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Objective: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos., Methods: CT scans of former workers previously occupationally exposed to asbestos who participated in the multicenter APEXS (Asbestos PostExposure Survey) study were collected retrospectively between 2010 and 2017 during the second and the third rounds of the survey. A hundred and forty-one participants with pleural plaques identified by expert radiologists at the 2nd and the 3rd CT screenings were included. Maximum Intensity Projection (MIP) with 5 mm thickness was used to reduce the number of CT slices for manual delineation. A Deep Learning AI algorithm using 2D-convolutional neural networks was trained with 8280 images from 138 CT scans of 69 participants for the semantic labeling of Pleural Plaques (PP). In all, 2160 CT images from 36 CT scans of 18 participants were used for AI testing versus ground-truth labels (GT). The clinical validity of the method was evaluated longitudinally in 54 participants with pleural plaques., Results: The concordance correlation coefficient (CCC) between AI-driven and GT was almost perfect (>0.98) for the volume extent of both PP and calcified PP. The 2D pixel similarity overlap of AI versus GT was good (DICE = 0.63) for PP, whether they were calcified or not, and very good (DICE = 0.82) for calcified PP. A longitudinal comparison of the volumetric extent of PP showed a significant increase in PP volumes ( p < 0.001) between the 2nd and the 3rd CT screenings with an average delay of 5 years., Conclusions: AI allows a fully automated volumetric quantification of pleural plaques showing volumetric progression of PP over a five-year period. The reproducible PP volume evaluation may enable further investigations for the comprehension of the unclear relationships between pleural plaques and both respiratory function and occurrence of thoracic malignancy.

Despite recent progress in the characterization of tumour components, the tri-dimensional (3D) organization of this pathological tissue and the parameters determining its internal architecture remain elusive. Here, we analysed the spatial organization of patient-derived xenograft tissues generated from hepatoblastoma, the most frequent childhood liver tumour, by serial block-face scanning electron microscopy using an integrated workflow combining 3D imaging, manual and machine learning-based semi-automatic segmentations, mathematics and infographics. By digitally reconstituting an entire hepatoblastoma sample with a blood capillary, a bile canaliculus-like structure, hundreds of tumour cells and their main organelles (e.g. cytoplasm, nucleus, mitochondria), we report unique 3D ultrastructural data about the organization of tumour tissue. We found that the size of hepatoblastoma cells correlates with the size of their nucleus, cytoplasm and mitochondrial mass. We also found anatomical connections between the blood capillary and the planar alignment and size of tumour cells in their 3D milieu. Finally, a set of tumour cells polarized in the direction of a hot spot corresponding to a bile canaliculus-like structure. In conclusion, this pilot study allowed the identification of bioarchitectural parameters that shape the internal and spatial organization of tumours, thus paving the way for future investigations in the emerging onconanotomy field., (© 2021. The Author(s).)

