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Purpose: Precise correlation between three-dimensional (3D) imaging and histology can aid biomechanical modeling of the breast. We develop a framework to register ex vivo images to histology using a novel cryo-fluorescence tomography (CFT) device., Methods: A formalin-fixed cadaveric breast specimen, including chest wall, was subjected to high-resolution magnetic resonance (MR) imaging. The specimen was then frozen and embedded in an optimal cutting temperature (OCT) compound. The OCT block was placed in a CFT device with an overhead camera and 50 μm thick slices were successively shaved off the block. After each shaving, the block-face was photographed. At select locations including connective/adipose tissue, muscle, skin, and fibroglandular tissue, 20 μm sections were transferred onto cryogenic tape for manual hematoxylin and eosin staining, histological assessment, and image capture. A 3D white-light image was automatically reconstructed from the photographs by aligning fiducial markers embedded in the OCT block. The 3D MR image, 3D white-light image, and photomicrographs were rigidly registered. Target registration errors (TREs) were computed based on 10 pairs of points marked at fibroglandular intersections. The overall MR-histology registration was used to compare the MR intensities at tissue extraction sites with a one-way analysis of variance., Results: The MR image to CFT-captured white-light image registration achieved a mean TRE of 0.73 ± 0.25 mm (less than the 1 mm MR slice resolution). The block-face white-light image and block-face photomicrograph registration showed visually indistinguishable alignment of anatomical structures and tissue boundaries. The MR intensities at the four tissue sites identified from histology differed significantly (p < 0.01). Each tissue pair, except the skin-connective/adipose tissue pair, also had significantly different MR intensities (p < 0.01)., Conclusions: Fine sectioning in a highly controlled imaging/sectioning environment enables accurate registration between the MR image and histology. Statistically significant differences in MR signal intensities between histological tissues are indicators for the specificity of correlation between MRI and histology., (© 2021 American Association of Physicists in Medicine.)

Purpose: Dynamic susceptibility contrast (DSC)-MRI is a perfusion imaging technique from which useful quantitative imaging biomarkers can be derived. Relative cerebral blood volume (rCBV) is such a biomarker commonly used for evaluating brain tumors. To account for the extravasation of contrast agents in tumors, post-processing leakage correction is often applied to improve rCBV accuracy. Digital reference objects (DRO) are ideal for testing the post-processing software, because the biophysical model used to generate the DRO can be matched to the one that the software uses. This study aims to develop DROs to validate the leakage correction of software using Weisskoff model and to examine the effect of background signal time curves that are required by the model., Methods: Three DROs were generated using the Weisskoff model, each composed of nine foreground lesion objects with combinations of different levels of rCBV and contrast leakage parameter (K2). Three types of background were implemented for these DROs: (1) a multi-compartment brain-like background, (2) a sphere background with a constant signal time curve, and (3) a sphere background with signal time curve identical to that of the brain-like DRO's white matter (WM). The DROs were then analyzed with an FDA-cleared software with and without leakage correction. Leakage correction was tested with and without brain segmentation., Results: Accuracy of leakage correction was able to be verified using the brain-like phantom and the sphere phantom with WM background. The sphere with constant background did not perform well with leakage correction with or without brain segmentation. The DROs were able to verify that for the particular software tested, leakage correction with brain segmentation achieved the lowest error., Conclusions: DSC-MRI DROs with biophysical model matched to that of the post-processing software can be well used for the software's validation, provided that the background signals are also properly simulated for generating the reference time curve required by the model. Care needs to be taken to consider the interaction of the design of the DRO with the software's implementation of brain segmentation to extract the reference time curve., (© 2021 American Association of Physicists in Medicine.)

