A unifying probabilistic Bayesian approach to derive electron density from MRI for radiation therapy treatment planning.

MRI significantly improves the accuracy and reliability of target delineation in radiation therapy for certain tumors due to its superior soft tissue contrast compared to CT. A treatment planning process with MRI as the sole imaging modality will eliminate systematic CT/MRI co-registration errors, reduce cost and radiation exposure, and simplify clinical workflow. However, MRI lacks the key electron density information necessary for accurate dose calculation and generating reference images for patient setup. The purpose of this work is to develop a unifying method to derive electron density from standard T1-weighted MRI. We propose to combine both intensity and geometry information into a unifying probabilistic Bayesian framework for electron density mapping. For each voxel, we compute two conditional probability density functions (PDFs) of electron density given its: (1) T1-weighted MRI intensity, and (2) geometry in a reference anatomy, obtained by deformable image registration between the MRI of the atlas and test patient. The two conditional PDFs containing intensity and geometry information are combined into a unifying posterior PDF, whose mean value corresponds to the optimal electron density value under the mean-square error criterion. We evaluated the algorithm's accuracy of electron density mapping and its ability to detect bone in the head for eight patients, using an additional patient as the atlas or template. Mean absolute HU error between the estimated and true CT, as well as receiver operating characteristics for bone detection (HU > 200) were calculated. The performance was compared with a global intensity approach based on T1 and no density correction (set whole head to water). The proposed technique significantly reduced the errors in electron density estimation, with a mean absolute HU error of 126, compared with 139 for deformable registration (p = 2 × 10(-4)), 283 for the intensity approach (p = 2 × 10(-6)) and 282 without density correction (p = 5 × 10(-6)). For 90% sensitivity in bone detection, the proposed method achieved a specificity of 86%, compared with 80, 11 and 10% using deformable registration, intensity and without density correction, respectively. Notably, the Bayesian approach was more robust against anatomical differences between patients, with a specificity of 62% in the worst case (patient), compared to 30% specificity in registration-based approach. In conclusion, the proposed unifying Bayesian method provides accurate electron density estimation and bone detection from MRI of the head with highly heterogeneous anatomy.

Noninvasive quantification of in vitro osteoblastic differentiation in 3D engineered tissue constructs using spectral ultrasound imaging.

Non-destructive monitoring of engineered tissues is needed for translation of these products from the lab to the clinic. In this study, non-invasive, high resolution spectral ultrasound imaging (SUSI) was used to monitor the differentiation of MC3T3 pre-osteoblasts seeded within collagen hydrogels. SUSI was used to measure the diameter, concentration and acoustic attenuation of scatterers within such constructs cultured in either control or osteogenic medium over 21 days. Conventional biochemical assays were used on parallel samples to determine DNA content and calcium deposition. Construct volume and morphology were accurately imaged using ultrasound. Cell diameter was estimated to be approximately 12.5-15.5 µm using SUSI, which corresponded well to measurements of fluorescently stained cells. The total number of cells per construct assessed by quantitation of DNA content decreased from 5.6±2.4×10(4) at day 1 to 0.9±0.2×10(4) at day 21. SUSI estimation of the equivalent number of acoustic scatters showed a similar decreasing trend, except at day 21 in the osteogenic samples, which showed a marked increase in both scatterer number and acoustic impedance, suggestive of mineral deposition by the differentiating MC3T3 cells. Estimation of calcium content by SUSI was 41.7±11.4 µg/ml, which agreed well with the biochemical measurement of 38.7±16.7 µg/ml. Color coded maps of parameter values were overlaid on B-mode images to show spatiotemporal changes in cell diameter and calcium deposition. This study demonstrates the use of non-destructive ultrasound imaging to provide quantitative information on the number and differentiated state of cells embedded within 3D engineered constructs, and therefore presents a valuable tool for longitudinal monitoring of engineered tissue development.

Tomographic reconstruction of tissue properties and temperature increase for high-intensity focused ultrasound applications.

The acoustic and thermal properties as well as the temperature change within a tissue volume during high-intensity focused ultrasound ablation are critically important for treatment planning and monitoring. Described in this article is a tomographic reconstruction method used to determine the tissue properties and increase in temperature in a 3-D volume. On the basis of the iterative finite-element solution to the bioheat equation coupled with Tikhonov regularization techniques, our reconstruction algorithm solves the inverse problem of bioheat transfer and uses the time-dependent temperature measured on a tissue surface to obtain the acoustic absorption coefficient, thermal diffusivity and temperature increase within the subsurface volume. Numerical simulations were performed to validate the reconstruction algorithm. The method was initially conducted in ex vivo experiments in which time-dependent temperature on a tissue surface was measured using high-resolution, non-invasive infrared thermography.

High-frequency rapid B-mode ultrasound imaging for real-time monitoring of lesion formation and gas body activity during high-intensity focused ultrasound ablation.

The goal of this study was to examine the ability of high-frame-rate, high-resolution imaging to monitor tissue necrosis and gas-body activities formed during high-intensity focused ultrasound (HIFU) application. Ex vivo porcine cardiac tissue specimens (n = 24) were treated with HIFU exposure (4.33 MHz, 77 to 130 Hz pulse repetition frequency (PRF), 25 to 50% duty cycle, 0.2 to 1 s, 2600 W/cm(2)). RF data from B-mode ultrasound imaging were obtained before, during, and after HIFU exposure at a frame rate ranging from 77 to 130 Hz using an ultrasound imaging system with a center frequency of 55 MHz. The time history of changes in the integrated backscatter (IBS), calibrated spectral parameters, and echo-decorrelation parameters of the RF data were assessed for lesion identification by comparison against gross sections. Temporal maximum IBS with +12 dB threshold achieved the best identification with a receiver-operating characteristic (ROC) curve area of 0.96. Frame-to-frame echo decorrelation identified and tracked transient gas-body activities. Macroscopic (millimeter-sized) cavities formed when the estimated initial expansion rate of gas bodies (rate of expansion in lateral-to-beam direction) crossed 0.8 mm/s. Together, these assessments provide a method for monitoring spatiotemporal evolution of lesion and gas-body activity and for predicting macroscopic cavity formation.