Objectives: In multiple myeloma, the diagnosis of diffuse bone marrow infiltration on 18-FDG PET/CT can be challenging. We aimed to develop a PET/CT radiomics-based model that could improve the diagnosis of multiple myeloma diffuse disease on 18-FDG PET/CT., Methods: We prospectively performed PET/CT and whole-body diffusion-weighted MRI in 30 newly diagnosed multiple myeloma. MRI was the reference standard for diffuse disease assessment. Twenty patients were randomly assigned to a training set and 10 to an independent test set. Visual analysis of PET/CT was performed by two nuclear medicine physicians. Spine volumes were automatically segmented, and a total of 174 Imaging Biomarker Standardisation Initiative-compliant radiomics features were extracted from PET and CT. Selection of best features was performed with random forest features importance and correlation analysis. Machine-learning algorithms were trained on the selected features with cross-validation and evaluated on the independent test set., Results: Out of the 30 patients, 18 had established diffuse disease on MRI. The sensitivity, specificity and accuracy of visual analysis were 67, 75 and 70%, respectively, with a moderate kappa coefficient of agreement of 0.6. Five radiomics features were selected. On the training set, random forest classifier reached a sensitivity, specificity and accuracy of 93, 86 and 91%, respectively, with an area under the curve of 0.90 (95% confidence interval, 0.89-0.91). On the independent test set, the model achieved an accuracy of 80%., Conclusions: Radiomics analysis of 18-FDG PET/CT images with machine-learning overcame the limitations of visual analysis, providing a highly accurate and more reliable diagnosis of diffuse bone marrow infiltration in multiple myeloma patients., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Real-time MR-imaging has been clinically adapted for monitoring thermal therapies since it can provide on-the-fly temperature maps simultaneously with anatomical information. However, proton resonance frequency based thermometry of moving targets remains challenging since temperature artifacts are induced by the respiratory as well as physiological motion. If left uncorrected, these artifacts lead to severe errors in temperature estimates and impair therapy guidance. In this study, we evaluated deep learning for on-line correction of motion related errors in abdominal MR-thermometry. For this, a convolutional neural network (CNN) was designed to learn the apparent temperature perturbation from images acquired during a preparative learning stage prior to hyperthermia. The input of the designed CNN is the most recent magnitude image and no surrogate of motion is needed. During the subsequent hyperthermia procedure, the recent magnitude image is used as an input for the CNN-model in order to generate an on-line correction for the current temperature map. The method's artifact suppression performance was evaluated on 12 free breathing volunteers and was found robust and artifact-free in all examined cases. Furthermore, thermometric precision and accuracy was assessed for in vivo ablation using high intensity focused ultrasound. All calculations involved at the different stages of the proposed workflow were designed to be compatible with the clinical time constraints of a therapeutic procedure., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Various multi-modal imaging sensors are currently involved at different steps of an interventional therapeutic work-flow. Cone beam computed tomography (CBCT), computed tomography (CT) or Magnetic Resonance (MR) images thereby provides complementary functional and/or structural information of the targeted region and organs at risk. Merging this information relies on a correct spatial alignment of the observed anatomy between the acquired images. This can be achieved by the means of multi-modal deformable image registration (DIR), demonstrated to be capable of estimating dense and elastic deformations between images acquired by multiple imaging devices. However, due to the typically different field-of-view (FOV) sampled across the various imaging modalities, such algorithms may severely fail in finding a satisfactory solution. In the current study we propose a new fast method to align the FOV in multi-modal 3D medical images. To this end, a patch-based approach is introduced and combined with a state-of-the-art multi-modal image similarity metric in order to cope with multi-modal medical images. The occurrence of estimated patch shifts is computed for each spatial direction and the shift value with maximum occurrence is selected and used to adjust the image field-of-view. The performance of the proposed method - in terms of both registration accuracy and computational needs - is analyzed in the practical case of on-line irreversible electroporation procedures. In total, 30 pairs of pre-/per-operative IRE images are considered to illustrate the efficiency of our algorithm. We show that a regional registration approach using voxel patches provides a good structural compromise between the voxel-wise and "global shifts" approaches. The method was thereby beneficial for CT to CBCT and MRI to CBCT registration tasks, especially when highly different image FOVs are involved. Besides, the benefit of the method for CT to CBCT and MRI to CBCT image registration is analyzed, including the impact of artifacts generated by percutaneous needle insertions. Additionally, the computational needs using commodity hardware are demonstrated to be compatible with clinical constraints in the practical case of on-line procedures. The proposed patch-based workflow thus represents an attractive asset for DIR at different stages of an interventional procedure., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

4D-MRI is a promising tool for organ exploration, target delineation and treatment planning. Intra-scan motion artifacts may be greatly reduced by increasing the imaging frame rate. However, poor signal-to-noise ratios (SNR) are observed when increasing spatial and/or frame number per physiological cycle, in particular in the abdomen. In the current work, the proposed 4D-MRI method favored spatial resolution, frame number, isotropic voxels and large field-of-view (FOV) during MR-acquisition. The consequential SNR penalty in the reconstructed data is addressed retrospectively using an iterative back-projection (IBP) algorithm. Practically, after computing individual spatial 3D deformations present in the images using a deformable image registration (DIR) algorithm, each 3D image is individually enhanced by fusing several successive frames in its local temporal neighborood, these latter being likely to cover common independent informations. A tuning parameter allows one to freely readjust the balance between temporal resolution and precision of the 4D-MRI. The benefit of the method was quantitatively evaluated on the thorax of 6 mice under free breathing using a clinically acceptable duration. Improved 4D cardiac imaging was also shown in the heart of 1 mice. Obtained results are compared to theoretical expectations and discussed. The proposed implementation is easily parallelizable and optimized 4D-MRI could thereby be obtained with a clinically acceptable duration.