Purpose: Magnetic resonance imaging (MRI) provides noninvasive evaluation of patient's anatomy without using ionizing radiation. Due to this and the high soft-tissue contrast, MRI use has increased and has potential for use in longitudinal studies where changes in patients' anatomy or tumors at different time points are compared. Deformable image registration can be useful for these studies. Here, we describe two datasets that can be used to evaluate the registration accuracy of systems for MR images, as it cannot be assumed to be the same as that measured on CT images., Acquisition and Validation Methods: Two sets of images were created to test registration accuracy. (a) A porcine phantom was created by placing ten 0.35-mm gold markers into porcine meat. The porcine phantom was immobilized in a plastic container with movable dividers. T1-weighted, T2-weighted, and CT images were acquired with the porcine phantom compressed in four different ways. The markers were not visible on the MR images, due to the selected voxel size, so they did not interfere with the measured registration accuracy, while the markers were visible on the CT images and were used to identify the known deformation between positions. (b) Synthetic images were created using 28 head and neck squamous cell carcinoma patients who had MR scans pre-, mid-, and postradiotherapy treatment. An inter- and intrapatient variation model was created using these patient scans. Four synthetic pretreatment images were created using the interpatient model, and four synthetic post-treatment images were created for each of the pretreatment images using the intrapatient model., Data Format and Usage Notes: The T1-weighted, T2-weighted, and CT scans of the porcine phantom in the four positions are provided. Four T1-weighted synthetic pretreatment images each with four synthetic post-treatment images, and four T2-weighted synthetic pretreatment images each with four synthetic post-treatment images are provided. Additionally, the applied deformation vector fields to generate the synthetic post-treatment images are provided. The data are available on TCIA under the collection MRI-DIR., Potential Applications: The proposed database provides two sets of images (one acquired and one computer generated) for use in evaluating deformable image registration accuracy. T1- and T2-weighted images are available for each technique as the different image contrast in the two types of images may impact the registration accuracy., (© 2018 American Association of Physicists in Medicine.)

Purpose: Synthetic tissue equivalent (STE) materials currently used to simulate tumor and surrounding tissues for IROC-Houston's anthropomorphic head and thorax QA phantoms cannot be visualized using magnetic resonance (MR) imaging. The purpose of this study was to characterize dual MR/CT-visible STE materials that can be used in an end-to-end QA phantom for MR-guided radiotherapy (MRgRT) modalities., Methods: Over 80 materials' MR, CT, and dosimetric STE properties were investigated for use in MRgRT QA phantoms. The materials tested included homogeneous and heterogeneous materials to simulate soft tissue/tumor and lung tissues. Materials were scanned on a Siemens' Magnetom Espree 1.5 T using four sequences, which showed the materials visual contrast between T1- and T2-weighted images. Each material's Hounsfield number and electron density data was collected using a GE's CT Lightspeed Simulator. Dosimetric properties were examined by constructing a 10 × 10 × 20 cm 3 phantom of the selected STE materials that was divided into three sections: anterior, middle, and posterior. Anterior and posterior pieces were composed of polystyrene, whereas the middle section was substituted with the selected STE materials. EBT3 film was inserted into the phantom's midline and was irradiated using an Elekta's Versa 6 MV beam with a prescription of 6 Gy at 1.5 cm and varying field size of: 10 × 10 cm 2 , 6 × 6 cm 2 , and 3 × 3 cm 2 . Measured film PDD curves were compared to planning system calculations and conventional STE materials' percent depth dose (PDD) curves., Results: The majority of the tested materials showed comparable CT attenuation properties to their respective organ site; however, most of the tested materials were not visible on either T1- or T2-weighted MR images. Silicone, hydrocarbon, synthetic gelatin, and liquid PVC plastic-based materials showed good MR image contrast. In-house lung equivalent materials made with either silicone- or hydrocarbon-based materials had HUs ranging from: -978 to -117 and -667 to -593, respectively. Synthetic gelatin and PVC plastic-based materials resembled soft tissue/tumor equivalent materials and had HUs of: -175 to -170 and -29 to 32, respectively. PDD curves of the selected MR/CT-visible materials were comparable to IROC-Houston's conventional phantom STE materials. The smallest field size showed the largest disagreements, where the average discrepancies between calculated and measured PDD curves were 1.8% and 5.9% for homogeneous and heterogeneous testing materials, respectively., Conclusions: Gelatin, liquid plastic, and hydrocarbon-based materials were determined as alternative STE substitutes for MRgRT QA phantoms., (© 2017 American Association of Physicists in Medicine.)

