[en] Developing a method of separating intravascular contrast agent concentration to measure the arterial input function (AIF) in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of tumours, and validating its performance in phantom and in vivo experiments. A tissue-mimicking phantom was constructed to model leaky tumour vasculature and DCE-MR images of this phantom were acquired. An in vivo study was performed using tumour-bearing rabbits. Co-registered DCE-MRI and contrast-enhanced ultrasound (CEUS) images were acquired. An independent component analysis (ICA)-based method was developed to separate the intravascular component from DCE-MRI. Results were validated by comparing the time-intensity curves with the actual phantom and in vivo curves. Phantom study: the AIF extracted using ICA correlated well with the true intravascular curve. In vivo study: the AIFs extracted from DCE-MRI using ICA were very close to the true AIF. Intravascular component images were very similar to the CEUS images. The contrast onset times and initial wash-in slope of the ICA-derived AIF showed good agreement with the CEUS curves. ICA has the potential to separate the intravascular component from DCE-MRI. This could eliminate the requirement for contrast medium uptake measurements in a major artery and potentially result in more accurate pharmacokinetic parameters. (orig.)

[en] MRI screening of high-risk patients for breast cancer provides very high sensitivity, but with a high recall rate and negative biopsies. Comparing the current exam to prior exams reduces the number of follow-up procedures requested by radiologists. Such comparison, however, can be challenging due to the highly deformable nature of breast tissues. Automated co-registration of multiple scans has the potential to aid diagnosis by providing 3D images for side-by-side comparison and also for use in CAD systems. Although many deformable registration techniques exist, they generally have a large number of parameters that need to be optimized and validated for each new application. Here, we propose a framework for such optimization and also identify the optimal input parameter set for registration of 3D T₁-weighted MRI of breast using Elastix, a widely used and freely available registration tool. A numerical simulation study was first conducted to model the breast tissue and its deformation through finite element (FE) modeling. This model generated the ground truth for evaluating the registration accuracy by providing the deformation of each voxel in the breast volume. An exhaustive search was performed over various values of 7 registration parameters (4050 different combinations of parameters were assessed) and the optimum parameter set was determined. This study showed that there was a large variation in the registration accuracy of different parameter sets ranging from 0.29 mm to 2.50 mm in median registration error and 3.71 mm to 8.90 mm in 95 percentile of the registration error. Mean registration errors of 0.32 mm, 0.29 mm, and 0.30 mm and 95 percentile errors of 3.71 mm, 5.02 mm, and 4.70 mm were obtained by the three best parameter sets. The optimal parameter set was applied to consecutive breast MRI scans of 13 patients. A radiologist identified 113 landmark pairs (~ 11 per patient) which were used to assess registration accuracy. The results demonstrated that using the optimal registration parameter set, a registration accuracy (in mm) of 3.4 [1.8 6.8] was achieved.

[en] Along the years INO has been involved in development of various uncooled infrared devices. Todays, the infrared imagers exhibit good resolutions and find their niche in numerous applications. Nevertheless, there is still a trend toward high resolution imaging for demanding applications. At the same time, low-resolution for mass market applications are sought for low-cost imaging solutions. These two opposite requirements reflect the evolution of infrared cameras from the origin, when only few pixel-count FPAs were available, to megapixel-count FPA of the recent years. This paper reviews the evolution of infrared camera technologies at INO from the uncooled bolometer detector capability up to the recent achievement of 1280x960 pixels infrared camera core using INO's patented microscan technology.

[en] The interior of cell is crowded with various kinds of macromolecules, and proteins are designed to function under crowding environment. However, experimental studies showing the direct evidence of the effect of macromolecular crowding environment on the structures of proteins seems to be insufficient. Then, by the complementally use of both X-ray and neutron scattering methods, we have studied the effect of macromolecular crowding on both the structure and the hydration-shell of myoglobin. The neutral co-solute, polyvinylpyrrolidone (PVP, 40 k Dalton) was used to mimic the crowding environment of cell. The compression of the maximum dimension and the radius of gyration of myoglobin by the presence of PVP were observed. These changes are reasonably explained by the theoretical scattering function simulation based on the preferential exclusion model accompanying a collapse of hydration-shell of the protein. The present results suggest the possibility that the crowding environment by high molecular-weight neutral co-solutes would be non-ideal and different from small molecular crowding such as sugars and polyols.