Image-guided radiation therapy (IGRT) allows radiation dose deposition with a high degree of geometric accuracy. Previous studies have demonstrated that such therapies may benefit from the employment of deformable image registration (DIR) algorithms, which allow both the automatic tracking of anatomical changes and accumulation of the delivered radiation dose over time. In order to ensure patient care and safety, however, the estimated deformations must be subjected to stringent quality assurance (QA) measures. In the present study we propose to extend the state-of-the-art methodology for QA of DIR algorithms by a set of novel biomechanical criteria. The proposed biomechanical criteria imply the calculation of the normal and shear mechanical stress, which would occur within the observed tissues as a result of the estimated deformations. The calculated stress is then compared to plausible physiological limits, providing thus the anatomical plausibility of the estimated deformations. The criteria were employed for the QA of three DIR algorithms in the context of abdominal conebeam computed tomography and magnetic resonance radiotherapy guidance. An initial evaluation of organ boundary alignment capabilities indicated that all three algorithms perform similarly. However, an analysis of the deformations within the organ boundaries with respect to the proposed biomechanical QA criteria revealed different degrees of anatomical plausibility. Additionally, it was demonstrated that violations of these criteria are also indicative of errors within the dose accumulation process. The proposed QA criteria, therefore, provide a tissue-dependent assessment of the anatomical plausibility of the deformations estimated by DIR algorithms, showcasing potential in ensuring patient safety for future adaptive IGRT treatments.

Background: Magnetic resonance (MR) thermometry allows visualization of lesion formation in real-time during cardiac radiofrequency (RF) ablation. The present study was performed to evaluate the precision of MR thermometry without RF heating in patients exhibiting cardiac arrhythmia in a clinical setting. The evaluation relied on quantification of changes in temperature measurements caused by noise and physiological motion., Methods: Fourteen patients referred for cardiovascular magnetic resonance imaging underwent an extra sequence to test the temperature mapping stability during free-breathing acquisition. Phase images were acquired using a multi-slice, cardiac-triggered, single-shot echo planar imaging sequence. Temperature maps were calculated and displayed in real-time while the electrocardiogram (ECG) was recorded. The precision of temperature measurement was assessed by measuring the temporal standard deviation and temporal mean of consecutive temperature maps over a period of three minutes. The cardiac cycle was analyzed from ECG recordings to quantify the impact of arrhythmia events on the precision of temperature measurement. Finally, two retrospective strategies were tested to remove acquisition dynamics related either to arrhythmia events or sudden breathing motion., Results: ECG synchronization allowed categorization of inter-beat intervals (RR) into distinct beat morphologies. Five patients were in stable sinus rhythm, while nine patients showed irregular RR intervals due to ectopic beats. An average temporal standard deviation of temperature of 1.6°C was observed in patients under sinus rhythm with a frame rate corresponding to the heart rate of the patient. The temporal standard deviation rose to 2.5°C in patients with arrhythmia. The retrospective rejection strategies increased the temperature precision measurement while maintaining a sufficient frame rate., Conclusions: Our results indicated that real-time cardiac MR thermometry shows good precision in patients under clinical conditions, even in the presence of arrhythmia. By providing real-time visualization of temperature distribution within the myocardium during RF delivery, MR thermometry could prevent insufficient or excessive heating and thus improve safety and efficacy., (© 2019 John Wiley & Sons, Ltd.)

