Search

Background: Magnetic resonance imaging (MRI) is widely used to diagnose subscapularis tendon tears; however, it is difficult to assess the anterosuperior aspect of these tears. Radial-sequence MRI can reveal the fiber components of the anterosuperior aspect, from perpendicular, by overcoming the partial volume effect. We aimed to classify the insertion of subscapularis tendon tears on radial-sequence MRI and determine the effectiveness of radial-sequence MRI for subscapularis tendon tear assessments. Methods: We retrospectively investigated 196 patients (mean age, 66.7 ± 9.0 years; 118 men, 78 women) who underwent 1.5 T MRI before arthroscopic rotator cuff repair. Radial-sequence MRI findings of the anterosuperior aspect insertion of the subscapularis tendon were classified into five grades, and intraoperative findings compared with preoperative conventional MRI and radial-sequence MRI. We calculated sensitivity, specificity, accuracy, and positive and negative predictive values. Interobserver and intraobserver reliability for radial-sequence MRI classification was calculated using kappa (κ). Results: Conventional MRI sensitivity of subscapularis tendon tears was 45.3%; specificity, 95.8%; accuracy, 82.1%; positive predictive value, 80.0%; and negative predictive value, 82.5%. Radial-sequence MRI sensitivity was 92.5%; specificity, 88.1%; accuracy, 89.3%; positive predictive value, 74.2%; and negative predictive value, 96.9%. Sensitivity (P

Purpose Selective internal radiation therapy (SIRT) is a treatment for various kinds of liver tumours by injecting 90 Y bearing microspheres into the liver vessels. To perform meaningful post-treatment dosimetry , quantitative imaging is performed. Methods This work uses a Monte-Carlo based reconstruction software with scatter and attenuation correction and collimator modelling that allows the quantification of 90 Y bremsstrahlung SPECT/CT data. A dataset comprising 17 patients and measurements on a Jaszczak phantom, a NEMA IEC Body phantom and an anthropomorphic liver phantom are analysed and activities and dose values are acquired. These measured values are compared with applied activities and pre-treatment calculations, allowing to assess the quality of the SPECT reconstruction. A detailed uncertainty budget is presented, including uncertainties of the dose calibrator, the count rate, non-included interactions and other factors. Results The applied method is validated by finding measurements repeatable within the given uncertainty, and it is shown the influence of various parameters on the reconstruction process is negligible. Furthermore, activities and doses measured in the phantoms show good agreement with calculated values, if they are corrected for partial volume effects . Conclusions The strict observation of metrological requirements and the creation of an uncertainty budget increase the reliability and traceability of this novel approach to 90Y dosimetry. It gives an example of successful voxel-based dosimetry based on quantitative 90Y SPECT/CT image data.

In this work, the following tasks were solved: to perform a comparative analysis of data processing methods when calculating recovery factors; to evaluate the influence of time-of-flight technology and PSF function on the recovery factor and the forecast of recovery factor deviation for potential pathological foci with a diameter of 6–8 mm; to evaluate the influence of parameters of iterative reconstruction algorithms, Gaussian filter and axial filters on the recovery factor. The calculation of the recovery factors was carried out on the basis of quantitative characteristics obtained in the analysis of reconstructions of images of the IEC phantom with six spheres installed inside and filled with a radiopharmaceutical. Eight series of experiments with background / sphere activity ratios 1/3, 1/4, 1/6, 1/8, 1/12, 1/14, 1/16, 1/20 were carried out with the same concentration of activity in the spheres during each separate experiment. The forecast of the effect of the partial volume effect on lesions with a diameter of 6 to 8 mm was carried out, taking into account the used reconstruction algorithms. It is advisable to use the results obtained to harmonize diagnostic protocols for scanning with positron emission tomographs using the input parameters of reconstruction algorithms and filters, which will minimize the error in the quantitative assessment of a radiopharmaceutical when analyzing the dynamics of the development of a pathological process, as well as the response of pathology to therapy.

