Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects.

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.

Deciphering tumour tissue organization by 3D electron microscopy and machine learning.

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.

Improved 18-FDG PET/CT diagnosis of multiple myeloma diffuse disease by radiomics analysis.

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.

Biomechanical quality assurance criteria for deformable image registration algorithms used in radiotherapy guidance.

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.

Assessment of left ventricle magnetic resonance temperature stability in patients in the presence of arrhythmias.

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.

Evaluating the benefit of PBS vs. VMAT dose distributions in terms of dosimetric sparing and robustness against inter-fraction anatomical changes for pediatric abdominal tumors.

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 (V95% > 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.

A planning strategy for combined motion-assisted/gated MR guided focused ultrasound treatment of the pancreas.

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.

Numerical workflow of irreversible electroporation for deep-seated tumor.

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.

T2 -based MRI Delta-radiomics improve response prediction in soft-tissue sarcomas treated by neoadjuvant chemotherapy.

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 T1 -weighted imaging (T1 -WI), turbo spin echo T2 -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_Histogram_Entropy, Δ_Elongation, Δ_Surrounding_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 T2 -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.

Non-rigid CT/CBCT to CBCT registration for online external beam radiotherapy guidance.

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.

Effect of intra-fraction motion on the accumulated dose for free-breathing MR-guided stereotactic body radiation therapy of renal-cell carcinoma.

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.

An Adaptive Non-Local-Means Filter for Real-Time MR-Thermometry.

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.

Improved cardiac magnetic resonance thermometry and dosimetry for monitoring lesion formation during catheter ablation.

PURPOSE: A new real-time MR-thermometry pipeline was developed to measure multiple temperature images per heartbeat with 1.6×1.6×3 mm3 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.

Image-driven, model-based 3D abdominal motion estimation for MR-guided radiotherapy.

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.

MRI-Guided HIFU Methods for the Ablation of Liver and Renal Cancers.

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.

Recruitment of endocytosis in sonopermeabilization-mediated drug delivery: a real-time study.

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.

Tracking of cell nuclei for assessment of in vitro uptake kinetics in ultrasound-mediated drug delivery using fibered confocal fluorescence microscopy.

PURPOSE: Previously, we demonstrated the feasibility to monitor ultrasound-mediated uptake of a cell-impermeable model drug in real time with fibered confocal fluorescence microscopy. Here, we present a complete post-processing methodology, which corrects for cell displacements, to improve the accuracy of pharmacokinetic parameter estimation. PROCEDURES: Nucleus detection was performed based on the radial symmetry transform algorithm. Cell tracking used an iterative closest point approach. Pharmacokinetic parameters were calculated by fitting a two-compartment model to the time-intensity curves of individual cells. RESULTS: Cells were tracked successfully, improving time-intensity curve accuracy and pharmacokinetic parameter estimation. With tracking, 93 % of the 370 nuclei showed a fluorescence signal variation that was well-described by a two-compartment model. In addition, parameter distributions were narrower, thus increasing precision. CONCLUSIONS: Dedicated image analysis was implemented and enabled studying ultrasound-mediated model drug uptake kinetics in hundreds of cells per experiment, using fiber-based confocal fluorescence microscopy.

MRI contrast variation of thermosensitive magnetoliposomes triggered by focused ultrasound: a tool for image-guided local drug delivery.

Improved drug delivery control during chemotherapy has the potential to increase the therapeutic index. MRI contrast agent such as iron oxide nanoparticles can be co-encapsulated with drugs in nanocarrier liposomes allowing their tracking and/or visualization by MRI. Furthermore, the combination of a thermosensitive liposomal formulation with an external source of heat such as high intensity focused ultrasound guided by MR temperature mapping allows the controlled local release of the content of the liposome. MRI-guided high-intensity focused ultrasound (HIFU), in combination represents a noninvasive technique to generate local hyperthermia for drug release. In this study we used ultrasmall superparamagnetic iron oxide nanoparticles (USPIO) encapsulated in thermosensitive liposomes to obtain thermosensitive magnetoliposomes (TSM). The transverse and longitudinal relaxivities of this MRI contrast agent were measured upon TSM membrane phase transition in vitro using a water bath or HIFU. The results showed significant differences for MRI signal enhancement and relaxivities before and after heating, which were absent for nonthermosensitive liposomes and free nanoparticles used as controls. Thus, incorporation of USPIO as MRI contrast agents into thermosensitive liposomes should, besides TSM tumor accumulation monitoring, allow the visualization of TSM membrane phase transition upon temperature elevation. In conclusion, HIFU under MR image guidance in combination with USPIO-loaded thermosensitive liposomes as drug delivery system has the potential for a better control of drug delivery and to increase the drug therapeutic index.

Real-time assessment of ultrasound-mediated drug delivery using fibered confocal fluorescence microscopy.

PURPOSE: Transport across the plasma membrane is a critical step of drug delivery for weakly permeable compounds with intracellular mode of action. The purpose of this study is to demonstrate real-time monitoring of ultrasound (US)-mediated cell-impermeable model drug uptake with fibered confocal fluorescence microscopy (FCFM). PROCEDURES: An in vitro setup was designed to combine a mono-element US transducer, a cell chamber with a monolayer of tumor cells together with SonoVue microbubbles, and a FCFM system. The cell-impermeable intercalating dye, SYTOX Green, was used to monitor US-mediated uptake. RESULTS: The majority of the cell population showed fluorescence signal enhancement 10 s after US onset. The mean rate constant k of signal enhancement was calculated to be 0.23 ± 0.04 min(-1). CONCLUSIONS: Feasibility of real-time monitoring of US-mediated intracellular delivery by FCFM has been demonstrated. The method allowed quantitative assessment of model drug uptake, holding great promise for further local drug delivery studies.