Background and Purpose: To evaluate the dosimetric sparing and robustness against inter-fraction anatomical changes between photon and proton dose distributions for children with abdominal tumors., Material and Methods: Volumetric modulated arc therapy (VMAT) and intensity-modulated pencil beam scanning (PBS) proton dose distributions were calculated for 20 abdominal pediatric cases (average 3, range 1-8 years). VMAT plans were based on a full-arc while PBS plans on 2-3 posterior-oblique irradiation fields. Plans were robustly optimized on a patient-specific internal target volume (ITV) using a uniform 5 mm set-up uncertainty. Additionally, for the PBS plans a ± 3% proton range uncertainty was accounted for. Fractional dose re-calculations were performed using the planning computed tomography (CT) deformably registered to the daily cone-beam CT (CBCT) images. Fractional doses were accumulated rigidly. Planned and CBCT accumulated VMAT and PBS dose distributions were compared using dose-volume histogram (DVH) parameters., Results: Significant better sparing of the organs at risk with a maximum reduction in the mean dose of 40% was achieved with PBS. Mean ITV DVH parameters differences between planned and CBCT accumulated dose distributions were smaller than 0.5% for both VMAT and PBS. However, the ITV coverage (V 95%  > 99%) was not reached for one patient for the accumulated VMAT dose distribution., Conclusions: For pediatric patients with abdominal tumors, improved dosimetric sparing was obtained with PBS compared to VMAT. In addition, PBS delivered by posterior-oblique irradiation fields demonstrated to be robust against anatomical inter-fraction changes. Compared to PBS, daily anatomical changes proved to affect the target coverage of VMAT dose distributions to a higher extent., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Standard of care for patients with high-grade soft-tissue sarcoma (STS) are being redefined since neoadjuvant chemotherapy (NAC) has demonstrated a positive effect on patients' outcome. Yet response evaluation in clinical trials still relies on RECIST criteria., Purpose: To investigate the added value of a Delta-radiomics approach for early response prediction in patients with STS undergoing NAC., Study Type: Retrospective., Population: Sixty-five adult patients with newly-diagnosed, locally-advanced, histologically proven high-grade STS of trunk and extremities. All were treated by anthracycline-based NAC followed by surgery and had available MRI at baseline and after two chemotherapy cycles., Field Strength/sequence: Pre- and postcontrast enhanced T 1 -weighted imaging (T 1 -WI), turbo spin echo T 2 -WI at 1.5 T., Assessment: A threshold of <10% viable cells on surgical specimens defined good response (Good-HR). Two senior radiologists performed a semantic analysis of the MRI. After 3D manual segmentation of tumors at baseline and early evaluation, and standardization of voxel-sizes and intensities, absolute changes in 33 texture and shape features were calculated., Statistical Tests: Classification models based on logistic regression, support vector machine, k-nearest neighbors, and random forests were elaborated using crossvalidation (training and validation) on 50 patients ("training cohort") and was validated on 15 other patients ("test cohort")., Results: Sixteen patients were good-HR. Neither RECIST status (P = 0.112) nor semantic radiological variables were associated with response (range of P-values: 0.134-0.490) except an edema decrease (P = 0.003), although 14 shape and texture features were (range of P-values: 0.002-0.037). On the training cohort, the highest diagnostic performances were obtained with random forests built on three features: Δ&#95;Histogram&#95;Entropy, Δ&#95;Elongation, Δ&#95;Surrounding&#95;Edema, which provided: area under the curve the receiver operating characteristic = 0.86, accuracy = 88.1%, sensitivity = 94.1%, and specificity = 66.3%. On the test cohort, this model provided an accuracy of 74.6% but 3/5 good-HR were systematically ill-classified., Data Conclusion: A T 2 -based Delta-radiomics approach might improve early response assessment in STS patients with a limited number of features., Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:497-510., (© 2018 International Society for Magnetic Resonance in Medicine.)

The paper provides a numerical workflow, based on the 'real-life' clinical workflow of irreversible electroporation (IRE) performed for the treatment of deep-seated liver tumors. Thanks to a combination of numerical modeling, image registration algorithm and clinical data, our numerical workflow enables to provide the distribution of the electric field as effectively delivered by the clinical IRE procedure. As a proof of concept, we show on a specific clinical case of IRE ablation of liver tumor that clinical data could be advantageously combined to numerical simulations in a near future, in order to give to the interventional radiologists information on the effective IRE ablation. We also corroborate the simulated treated region with the post-treatment MRI performed 3 d after the treatment.

Objective: To develop and evaluate a combined motion-assisted/gated MRHIFU heating strategy designed to accelerate the treatment procedure by reducing the required number of sonications to ablate a target volume in the pancreas. Methods: A planning method for combined motion-assisted/gated MRHIFU using 4D-MRI and motion characterization is introduced. Six healthy volunteers underwent 4D-MRI for target motion characterization on a 3.0-T clinical scanner. Using displacement patterns, simulations were performed for all volunteers for three sonication approaches: gated, combined motion-assisted/gated, and static. The number of sonications needed to ablate the pancreas head was compared. The influence of displacement amplitude and target volume size was investigated. Spherical target volumes (8, 15, 20 and 34 mL) and displacement amplitudes ranging from 5 to 25 mm were evaluated. For this case, the number of sonications required to ablate the whole target was determined. Results: The number of required sonications was lowest for a static target, 62 on average (range 49-78). The gated approach required most sonications, 126 (range 97-159). The combined approach was almost as efficient as the hypothetical static case, with an average of 78 (range 53-123). Simulations showed that with a 5-mm displacement amplitude, the target could be treated by making use of motion-assisted MRHIFU sonications only. In that case, this approach allowed the lowest number of sonication, while for 10 mm and above, the number of required sonications increased. Conclusion: The use of a combined motion-assisted/gated MRHIFU strategy may accelerate tumor ablation in the pancreas when respiratory-induced displacement amplitudes are between 5 and 10 mm.