Purpose: During magnetic resonance (MR)-guided thermal therapies, water proton resonance frequency shift (PRFS)-based MR temperature imaging can quantitatively monitor tissue temperature changes. It is widely known that the PRFS technique is easily perturbed by tissue motion, tissue susceptibility changes, magnetic field drift, and modality-dependent applicator-induced artifacts. Here, a referenceless Gaussian process modeling (GPM)-based estimation of the PRFS is investigated as a methodology to mitigate unwanted background field changes. The GPM offers a complementary trade-off between data fitting and smoothing and allows prior information to be used. The end result being the GPM provides a full probabilistic prediction and an estimate of the uncertainty., Methods: GPM was employed to estimate the covariance between the spatial position and MR phase measurements. The mean and variance provided by the statistical model extrapolated background phase values from nonheated neighboring voxels used to train the model. MR phase predictions in the heating ROI are computed using the spatial coordinates as the test input. The method is demonstrated in ex vivo rabbit liver tissue during focused ultrasound heating with manually introduced perturbations (n = 6) and in vivo during laser-induced interstitial thermal therapy to treat the human brain (n = 1) and liver (n = 1)., Results: Temperature maps estimated using the GPM referenceless method demonstrated a RMS error of <0.8°C with artifact-induced reference-based MR thermometry during ex vivo heating using focused ultrasound. Nonheated surrounding areas were <0.5°C from the artifact-free MR measurements. The GPM referenceless MR temperature values and thermally damaged regions were within the 95% confidence interval during in vivo laser ablations., Conclusions: A new approach to estimation for referenceless PRFS temperature imaging is introduced that allows for an accurate probabilistic extrapolation of the background phase. The technique demonstrated reliable temperature estimates in the presence of the background phase changes and was demonstrated useful in the in vivo brain and liver ablation scenarios presented., (© 2017 American Association of Physicists in Medicine.)

Purpose: For postimplant dosimetric assessment, computed tomography (CT) is commonly used to identify prostate brachytherapy seeds, at the expense of accurate anatomical contouring. Magnetic resonance imaging (MRI) is superior to CT for anatomical delineation, but identification of the negative-contrast seeds is challenging. Positive-contrast MRI markers were proposed to replace spacers to assist seed localization on MRI images. Visualization of these markers under varying scan parameters was investigated., Methods: To simulate a clinical scenario, a prostate phantom was implanted with 66 markers and 86 seeds, and imaged on a 3.0T MRI scanner using a 3D fast radiofrequency-spoiled gradient recalled echo acquisition with various combinations of scan parameters. Scan parameters, including flip angle, number of excitations, bandwidth, field-of-view, slice thickness, and encoding steps were systematically varied to study their effects on signal, noise, scan time, image resolution, and artifacts., Results: The effects of pulse sequence parameter selection on the marker signal strength and image noise were characterized. The authors also examined the tradeoff between signal-to-noise ratio, scan time, and image artifacts, such as the wraparound artifact, susceptibility artifact, chemical shift artifact, and partial volume averaging artifact. Given reasonable scan time and managable artifacts, the authors recommended scan parameter combinations that can provide robust visualization of the MRI markers., Conclusions: The recommended MRI pulse sequence protocol allows for consistent visualization of the markers to assist seed localization, potentially enabling MRI-only prostate postimplant dosimetry.