[en] Breast MRI is frequently performed prior to breast conserving surgery in order to assess the location and extent of the lesion. Ideally, the surgeon should also be able to use the image information during surgery to guide the excision and this requires that the MR image is co-registered to conform to the patient’s position on the operating table. Recent progress in MR imaging techniques has made it possible to obtain high quality images of the patient in the supine position which significantly reduces the complexity of the registration task. Surface markers placed on the breast during imaging can be located during surgery using an external tracking device and this information can be used to co-register the images to the patient. There remains the problem that in most clinical MR scanners the arm of the patient has to be placed parallel to the body whereas the arm is placed perpendicular to the patient during surgery. The aim of this study is to determine the accuracy of co-registration based on a surface marker approach and, in particular, to determine what effect the difference in a patient’s arm position makes on the accuracy of tumour localization. Obtaining a second MRI of the patient where the patient’s arm is perpendicular to body axes (operating room position) is not possible. Instead we obtain a secondary MRI scan where the patient’s arm is above the patient’s head to validate the registration. Five patients with enhancing lesions ranging from 1.5 to 80 cm"3 in size were imaged using contrast enhanced MRI with their arms in two positions. A thin-plate spline registration scheme was used to match these two configurations. The registration algorithm uses the surface markers only and does not employ the image intensities. Tumour outlines were segmented and centre of mass (COM) displacement and Dice measures of lesion overlap were calculated. The relationship between the number of markers used and the COM-displacement was also studied. The lesion COM-displacements ranged from 0.9  to 9.3 mm and the Dice overlap score ranged from 20% to 80%. The registration procedure took less than 1 min to run on a standard PC. Alignment of pre-surgical supine MR images to the patient using surface markers on the breast for co-registration therefore appears to be feasible. (paper)

[en] A set of quantitative techniques is suggested for assessing SAXS data quality. These are applied in the form of a script, SAXStats, to a test set of 27 proteins, showing that these techniques are more sensitive than manual assessment of data quality. Small-angle X-ray scattering (SAXS) has grown in popularity in recent times with the advent of bright synchrotron X-ray sources, powerful computational resources and algorithms enabling the calculation of increasingly complex models. However, the lack of standardized data-quality metrics presents difficulties for the growing user community in accurately assessing the quality of experimental SAXS data. Here, a series of metrics to quantitatively describe SAXS data in an objective manner using statistical evaluations are defined. These metrics are applied to identify the effects of radiation damage, concentration dependence and interparticle interactions on SAXS data from a set of 27 previously described targets for which high-resolution structures have been determined via X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. The studies show that these metrics are sufficient to characterize SAXS data quality on a small sample set with statistical rigor and sensitivity similar to or better than manual analysis. The development of data-quality analysis strategies such as these initial efforts is needed to enable the accurate and unbiased assessment of SAXS data quality

[en] Purpose: This study was designed to evaluate whether changes in metastatic brain tumors after stereotactic radiosurgery (SRS) can be seen with quantitative MRI early after treatment. Methods and Materials: Using contrast-enhanced MRI, a 3-water-compartment tissue model consisting of intracellular (I), extracellular-extravascular (E), and vascular (V) compartments was used to assess the intra–extracellular water exchange rate constant (k_I_E), efflux rate constant (k_e_p), and water compartment volume fractions (M_0_,_I, M_0_,_E, M_0_,_V). In this prospective study, 19 patients were MRI-scanned before treatment and 1 week and 1 month after SRS. The change in model parameters between the pretreatment and 1-week posttreatment scans was correlated to the change in tumor volume between pretreatment and 1-month posttreatment scans. Results: At 1 week k_I_E differentiated (P<.001) tumors that had partial response from tumors with stable and progressive disease, and a high correlation (R=−0.76, P<.001) was observed between early changes in the k_I_E and tumor volume change 1 month after treatment. Other model parameters had lower correlation (M_0_,_E) or no correlation (k_e_p, M_0_,_V). Conclusions: This is the first study that measured k_I_E early after SRS, and it found that early changes in k_I_E (1 week after treatment) highly correlated with long-term tumor response and could predict the extent of tumor shrinkage at 1 month after SRS.