Background Multiple post-treatment dosimetry methods are currently under investigation for Yttrium-90 ($$^{90}\hbox {Y}$$ 90 Y ) radioembolization. Within each methodology, a variety of dosimetric inputs exists that affect the final dose estimates. Understanding their effects is essential to facilitating proper dose analysis and crucial in the eventual standardization of radioembolization dosimetry. The purpose of this study is to investigate the dose differences due to different self-calibrations and mass density assignments in the non-compartmental and local deposition methods. A practical mean correction method was introduced that permits dosimetry in images where the quality is compromised by patient motion and partial volume effects. Methods Twenty-one patients underwent $$^{90}\hbox {Y}$$ 90 Y radioembolization and were imaged with SPECT/CT. Five different self-calibrations (FOV, Body, OAR, Liverlung, and Liver) were implemented and dosimetrically compared. The non-compartmental and local deposition method were used to perform dosimetry based on either nominal- or CT calibration-based mass densities. A mean correction method was derived assuming homogeneous densities. Cumulative dose volume histograms, linear regressions, boxplots, and Bland Altman plots were utilized for analysis. Results Up to 270% weighted dose difference was found between self-calibrations with mean dose differences up to 50 Gy in the liver and 23 Gy in the lungs. Between the local deposition and non-compartmental methods, the liver and lung had dose differences within 0.71 Gy and 20 Gy, respectively. The local deposition method’s nominal and CT calibration-based mass density implementations dosimetric metrics were within 1.4% in the liver and 24% in the lungs. The mean lung doses calculated with the CT method were shown to be inflated. The mean correction method demonstrated that the corrected mean doses were greater by up to $$\sim 5$$ ∼ 5 Gy in the liver and lower by up to $$\sim 12$$ ∼ 12 Gy in the lungs. Conclusions The OAR calibration may be utilized as a potentially more accurate and precise self-calibration. The non-compartmental method was found more comparable to the local deposition method in organs that were more homogeneous in mass densities. Due to the potential for inflated lung mean doses, the non-compartmental and local deposition method implemented with nominal mass densities is recommended for more consistent dosimetric results. If patient motion and partial volume effects are present in the liver, our practical correction method will calculate more representative doses in images suboptimal for dosimetry.

Purpose The aims of this study were to develop and apply a method to correct for the differences in partial volume effects of pre-therapy Technetium-99 m (99mTc)-MAA SPECT and post-therapy Yttrium-90 (90Y) bremsstrahlung SPECT imaging in selective internal radiation therapy, and to use this method to improve quantitative comparison of predicted and delivered 90Y absorbed doses. Methods The spatial resolution of 99mTc SPECT data was converted to that of 90Y SPECT data using a function calculated from 99mTc and 90Y point spread functions. This resolution conversion method (RCM) was first applied to 99mTc and 90Y SPECT phantom data to validate the method, and then to clinical data to assess the power of 99mTc SPECT imaging to predict the therapeutic absorbed dose. Results The maximum difference between absorbed doses to phantom spheres was 178%. This was reduced to 27% after the RCM was applied. The clinical data demonstrated differences within 38% for mean absorbed doses delivered to the normal liver, which were reduced to 20% after application of the RCM. Analysis of clinical data showed that therapeutic absorbed doses delivered to tumours greater than 100 cm3 were predicted to within 52%, although there were differences of up to 210% for smaller tumours, even after the RCM was applied. Conclusions The RCM was successfully verified using phantom data. Analysis of the clinical data established that the 99mTc pre-therapy imaging was predictive of the 90Y absorbed dose to the normal liver to within 20%, but had poor predictability for tumours smaller than 100 cm3.

Producción Científica, To accurately estimate the partial volume fraction of free water in the white matter from diffusion MRI acquisitions not demanding strong sensitizing gradients and/or large collections of different b-values. Data sets considered comprise~32- 64 gradients near b =1000 s/mm2 plus~6 gradients near b =500 s/mm2.Theory and Methods: The spherical means of each diffusion MRI set with the same b- value are computed. These means are related to the inherent diffusion parameters within the voxel (free- and cellular- water fractions; cellular- water diffusivity), which are solved by constrained nonlinear least squares regression.Results: The proposed method outperforms those based on mixtures of two Gaussians for the kind of data sets considered. W.r.t. the accuracy, the former does not introduce significant biases in the scenarios of interest, while the latter can reach a bias of 5%– 7% if fiber crossings are present. W.r.t. the precision, a variance near 10%, compared to 15%, can be attained for usual configurations.Conclusion: It is possible to compute reliable estimates of the free- water fraction inside the white matter by complementing typical DTI acquisitions with few gradients at a lowb- value. It can be done voxel- by- voxel, without imposing spatial regularity constraints., Ministerio de Ciencia e Innovación, (grant RTI2018- 094569- B- I00)

Purpose We propose a new method, displacement spectrum (DiSpect) imaging, for probing in vivo complex tissue dynamics such as motion, flow, diffusion, and perfusion. Based on stimulated echoes and image phase, our flexible approach enables observations of the spin dynamics over short (milliseconds) to long (seconds) evolution times. Methods The DiSpect method is a Fourier-encoded variant of displacement encoding with stimulated echoes, which encodes bulk displacement of spins that occurs between tagging and imaging in the image phase. However, this method fails to capture partial volume effects as well as blood flow. The DiSpect variant mitigates this by performing multiple scans with increasing displacement-encoding steps. Fourier analysis can then resolve the multidimensional spectrum of displacements that spins exhibit over the mixing time. In addition, repeated imaging following tagging can capture dynamic displacement spectra with increasing mixing times. Results We demonstrate properties of DiSpect MRI using flow phantom experiments as well as in vivo brain scans. Specifically, the ability of DiSpect to perform retrospective vessel-selective perfusion imaging at multiple mixing times is highlighted. Conclusion The DiSpect variant is a new tool in the arsenal of MRI techniques for probing complex tissue dynamics. The flexibility and the rich information it provides open the possibility of alternative ways to quantitatively measure numerous complex spin dynamics, such as flow and perfusion within a single exam.