Medical imaging is currently employed in the diagnosis, planning, delivery and response monitoring of cancer treatments. Due to physiological motion and/or treatment response, the shape and location of the pathology and organs-at-risk may change over time. Establishing their location within the acquired images is therefore paramount for an accurate treatment delivery and monitoring. A feasible solution for tracking anatomical changes during an image-guided cancer treatment is provided by image registration algorithms. Such methods are, however, often built upon elements originating from the computer vision/graphics domain. Since the original design of such elements did not take into consideration the material properties of particular biological tissues, the anatomical plausibility of the estimated deformations may not be guaranteed. In the current work we adapt two existing variational registration algorithms, namely Horn-Schunck and EVolution, to online soft tissue tracking. This is achieved by enforcing an incompressibility constraint on the estimated deformations during the registration process. The existing and the modified registration methods were comparatively tested against several quality assurance criteria on abdominal in vivo MR and CT data. These criteria included: the Dice similarity coefficient (DSC), the Jaccard index, the target registration error (TRE) and three additional criteria evaluating the anatomical plausibility of the estimated deformations. Results demonstrated that both the original and the modified registration methods have similar registration capabilities in high-contrast areas, with DSC and Jaccard index values predominantly in the 0.8-0.9 range and an average TRE of 1.6-2.0 mm. In contrast-devoid regions of the liver and kidneys, however, the three additional quality assurance criteria have indicated a considerable improvement of the anatomical plausibility of the deformations estimated by the incompressibility-constrained methods. Moreover, the proposed registration models maintain the potential of the original methods for online image-based guidance of cancer treatments.

Image-guided external beam radiotherapy (EBRT) allows radiation dose deposition with a high degree of accuracy and precision. Guidance is usually achieved by estimating the displacements, via image registration, between cone beam computed tomography (CBCT) and computed tomography (CT) images acquired at different stages of the therapy. The resulting displacements are then used to reposition the patient such that the location of the tumor at the time of treatment matches its position during planning. Moreover, ongoing research aims to use CBCT-CT image registration for online plan adaptation. However, CBCT images are usually acquired using a small number of x-ray projections and/or low beam intensities. This often leads to the images being subject to low contrast, low signal-to-noise ratio and artifacts, which ends-up hampering the image registration process. Previous studies addressed this by integrating additional image processing steps into the registration procedure. However, these steps are usually designed for particular image acquisition schemes, therefore limiting their use on a case-by-case basis. In the current study we address CT to CBCT and CBCT to CBCT registration by the means of the recently proposed EVolution registration algorithm. Contrary to previous approaches, EVolution does not require the integration of additional image processing steps in the registration scheme. Moreover, the algorithm requires a low number of input parameters, is easily parallelizable and provides an elastic deformation on a point-by-point basis. Results have shown that relative to a pure CT-based registration, the intrinsic artifacts present in typical CBCT images only have a sub-millimeter impact on the accuracy and precision of the estimated deformation. In addition, the algorithm has low computational requirements, which are compatible with online image-based guidance of EBRT treatments.

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of  ∼1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions.

Stereotactic body radiation therapy (SBRT) has shown great promise in increasing local control rates for renal-cell carcinoma (RCC). Characterized by steep dose gradients and high fraction doses, these hypo-fractionated treatments are, however, prone to dosimetric errors as a result of variations in intra-fraction respiratory-induced motion, such as drifts and amplitude alterations. This may lead to significant variations in the deposited dose. This study aims to develop a method for calculating the accumulated dose for MRI-guided SBRT of RCC in the presence of intra-fraction respiratory variations and determine the effect of such variations on the deposited dose. For this, RCC SBRT treatments were simulated while the underlying anatomy was moving, based on motion information from three motion models with increasing complexity: (1) STATIC, in which static anatomy was assumed, (2) AVG-RESP, in which 4D-MRI phase-volumes were time-weighted, and (3) PCA, a method that generates 3D volumes with sufficient spatio-temporal resolution to capture respiration and intra-fraction variations. Five RCC patients and two volunteers were included and treatments delivery was simulated, using motion derived from subject-specific MR imaging. Motion was most accurately estimated using the PCA method with root-mean-squared errors of 2.7, 2.4, 1.0 mm for STATIC, AVG-RESP and PCA, respectively. The heterogeneous patient group demonstrated relatively large dosimetric differences between the STATIC and AVG-RESP, and the PCA reconstructed dose maps, with hotspots up to [Formula: see text] of the D99 and an underdosed GTV in three out of the five patients. This shows the potential importance of including intra-fraction motion variations in dose calculations.