Purpose: A k-means-based classification algorithm is investigated to assess suitability for rapidly separating and classifying fat/water spectral peaks from a fast chemical shift imaging technique for magnetic resonance temperature imaging. Algorithm testing is performed in simulated mathematical phantoms and agar gel phantoms containing mixed fat/water regions., Methods: Proton resonance frequencies (PRFs), apparent spin-spin relaxation (T2*) times, and T1-weighted (T1-W) amplitude values were calculated for each voxel using a single-peak autoregressive moving average (ARMA) signal model. These parameters were then used as criteria for k-means sorting, with the results used to determine PRF ranges of each chemical species cluster for further classification. To detect the presence of secondary chemical species, spectral parameters were recalculated when needed using a two-peak ARMA signal model during the subsequent classification steps. Mathematical phantom simulations involved the modulation of signal-to-noise ratios (SNR), maximum PRF shift (MPS) values, analysis window sizes, and frequency expansion factor sizes in order to characterize the algorithm performance across a variety of conditions. In agar, images were collected on a 1.5T clinical MR scanner using acquisition parameters close to simulation, and algorithm performance was assessed by comparing classification results to manually segmented maps of the fat/water regions., Results: Performance was characterized quantitatively using the Dice Similarity Coefficient (DSC), sensitivity, and specificity. The simulated mathematical phantom experiments demonstrated good fat/water separation depending on conditions, specifically high SNR, moderate MPS value, small analysis window size, and low but nonzero frequency expansion factor size. Physical phantom results demonstrated good identification for both water (0.997 ± 0.001, 0.999 ± 0.001, and 0.986 ± 0.001 for DSC, sensitivity, and specificity, respectively) and fat (0.763 ± 0.006, 0.980 ± 0.004, and 0.941 ± 0.002 for DSC, sensitivity, and specificity, respectively). Temperature uncertainties, based on PRF uncertainties from a 5 × 5-voxel ROI, were 0.342 and 0.351°C for pure and mixed fat/water regions, respectively. Algorithm speed was tested using 25 × 25-voxel and whole image ROIs containing both fat and water, resulting in average processing times per acquisition of 2.00 ± 0.07 s and 146 ± 1 s, respectively, using uncompiled MATLAB scripts running on a shared CPU server with eight Intel Xeon(TM) E5640 quad-core processors (2.66 GHz, 12 MB cache) and 12 GB RAM., Conclusions: Results from both the mathematical and physical phantom suggest the k-means-based classification algorithm could be useful for rapid, dynamic imaging in an ROI for thermal interventions. Successful separation of fat/water information would aid in reducing errors from the nontemperature sensitive fat PRF, as well as potentially facilitate using fat as an internal reference for PRF shift thermometry when appropriate. Additionally, the T1-W or R2* signals may be used for monitoring temperature in surrounding adipose tissue.

Purpose: To investigate the utility of five different standard measurement methods for determining image uniformity for partially parallel imaging (PPI) acquisitions in terms of consistency across a variety of pulse sequences and reconstruction strategies., Methods: Images were produced with a phantom using a 12-channel head matrix coil in a 3T MRI system (TIM TRIO, Siemens Medical Solutions, Erlangen, Germany). Images produced using echo-planar, fast spin echo, gradient echo, and balanced steady state free precession pulse sequences were evaluated. Two different PPI reconstruction methods were investigated, generalized autocalibrating partially parallel acquisition algorithm (GRAPPA) and modified sensitivity-encoding (mSENSE) with acceleration factors (R) of 2, 3, and 4. Additionally images were acquired with conventional, two-dimensional Fourier imaging methods (R=1). Five measurement methods of uniformity, recommended by the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) were considered. The methods investigated were (1) an ACR method and a (2) NEMA method for calculating the peak deviation nonuniformity, (3) a modification of a NEMA method used to produce a gray scale uniformity map, (4) determining the normalized absolute average deviation uniformity, and (5) a NEMA method that focused on 17 areas of the image to measure uniformity. Changes in uniformity as a function of reconstruction method at the same R-value were also investigated. Two-way analysis of variance (ANOVA) was used to determine whether R-value or reconstruction method had a greater influence on signal intensity uniformity measurements for partially parallel MRI., Results: Two of the methods studied had consistently negative slopes when signal intensity uniformity was plotted against R-value. The results obtained comparing mSENSE against GRAPPA found no consistent difference between GRAPPA and mSENSE with regard to signal intensity uniformity. The results of the two-way ANOVA analysis suggest that R-value and pulse sequence type produce the largest influences on uniformity and PPI reconstruction method had relatively little effect., Conclusions: Two of the methods of measuring signal intensity uniformity, described by the (NEMA) MRI standards, consistently indicated a decrease in uniformity with an increase in R-value. Other methods investigated did not demonstrate consistent results for evaluating signal uniformity in MR images obtained by partially parallel methods. However, because the spatial distribution of noise affects uniformity, it is recommended that additional uniformity quality metrics be investigated for partially parallel MR images.

