In the study of asthma, a vital role is played by mouse models, because knockout or transgenic methods can be used to alter disease pathways and identify therapeutic targets that affect lung function. Assessment of lung function in rodents by available methods is insensitive because these techniques lack regional specificity. A more sensitive method for evaluating lung function in human asthma patients uses hyperpolarized (HP) 3 He MRI before and after bronchoconstriction induced by methacholine (MCh). We now report the ability to perform such 3 He imaging of MCh response in mice, where voxels must be ϳ3000 times smaller than in humans and 3 He diffusion becomes an impediment to resolving the airways. We show three-dimensional (

Background: Radiotherapy continues to be delivered uniformly without consideration of individual tumor characteristics. To advance toward more precise treatments in radiotherapy, we queried the lung computed tomography (CT)-derived feature space to identify radiation sensitivity parameters that can predict treatment failure and hence guide the individualization of radiotherapy dose. Methods: We used a cohort-based registry of 849 patients with cancer in the lung treated with high dose radiotherapy using stereotactic body radiotherapy. We input pre-therapy lung CT images into a multi-task deep neural network, Deep Profiler, to generate an image fingerprint that primarily predicts time to event treatment outcomes and secondarily approximates classical radiomic features. We validated our findings in an independent study population (n = 95). Deep Profiler was combined with clinical variables to derive iGray, an individualized dose that estimates treatment failure probability to be <5%. Findings: Radiation treatments in patients with high Deep Profiler scores fail at a significantly higher rate than in those with low scores. The 3-year cumulative incidences of local failure were 20.3% (95% CI: 16.0–24.9) and 5.7% (95% CI: 3.5–8.8), respectively. Deep Profiler independently predicted local failure (hazard ratio 1.65, 95% 1.02–2.66, p = 0.04). Models that included Deep Profiler and clinical variables predicted treatment failures with a concordance index of 0.72 (95% CI: 0.67–0.77), a significant improvement compared to classical radiomics or clinical variables alone (p = <0.001 and <0.001, respectively). Deep Profiler performed well in an external study population (n = 95), accurately predicting treatment failures across diverse clinical settings and CT scanner types (concordance index = 0.77 [95% CI: 0.69–0.92]). iGray had a wide dose range (21.1–277 Gy, BED), suggested dose reductions in 23.3% of patients and can be safely delivered in the majority of cases. Interpretation: Our results indicate that there are image-distinct subpopulations that have differential sensitivity to radiotherapy. The image-based deep learning framework proposed herein is the first opportunity to use medical images to individualize radiotherapy dose.

With the development of various models of pulmonary disease, there is tremendous interest in quantitative regional assessment of pulmonary function. While ventilation imaging has been addressed to a certain extent, perfusion imaging for small animals has not kept pace. In humans and large animals perfusion can be assessed using dynamic contrast-enhanced (DCE) MRI with a single bolus injection of a gadolinium (Gd)-based contrast agent. But the method developed for the clinic cannot be translated directly to image the rodent due to the combined requirements of higher spatial and temporal resolution. This work describes a novel image acquisition technique staggered over multiple, repeatable bolus injections of contrast agent using an automated microinjector, synchronized with image acquisition to achieve dynamic first-pass contrast enhancement in the rat lung. This allows dynamic first-pass imaging that can be used to quantify pulmonary perfusion. Gas exchange between the airspaces and the blood is one of the core functions of the lungs. Matched ventilation and perfusion is essential for effective gas exchange (1). Ventilation/perfusion mismatch occurs during most respiratory diseases, such as chronic obstructive pulmonary disease (COPD), asthma, pulmonary embolism (PE), and pulmonary arterial hypertension (PAH). With a large number of genetic rodent models of pulmonary diseases now available for diseases such as asthma (2), COPD (3), pulmonary hypertension (4), pneumonia (5), and pulmonary fibrosis (6), there is a need to develop robust techniques for quantitative regional assessment of pulmonary function in small animals (7).A number of imaging techniques have been developed over the years to study regional lung function. Pulmonary ventilation/perfusion (V/Q) imaging in humans is traditionally performed using a pair of nuclear scans that use inhaled and injected radioisotopes to assess lung function (8). While this technique has been demonstrated in animals, it is limited by poor spatial and temporal resolution and also requires the administration of radioactive materials.The use of MR for lung imaging has been previously limited due to extremely low proton density and susceptibility-related signal loss. With the development of intrinsic as well as extrinsic contrast agent techniques, MRI is emerging as a choice for high-resolution functional imaging in the lung. While MRI is being developed as an alternative in clinics using hyperpolarized 3 He (9,10) or paramagnetic 15 O (11) for ventilation, and dynamic contrastenhanced (DCE) MRI for perfusion, the technological barriers in developing these methods for small animal imaging have been significant.Most MRI pulmonary imaging methods in the rodent have been developed to demonstrate ventilation (12,13); however, methods for perfusion imaging have remained elusive. Quantitative perfusion imaging in the lungs has been demonstrated in humans, canine, and porcine models (14 -16) by capturing the wash-in and wash-out of a single bolus of contrast agent. Most studies on i...