Proton resonance frequency shift-based magnetic resonance thermometry is a currently used technique for monitoring temperature during targeted thermal therapies. However, in order to provide temperature updates with very short latency times, fast MR acquisition schemes are usually employed, which in turn might lead to noisy temperature measurements. This will, in general, have a direct impact on therapy control and endpoint detection. In this paper, we address this problem through an improved non-local filtering technique applied on the temperature images. Compared with previous non-local filtering methods, the proposed approach considers not only spatial information but also exploits temporal redundancies. The method is fully automatic and designed to improve the precision of the temperature measurements while at the same time maintaining output accuracy. In addition, the implementation was optimized in order to ensure real-time availability of the temperature measurements while having a minimal impact on latency. The method was validated in three complementary experiments: a simulation, an ex-vivo and an in-vivo study. Compared to the original non-local means filter and two other previously employed temperature filtering methods, the proposed approach shows considerable improvement in both accuracy and precision of the filtered data. Together with the low computational demands of the numerical scheme, the proposed filtering technique shows great potential for improving temperature measurements during real-time MR thermometry dedicated to targeted thermal therapies.

The use of magnetic resonance (MR) thermometry for the monitoring of thermal ablation is rapidly expanding. However, this technique remains challenging for the monitoring of the treatment of cardiac arrhythmia by radiofrequency ablation due to the heart displacement with respiration and contraction. Recent studies have addressed this problem by compensating in-plane motion in real-time with optical-flow based tracking technique. However, these algorithms are sensitive to local variation of signal intensity on magnitude images associated with tissue heating. In this study, an optical-flow algorithm was combined with a principal component analysis method to reduce the impact of such effects. The proposed method was integrated to a fully automatic cardiac MR thermometry pipeline, compatible with a future clinical workflow. It was evaluated on nine healthy volunteers under free breathing conditions, on a phantom and in vivo on the left ventricle of a sheep. The results showed that local intensity changes in magnitude images had lower impact on motion estimation with the proposed method. Using this strategy, the temperature mapping accuracy was significantly improved.

Purpose: A new real-time MR-thermometry pipeline was developed to measure multiple temperature images per heartbeat with 1.6×1.6×3 mm 3 spatial resolution. The method was evaluated on 10 healthy volunteers and during radiofrequency ablation (RFA) in sheep., Methods: Multislice, electrocardiogram-triggered, echo-planar imaging was combined with parallel imaging, under free breathing conditions. In-plane respiratory motion was corrected on magnitude images by an optical flow algorithm. Motion-related susceptibility artifacts were compensated on phase images by an algorithm based on Principal Component Analysis. Correction of phase drift and temporal filter were included in the pipeline implemented in the Gadgetron framework. Contact electrograms were recorded simultaneously with MR thermometry by an MR-compatible ablation catheter., Results: The temporal standard deviation of temperature in the left ventricle remained below 2 °C on each volunteer. In sheep, focal heated regions near the catheter tip were observed on temperature images (maximal temperature increase of 38 °C) during RFA, with contact electrograms of acceptable quality. Thermal lesion dimensions at gross pathology were in agreement with those observed on thermal dose images., Conclusion: This fully automated MR thermometry pipeline (five images/heartbeat) provides direct assessment of lesion formation in the heart during catheter-based RFA, which may improve treatment of cardiac arrhythmia by ablation. Magn Reson Med 77:673-683, 2017. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)

In radiotherapy, abdominal and thoracic sites are candidates for performing motion tracking. With real-time control it is possible to adjust the multileaf collimator (MLC) position to the target position. However, positions are not perfectly matched and position errors arise from system delays and complicated response of the electromechanic MLC system. Although, it is possible to compensate parts of these errors by using predictors, residual errors remain and need to be compensated to retain target coverage. This work presents a method to statistically describe tracking errors and to automatically derive a patient-specific, per-segment margin to compensate the arising underdosage on-line, i.e. during plan delivery. The statistics of the geometric error between intended and actual machine position are derived using kernel density estimators. Subsequently a margin is calculated on-line according to a selected coverage parameter, which determines the amount of accepted underdosage. The margin is then applied onto the actual segment to accommodate the positioning errors in the enlarged segment. The proof-of-concept was tested in an on-line tracking experiment and showed the ability to recover underdosages for two test cases, increasing [Formula: see text] in the underdosed area about [Formula: see text] and [Formula: see text], respectively. The used dose model was able to predict the loss of dose due to tracking errors and could be used to infer the necessary margins. The implementation had a running time of 23 ms which is compatible with real-time requirements of MLC tracking systems. The auto-adaptivity to machine and patient characteristics makes the technique a generic yet intuitive candidate to avoid underdosages due to MLC tracking errors.

Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.

We have previously demonstrated the feasibility of monitoring ultrasound-mediated uptake of a hydrophilic model drug in real time with dynamic confocal fluorescence microscopy. In this study, we evaluate and correct the impact of photobleaching to improve the accuracy of pharmacokinetic parameter estimates. To model photobleaching of the fluorescent model drug SYTOX Green, a photobleaching process was added to the current two-compartment model describing cell uptake. After collection of the uptake profile, a second acquisition was performed when SYTOX Green was equilibrated, to evaluate the photobleaching rate experimentally. Photobleaching rates up to 5.0 10(-3) s(-1) were measured when applying power densities up to 0.2 W.cm(-2). By applying the three-compartment model, the model drug uptake rate of 6.0 10(-3) s(-1) was measured independent of the applied laser power. The impact of photobleaching on uptake rate estimates measured by dynamic fluorescence microscopy was evaluated. Subsequent compensation improved the accuracy of pharmacokinetic parameter estimates in the cell population subjected to sonopermeabilization.

MRI-guided High Intensity Focused Ultrasound (MRI-HIFU) is a promising method for the non-invasive ablation of pathological tissue in many organs, including mobile organs such as liver and kidney. The possibility to locally deposit thermal energy in a non-invasive way opens a path towards new therapeutic strategies with improved reliability and reduced associated trauma, leading to improved efficacy, reduced hospitalization and costs. Liver and kidney tumors represent a major health problem because not all patients are suitable for curative treatment with surgery. Currently, radio-frequency is the most used method for percutaneous ablation. The development of a completely non-invasive method based on MR guided high intensity focused ultrasound (HIFU) treatments is of particular interest due to the associated reduced burden for the patient, treatment related patient morbidity and complication rate. The objective of MR-guidance is hereby to control heat deposition with HIFU within the targeted pathological area, despite the physiological motion of these organs, in order to provide an effective treatment with a reduced duration and an increased level of patient safety. Regarding this, several technological challenges have to be addressed: Firstly, the anatomical location of both organs within the thoracic cage requires inter-costal ablation strategies, which preserve the therapeutic efficiency, but prevent undesired tissue damage to the ribs and the intercostal muscle. Secondly, both therapy guidance and energy deposition have to be rendered compatible with the continuous physiological motion of the abdomen.

For quality assurance and adaptive radiotherapy, validation of the actual delivered dose is crucial.Intrafractional anatomy changes cannot be captured satisfactorily during treatment with hitherto available imaging modalitites. Consequently, dose calculations are based on the assumption of static anatomy throughout the treatment. However, intra- and interfraction anatomy is dynamic and changes can be significant.In this paper, we investigate the use of an MR-linac as a dose tracking modality for the validation of treatments in abdominal targets where both respiratory and long-term peristaltic and drift motion occur.The on-line MR imaging capability of the modality provides the means to perform respiratory gating of both delivery and acquisition yielding a model-free respiratory motion management under free breathing conditions.In parallel to the treatment, the volumetric patient anatomy was captured and used to calculate the applied dose. Subsequently, the individual doses were warped back to the planning grid to obtain the actual dose accumulated over the entire treatment duration. Ultimately, the planned dose was validated by comparison with the accumulated dose.Representative for a site subject to breathing modulation, two kidney cases (25 Gy target dose) demonstrated the working principle on volunteer data and simulated delivery. The proposed workflow successfully showed its ability to track local dosimetric changes. Integration of the on-line anatomy information could reveal local dose variations  -2.3-1.5 Gy in the target volume of a volunteer dataset. In the adjacent organs at risk, high local dose errors ranging from  -2.5 to 1.9 Gy could be traced back.

