacts caused by larger blood vessels surrounding the tumor. Although based on a limited number of samples, this study provides histological proof for MET as an indicator of tumor cell density and for the lack of statistically significant correlations between rCBV and histological cell markers in oligodendrogliomas.

Improved co-registration of ex-vivo and in-vivo cardiovascular magnetic resonance images using heart-specific flexible 3D printed acrylic scaffold combined with non-rigid registration.

BACKGROUND: Ex-vivo cardiovascular magnetic resonance (CMR) imaging has played an important role in the validation of in-vivo CMR characterization of pathological processes. However, comparison between in-vivo and ex-vivo imaging remains challenging due to shape changes occurring between the two states, which may be non-uniform across the diseased heart. A novel two-step process to facilitate registration between ex-vivo and in-vivo CMR was developed and evaluated in a porcine model of chronic myocardial infarction (MI). METHODS: Seven weeks after ischemia-reperfusion MI, 12 swine underwent in-vivo CMR imaging with late gadolinium enhancement followed by ex-vivo CMR 1 week later. Five animals comprised the control group, in which ex-vivo imaging was undertaken without any support in the LV cavity, 7 animals comprised the experimental group, in which a two-step registration optimization process was undertaken. The first step involved a heart specific flexible 3D printed scaffold generated from in-vivo CMR, which was used to maintain left ventricular (LV) shape during ex-vivo imaging. In the second step, a non-rigid co-registration algorithm was applied to align in-vivo and ex-vivo data. Tissue dimension changes between in-vivo and ex-vivo imaging were compared between the experimental and control group. In the experimental group, tissue compartment volumes and thickness were compared between in-vivo and ex-vivo data before and after non-rigid registration. The effectiveness of the alignment was assessed quantitatively using the DICE similarity coefficient. RESULTS: LV cavity volume changed more in the control group (ratio of cavity volume between ex-vivo and in-vivo imaging in control and experimental group 0.14 vs 0.56, p < 0.0001) and there was a significantly greater change in the short axis dimensions in the control group (ratio of short axis dimensions in control and experimental group 0.38 vs 0.79, p < 0.001). In the experimental group, prior to non-rigid co-registration the LV cavity contracted isotropically in the ex-vivo condition by less than 20% in each dimension. There was a significant proportional change in tissue thickness in the healthy myocardium (change = 29 ± 21%), but not in dense scar (change = - 2 ± 2%, p = 0.034). Following the non-rigid co-registration step of the process, the DICE similarity coefficients for the myocardium, LV cavity and scar were 0.93 (±0.02), 0.89 (±0.01) and 0.77 (±0.07) respectively and the myocardial tissue and LV cavity volumes had a ratio of 1.03 and 1.00 respectively. CONCLUSIONS: The pattern of the morphological changes seen between the in-vivo and the ex-vivo LV differs between scar and healthy myocardium. A 3D printed flexible scaffold based on the in-vivo shape of the LV cavity is an effective strategy to minimize morphological changes in the ex-vivo LV. The subsequent non-rigid registration step further improved the co-registration and local comparison between in-vivo and ex-vivo data.

Precise co-registration of mass spectrometry imaging, histology, and laser microdissection-based omics.

Mass spectrometry imaging (MSI) is an analytical technique for the unlabeled and multiplex imaging of molecules in biological tissue sections. It therefore enables the spatial and molecular annotations of tissues complementary to histology. It has already been shown that MSI can guide subsequent material isolation technologies such as laser microdissection (LMD) to enable a more in-depth molecular characterization of MSI-highlighted tissue regions. However, with MSI now reaching spatial resolutions at the single-cell scale, there is a need for a precise co-registration between MSI and the LMD. As proof-of-principle, MSI of lipids was performed on a breast cancer tissue followed by a segmentation of the data to detect molecularly distinct segments within its tumor areas. After image processing of the segmentation results, the coordinates of the MSI-detected segments were passed to the LMD system by three co-registration steps. The errors of each co-registration step were quantified and the total error was found to be less than 13 µm. With this link established, MSI data can now accurately guide LMD to excise MSI-defined regions of interest for subsequent extract-based analyses. In our example, the excised tissue material was then subjected to ultrasensitive microproteomics in order to determine predominant molecular mechanisms in each of the MSI-highlighted intratumor segments. This work shows how the strengths of MSI, histology, and extract-based omics can be combined to enable a more comprehensive molecular characterization of in situ biological processes.

Quantitative margin assessment of radiofrequency ablation of a solitary colorectal hepatic metastasis using MIRADA RTx on CT scans: a feasibility study.

BACKGROUND: Compared to surgery, radiofrequency ablation(RFA) for colorectal liver metastasis(CRLM) is associated with higher local recurrence(LR) rates. A wide margin (at least 5 mm) is generally recommended to prevent LR, but the optimal method to assess ablation margins is yet to be established. The aim of our study was to evaluate the feasibility and reproducibility of CT-CT co-registration, using MIRADA software, in order to assess ablation margins of patients with CRLM. METHODS: In this retrospective study, pre- and post-ablation contrast-enhanced CT scans of 29 patients, treated with percutaneous RFA for a solitary CRLM, were co-registered. Co-registration was performed by two independent radiologist, based on venous structures in proximity to the tumor. Feasibility of CT-CT co-registration and inter-observer agreement for reproducibility and ablation margins was determined. Furthermore, the minimal ablation margin was compared with the occurrence of LR during follow-up. RESULTS: Co-registration was considered feasible in 18 patients (61% male, 63.1(±10.9) year), with a perfect inter-observer agreement for completeness of ablation: κ = 1.0(p < 0.001). And substantial inter-observer agreement for measurement of the minimal margin (≤ 0 mm, 1-5 mm, ≥ 5 mm): κ = 0.723(p-value < 0.001). LR occurred in eight of nine(88.9%) incompletely ablated CRLM and in one of the nine completely ablated CRLM(11.1%). CONCLUSION: Co-registration using MIRADA is reproducible and potentially a valuable tool in defining technical success. Feasibility of co-registration of pre- and post-ablation CT scans is suboptimal if scans are not acquired concordantly. Co-registration may potentially aid in the prediction of LR after percutaneous ablation.