Purpose Wide bore CT scanners use extended field‐of‐view (eFOV) reconstruction algorithms to attempt to recreate tissue truncated due to large patient habitus. Radiation therapy planning systems rely on accurate CT numbers in order to correctly plan and calculate radiation dose. This study looks at the impact of eFOV reconstructions on CT numbers and radiation dose calculations in real patient geometries. Methods A large modular phantom based on real patient geometries was created to surround a CIRS Model 062M phantom. The modular sections included a smooth patient surface, a skin fold in the patient surface, and the addition of arms for simulation of the patient in arms up or arms down position. This phantom was used to evaluate the accuracy of CT numbers for three extended FOV algorithms implemented on Siemens CT scanners: eFOV, HDFOV, and HDProFOV. Six different configurations of the phantoms were scanned and images were reconstructed for the three different extended FOV algorithms. The CIRS phantom inserts and overall phantom geometry were contoured in each image, and the Hounsfield units (HU) numbers were compared to an image of the phantom within the standard scan FOV (sFOV) without the modular sections. To evaluate the effect on dose calculations, six radiotherapy patients previously treated at our institution (three head and neck and three chest/pelvis) whose body circumferences extended past the 50 cm sFOV in the treatment planning CT were used. Images acquired on a Siemens Sensation Open scanner were reconstructed using sFOV, eFOV and HDFOV algorithms. A physician and dosimetrist identified the radiation target, critical organs, and external patient contour. A benchmark CT was created for each patient, consisting of an average of the 3 CT reconstructions with a density override applied to regions containing truncation artifacts. The benchmark CT was used to create an optimal radiation treatment plan. The plan was copied onto each CT reconstruction without density override and dose was recalculated. Results Tissue extending past the sFOV impacts the HU numbers for tissues inside and outside the sFOV when using extended FOV reconstructions. On average, the HU for all CIRS density inserts in the arms up (arms down) position varied by 43 HU (67 HU), 39 HU (73 HU), and 18 HU (51 HU) for the eFOV, HDFOV, and HDProFOV scans, respectively. In the patient dose calculations, patients with a smooth patient contour had the least deviation from the benchmark in the HDFOV (0.1–0.5%) compared to eFOV (0.4–1.8%) reconstructions. In cases with large amounts of tissue and irregular skin folds, the eFOV deviated the least from the benchmark (range 0.2–0.6% dose difference) compared to HDFOV (range 1.3–1.8% dose difference). Conclusions All reconstruction algorithms demonstrated good CT number accuracy in the center of the image. Larger artifacts are seen near and extending outside the scan FOV, however, dose calculations performed using typical beam arrangements using the extended FOV reconstructions were still mostly wit...

Results from this study indicate that the performance of template matching is comparable with or better than that of manual tumor localization. This study serves as preliminary investigations towards developing online motion tracking techniques for hybrid MRI-Linac systems. Accuracy of template matching makes it a suitable candidate to replace the labor intensive manual tumor localization for obtaining the ground truth when testing other motion management techniques.