Image processing such as deformable image registration finds its way into radiotherapy as a means to track non-rigid anatomy. With the advent of magnetic resonance imaging (MRI) guided radiotherapy, intrafraction anatomy snapshots become technically feasible. MRI provides the needed tissue signal for high-fidelity image registration. However, acquisitions, especially in 3D, take a considerable amount of time. Pushing towards real-time adaptive radiotherapy, MRI needs to be accelerated without degrading the quality of information. In this paper, we investigate the impact of image resolution on the quality of motion estimations. Potentially, spatially undersampled images yield comparable motion estimations. At the same time, their acquisition times would reduce greatly due to the sparser sampling. In order to substantiate this hypothesis, exemplary 4D datasets of the abdomen were downsampled gradually. Subsequently, spatiotemporal deformations are extracted consistently using the same motion estimation for each downsampled dataset. Errors between the original and the respectively downsampled version of the dataset are then evaluated. Compared to ground-truth, results show high similarity of deformations estimated from downsampled image data. Using a dataset with (2.5 mm)3 voxel size, deformation fields could be recovered well up to a downsampling factor of 2, i.e. (5 mm)3. In a therapy guidance scenario MRI, imaging speed could accordingly increase approximately fourfold, with acceptable loss of estimated motion quality.

Microbubbles (MBs) in combination with ultrasound (US) can enhance cell membrane permeability, and have the potential to facilitate the cellular uptake of hydrophilic molecules. However, the exact mechanism behind US- and MB-mediated intracellular delivery still remains to be fully understood. Among the proposed mechanisms are formation of transient pores and endocytosis stimulation. In our study, we investigated whether endocytosis is involved in US- and MB-mediated delivery of small molecules. Dynamic fluorescence microscopy was used to investigate the effects of endocytosis inhibitors on the pharmacokinetic parameters of US- and MB-mediated uptake of SYTOX Green, a 600 Da hydrophilic model drug. C6 rat glioma cells, together with SonoVue(®) MBs, were exposed to 1.4 MHz US waves at 0.2 MPa peak-negative pressure. Collection of the signal intensity in each individual nucleus was monitored during and after US exposure by a fibered confocal fluorescence microscope designed for real-time imaging. Exposed to US waves, C6 cells pretreated with chlorpromazine, an inhibitor of clathrin-mediated endocytosis, showed up to a 2.5-fold significant increase of the uptake time constant, and a 1.1-fold increase with genistein, an inhibitor of caveolae-mediated endocytosis. Both inhibitors slowed down the US-mediated uptake of SYTOX Green. With C6 cells and our experimental settings, these quantitative data indicate that endocytosis plays a role in sonopermeabilization-mediated delivery of small molecules with a more predominant contribution of clathrin-mediated endocytosis.

For motion adaptive radiotherapy, dynamic multileaf collimator tracking can be employed to reduce treatment margins by steering the beam according to the organ motion. The Elekta Agility 160 MLC has hitherto not been evaluated for its tracking suitability. Both dosimetric performance and latency are key figures and need to be assessed generically, independent of the used motion sensor. In this paper, we propose the use of harmonic functions directly fed to the MLC to determine its latency during continuous motion. Furthermore, a control variable is extracted from a camera system and fed to the MLC. Using this setup, film dosimetry and subsequent γ statistics are performed, evaluating the response when tracking (MRI)-based physiologic motion in a closed-loop. The delay attributed to the MLC itself was shown to be a minor contributor to the overall feedback chain as compared to the impact of imaging components such as MRI sequences. Delay showed a linear phase behaviour of the MLC employed in continuously dynamic applications, which enables a general MLC-characterization. Using the exemplary feedback chain, dosimetry showed a vast increase in pass rate employing γ statistics. In this early stage, the tracking performance of the Agility using the test bench yielded promising results, making the technique eligible for translation to tracking using clinical imaging modalities.

Purpose: To determine the optimum sampling strategy for retrospective reconstruction of 4-dimensional (4D) MR data for nonrigid motion characterization of tumor and organs at risk for radiation therapy purposes., Methods and Materials: For optimization, we compared 2 surrogate signals (external respiratory bellows and internal MRI navigators) and 2 MR sampling strategies (Cartesian and radial) in terms of image quality and robustness. Using the optimized protocol, 6 pancreatic cancer patients were scanned to calculate the 4D motion. Region of interest analysis was performed to characterize the respiratory-induced motion of the tumor and organs at risk simultaneously., Results: The MRI navigator was found to be a more reliable surrogate for pancreatic motion than the respiratory bellows signal. Radial sampling is most benign for undersampling artifacts and intraview motion. Motion characterization revealed interorgan and interpatient variation, as well as heterogeneity within the tumor., Conclusions: A robust 4D-MRI method, based on clinically available protocols, is presented and successfully applied to characterize the abdominal motion in a small number of pancreatic cancer patients., (Copyright © 2015 Elsevier Inc. All rights reserved.)