Purpose: Minimally invasive thermal ablative therapies as alternatives to conventional surgical management of solid tumors and other pathologies is increasing owing to the potential benefits of performing these procedures in an outpatient setting with reduced complications and comorbidity. Magnetic resonance temperature imaging (MRTI) measurement allows existing thermal dose models to use the spatiotemporal temperature history to estimate the thermal damage to tissue. However, the various thermal dose models presented in the literature employ different parameters and thresholds, affecting the reliability of thermal dosimetry. In this study, the authors quantitatively compared three thermal dose models (Arrhenius rate process, CEM43, and threshold temperature) using the dice similarity coefficient (DSC)., Methods: The DSC was used to compare the spatial overlap between the region of thermal damage as predicted by the models for in vivo normal canine brain during thermal therapy to the region of thermal damage as revealed by contrast-enhanced T1-weighted images acquired immediately after therapy (< 20 min). The outer edge of the hyperintense rim of the ablation region was used as the surrogate marker for the limits of thermal coagulation. The DSC was also used to investigate the impact of varying the thresholds on each models' ability to predict the zone of thermal necrosis., Results: At previously reported thresholds, the authors found that all three models showed good agreement (defined as DSC > 0.7) with post-treatment imaging. All three models examined across the range of commonly applied thresholds consistently showed highly accurate spatial overlap, low variability, and little dependence on temperature uncertainty. DSC values corresponding to cited thresholds were not significantly different from peak DSC values., Conclusions: Thus, the authors conclude that the all three thermal dose models can be used as a reliable surrogate for postcontrast tissue damage verification imaging in rapid ablation procedures and can also be used to enhance the capability of MRTI to control thermal therapy in real time.