Dynamic contrast-enhanced MRI (or DCE-MRI) is a useful tool for measuring blood flow and perfusion, and it has found use in the study of pulmonary perfusion in animal models. However, DCE-MRI experiments are difficult in small animals such as rats. A recently developed method known as Interleaved Radial Imaging and Sliding window-keyhole (IRIS) addresses this problem by using a data acquisition scheme that covers (k, t)-space with data acquired from multiple bolus injections of a contrast agent. However, the temporal resolution of IRIS is limited by the effects of temporal averaging inherent in the sliding window and keyhole operations. This article describes a new method to cover (k, t)-space based on the theory of partially separable functions (PSF). Specifically, a sparse sampling of (k, t)-space is performed to acquire two data sets, one with high-temporal resolution and the other with extended k-space coverage. The high-temporal resolution training data are used to determine the temporal basis functions of the PSF model, whereas the other data set is used to determine the spatial variations of the model. The proposed method was validated by simulations and demonstrated by an experimental study. In this particular study, the proposed method achieved a temporal resolution of 32 msec. Key words: dynamic contrast-enhanced MRI; pulmonary; lung; perfusion; partially separable function; PSF Dynamic contrast-enhanced MRI (or DCE-MRI) experiments often involve the acquisition of a time series of images after the bolus injection of a contrast agent. These images are then used to estimate perfusion metrics [such as time of peak contrast enhancement, wash-in rate, and mean transit time (MTT)] in tissues and blood vessels (1). Many respiratory diseases are known to affect perfusion characteristics in the pulmonary arteries and veins (2-7), and the diagnostic value of perfusion measurements in pulmonary blood vessels has been the topic of DCE-MRI research for many years using genetically bred rat models (2,5-8). However, imaging these small animals places high demands on signal-to-noise ratio (SNR) and spatiotemporal resolution. To address this problem for pulmonary perfusion imaging, Mistry et al. proposed a DCE-MRI technique, known as Interleaved Radial Imaging combined with a Sliding window-keyhole reconstruction (IRIS) (8). IRIS collects data over multiple contrast injections (8) acquired with carefully controlled experimental conditions such that the acquisition conditions were repeatable. IRIS is able to achieve much of the needed SNR and spatial resolution for pulmonary studies in rats; however, the temporal resolution is limited by the temporal averaging effect of the sliding window operation. Improved temporal resolution may improve the accuracy of the signal intensity curves from the DCE-MRI data especially since pulmonary perfusion data from rats contain frequencies as high as twice the heart rate or roughly 12 Hz (see Fig. 5a in Ref. (8)) implying a temporal Nyquist criterion of 24 Hz. Also, improved temporal...

The availability of genetically altered animal models of human disease for basic research has generated great interest in new imaging methodologies. Digital subtraction angiography (DSA) offers an appealing approach to functional imaging in small animals because of the high spatial and temporal resolution, and the ability to visualize and measure blood flow. The micro-injector described here meets crucial performance parameters to ensure optimal vessel enhancement without significantly increasing the total blood volume or producing overlap of enhanced structures. The micro-injector can inject small, reproducible volumes of contrast agent at high flow rates with computer-controlled timing synchronized to cardio-pulmonary activity. Iterative bench-top and live animal experiments with both rat and mouse have been conducted to evaluate the performance of this computer-controlled micro-injector, a first demonstration of a new device designed explicitly for the unique requirements of DSA in small animals. Injection protocols were optimized and screened for potential physiological impact. For the optimized protocols, we found that changes in the time-density curves for representative regions of interest in the thorax were due primarily to physiological changes, independent of micro-injector parameters.

Micro-CT-based cardiac function estimation in small animals requires measurement of left ventricle (LV) volume at multiple time points during the cardiac cycle. Measurement accuracy depends on the image resolution, its signal and noise properties, and the analysis procedure. This work compares the accuracy of the Otsu thresholding and a region sampled binary mixture approach, for live mouse LV volume measurement using 100 microm resolution datasets. We evaluate both analysis methods after varying the volume of injected contrast agent and the number of projections used for CT reconstruction with a goal of permitting reduced levels of both X-ray and contrast agent doses.