Purpose: Focused ultrasound surgery (FUS) is a highly precise noninvasive procedure to ablate pathogenic tissue. FUS therapy is often combined with magnetic resonance (MR) imaging as MR imaging offers excellent target identification and allows for continuous monitoring of FUS induced temperature changes. As the dimensions of the ultrasound (US) focus are typically much smaller than the targeted volume, multiple sonications and focus repositioning are interleaved to scan the focus over the target volume. Focal scanning can be achieved electronically by using phased-array US transducers or mechanically by using dedicated mechanical actuators. In this study, the authors propose and evaluate the precision of a combined robotic FUS setup to overcome some of the limitations of the existing MRgFUS systems. Such systems are typically integrated into the patient table of the MR scanner and thus only provide an application of the US wave within a limited spatial range from below the patient., Methods: The fully MR-compatible robotic assistance system InnoMotion (InnoMedic GmbH, Herxheim, Germany) was originally designed for MR-guided interventions with needles. It offers five pneumatically driven degrees of freedom and can be moved over a wide range within the bore of the magnet. In this work, the robotic system was combined with a fixed-focus US transducer (frequency: 1.7 MHz; focal length: 68 mm, and numerical aperture: 0.44) that was integrated into a dedicated, in-house developed treatment unit for FUS application. A series of MR-guided focal scanning procedures was performed in a polyacrylamide-egg white gel phantom to assess the positioning accuracy of the combined FUS setup. In animal experiments with a 3-month-old domestic pig, the system's potential and suitability for MRgFUS was tested., Results: In phantom experiments, a total targeting precision of about 3 mm was found, which is comparable to that of the existing MRgFUS systems. Focus positioning could be performed within a few seconds. During in vivo experiments, a defined pattern of single thermal lesions and a therapeutically relevant confluent thermal lesion could be created. The creation of local tissue necrosis by coagulation was confirmed by post-FUS MR imaging and histological examinations on the treated tissue sample. During all sonications in phantom and in vivo, reliable MR imaging and online MR thermometry could be performed without compromises due to operation of the combined robotic FUS setup., Conclusions: Compared to the existing MRgFUS systems, the combined robotic FUS approach offers a wide range of spatial flexibility so that highly flexible application of the US wave would be possible, for example, to avoid risk structures within the US field. The setup might help to realize new ways of patient access in MRgFUS therapy. The setup is compatible with any closed-bore MR system and does not require an especially designed patient table.

Laser induced thermal therapy combined with the wavelength dependent optical absorption and heating power of gold-coated silica nanoshells can achieve therapeutic heating localized to a tumor volume. Accurate modeling of the spatiotemperal thermal distribution associated with this heating is essential for accurate thermal therapy treatment planning. The optical diffusion approximation (ODA), used in numerous applications of laser fluence in biology, is compared to the delta P1 optical approximation in phantoms containing different concentrations of nanoshells for several laser powers. Results are compared with temperature maps generated by magnetic resonance temperature imaging techniques and show that the delta P1 approximation is more effective than ODA at modeling the thermal distribution. The discrepancy between the two is especially prominent in phantoms with higher nanoshell concentrations where ODA was shown to give unsatisfactory results.

The authors investigated the performance of the iterative Steiglitz-McBride (SM) algorithm on an autoregressive moving average (ARMA) model of signals from a fast, sparsely sampled, multiecho, chemical shift imaging (CSI) acquisition using simulation, phantom, ex vivo, and in vivo experiments with a focus on its potential usage in magnetic resonance (MR)-guided interventions. The ARMA signal model facilitated a rapid calculation of the chemical shift, apparent spin-spin relaxation time (T2*), and complex amplitudes of a multipeak system from a limited number of echoes (< or equal 16). Numerical simulations of one- and two-peak systems were used to assess the accuracy and uncertainty in the calculated spectral parameters as a function of acquisition and tissue parameters. The measured uncertainties from simulation were compared to the theoretical Cramer-Rao lower bound (CRLB) for the acquisition. Measurements made in phantoms were used to validate the T2* estimates and to validate uncertainty estimates made from the CRLB. We demonstrated application to real-time MR-guided interventions ex vivo by using the technique to monitor a percutaneous ethanol injection into a bovine liver and in vivo to monitor a laser-induced thermal therapy treatment in a canine brain. Simulation results showed that the chemical shift and amplitude uncertainties reached their respective CRLB at a signal-to-noise ratio (SNR) > or =5 for echo train lengths (ETLs) > or =4 using a fixed echo spacing of 3.3 ms. T2* estimates from the signal model possessed higher uncertainties but reached the CRLB at larger SNRs and/or ETLs. Highly accurate estimates for the chemical shift (<0.01 ppm) and amplitude (<1.0%) were obtained with > or =4 echoes and for T2*(<1.0%) with > or =7 echoes. We conclude that, over a reasonable range of SNR, the SM algorithm is a robust estimator of spectral parameters from fast CSI acquisitions that acquire < or =16 echoes for one- and two-peak systems. Preliminary ex vivo and in vivo experiments corroborated the results from simulation experiments and further indicate the potential of this technique for MR-guided interventional procedures with high spatiotemporal resolution approximately 1.6 x 1.6 x 4 mm3 in < or =5 s.

A fast chemical shift imaging (CSI) technique based on a multiple gradient-recalled acquisition using a small number of echoes with intentional aliasing of the reference lipid peak is studied to determine its feasibility for temperature monitoring. Simulations were implemented to find parameters where the lipid and water peaks can be measured using a Fourier-based peak fitting approach as well as using an innovative autoregressive moving average technique. A phantom consisting of 50% mayonnaise/50% lemon juice was calibrated to temperature and compared to literature values. A porcine kidney was treated ex vivo with an external laser and imaged with the CSI technique with comparisons to temperature readings from a fluoroptic monitoring system and complex phase difference (CPD) calculations. To demonstrate the technique in vivo, a Balb/c mouse with a CT26 xenograft in the subcutaneous lower back was treated using gold-coated, silica-core nanoshells heated with an 808 nm interstitial laser. Compared to standard CPD techniques using a two-dimensional fast spoiled gradient recalled echo, this technique maintains spatiotemporal resolution, has high signal-to-noise ratio and accuracy over a wide range of T2* tissue values, can separate water and lipid signals, and additionally can use the lipid peak, when present, as an internal reference.

Spherical nanoparticles with a gold outer shell and silica core can be tuned to absorb near-infrared light of a specific wavelength. These nanoparticles have the potential to enhance the treatment efficacy of laser-induced thermal therapy (LITT). In order to enhance both the potential efficacy and safety of such procedures, accurate methods of treatment planning are needed to predict the temperature distribution associated with treatment application. In this work, the standard diffusion approximation was used to model the laser fluence in phantoms containing different concentrations of nanoparticles, and the temperature distribution within the phantom was simulated in three-dimensions using the finite element technique. Magnetic resonance temperature imaging was used to visualize the spatiotemporal distribution of the temperature in the phantoms. In most cases, excellent correlation is demonstrated between the simulations and the experiment (<3.0% mean error observed). This has significant implications for the treatment planning of LITT treatments using gold-silica nanoshells.

A catheter-based transurethral ultrasound applicator with angularly directional heating patterns has been designed for prostate thermal therapy and evaluated in canine prostate in vivo using MRI to monitor and assess performance. The ultrasound transducer array (3.5 mm diameter tubular transducers, 180 degrees active sectors, approximately 7.5 MHz) was integrated to a flexible delivery catheter (4 mm OD), and encapsulated within an expandable balloon (35 mm x 10 mm OD, 80 ml min(-1) ambient water) for coupling and cooling of the prostatic urethra. These devices were used to thermally coagulate targeted portions of the canine prostate (n = 2) while using MR thermal imaging (MRTI) to monitor the therapy. MRI was also used for target definition, positioning of the applicator, and evaluation of target viability post-therapy. MRTI was based upon the complex phase-difference mapping technique using an interleaved gradient echo-planar imaging sequence with lipid suppression. MRTI derived temperature distributions, thermal dose exposures, T1-contrast enhanced MR images, and histology of sectioned prostates were used to define destroyed tissue zones and characterize the three-dimensional heating patterns. The ultrasound applicators produced approximately 180 degrees directed zones of thermal coagulation within targeted tissue which extended 15-20 mm radially to the outer boundary of the prostate within 15 min. Transducer activation lengths of 17 mm and 24 mm produced contiguous zones of coagulation extending axially approximately 18 mm and approximately 25 mm from base to apex, respectively. Peak temperatures around 90 degrees C were measured, with approximately 50 degrees C-52 degrees C corresponding to outer boundary t43 = 240 min at approximately 15 min treatment time. These devices are MRI compatible, and when coupled with multiplanar MRTI provide a means for selectively controlling the length and sector angle of therapeutic thermal treatment in the prostate.