Introduction The assessment of ex vivo biodistribution is the preferred method for quantification of radiotracers biodistribution in preclinical models, but is not in line with current ethics on animal research. PET imaging allows for noninvasive longitudinal evaluation of tracer distribution in the same animals, but systemic comparison with ex vivo biodistribution is lacking. Our aim was to evaluate the potential of preclinical PET imaging for accurate tracer quantification, especially in tumor models. Methods NEMA NU 4-2008 phantoms were filled with 11C, 68Ga, 18F, or 89Zr solutions and scanned in Mediso nanoPET/CT and PET/MR scanners until decay. N87 tumor-bearing mice were i.v. injected with either [18F]FDG (~ 14 MBq), kept 50 min under anesthesia followed by imaging for 20 min, or with [89Zr]Zr-DFO-NCS-trastuzumab (~ 5 MBq) and imaged 3 days post-injection for 45 min. After PET acquisition, animals were killed and organs of interest were collected and measured in a γ-counter to determine tracer uptake levels. PET data were reconstructed using TeraTomo reconstruction algorithm with attenuation and scatter correction and regions of interest were drawn using Vivoquant software. PET imaging and ex vivo biodistribution were compared using Bland–Altman plots. Results In phantoms, the highest recovery coefficient, thus the smallest partial volume effect, was obtained with 18F for both PET/CT and PET/MR. Recovery was slightly lower for 11C and 89Zr, while the lowest recovery was obtained with 68Ga in both scanners. In vivo, tumor uptake of the 18F- or 89Zr-labeled tracer proved to be similar irrespective whether quantified by either PET/CT and PET/MR or ex vivo biodistribution with average PET/ex vivo ratios of 0.8–0.9 and a deviation of 10% or less. Both methods appeared less congruent in the quantification of tracer uptake in healthy organs such as brain, kidney, and liver, and depended on the organ evaluated and the radionuclide used. Conclusions Our study suggests that PET quantification of 18F- and 89Zr-labeled tracers is reliable for the evaluation of tumor uptake in preclinical models and a valuable alternative technique for ex vivo biodistribution. However, PET and ex vivo quantification require fully described experimental and analytical procedures for reliability and reproducibility.

To compare aortic sac changes after endovascular aneurysm repair (EVAR) assessed by three-dimensional ultrasound (3D-US), two-dimensional ultrasound (2D-US), and traditional computed tomographic angiography (CTA).Using volume assessment with three-dimensional CTA (3D-CTA-volume) as the gold standard, this study investigated aortic sac changes at three and 12 months after EVAR with three different ultrasound methods (2D-US anterior-posterior (AP) diameter, 3D-US AP centerline diameter, and 3D-US partial volume), and traditional CT multiplanar outer-to-outer diameter (CT-MPR OTO diameter). From august 1st, 2011 to January 2014, consecutive EVAR patients (n = 113) were available for analysis in two time intervals; 1) between preoperative and three-month follow-up and 2) between three and 12 month follow-up.The risk of missing true aortic sac growth (false negative finding) at three-month postoperative visit using 3D-US partial volume, 3D-US AP centerline diameter, 2D-US AP diameter, and CT-MPR OTO diameter was 19%, 21%, 22%, and 18%, respectively. Corresponding low sensitivities (0% to 21%) and kappa-values (0.50) in detecting aortic sac changes were found. The risk of missing true growth between three and 12 months were lower (6%, 5%, 6%, and 6%, respectively), and matching sensitivities 33%, 33%, 17%, and 17%, respectively.All tested methods for aortic sac changes were as good as traditional CT-MPR OTO diameter and corresponded poorly with 3D-CTA-volume at three months postoperative visit but substantially better after 12 months where the residual sac change was more profound.

PURPOSE A pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data is subject to inaccuracy and instability partly owing to the partial volume effect (PVE). We proposed a new multicompartment model for a tissue-specific pharmacokinetic analysis in DCE-MRI data to solve the PVE problem and to provide better kinetic parameter maps. METHODS We introduced an independent parameter named fractional volumes of tissue compartments in each DCE-MRI pixel to construct a new linear separable multicompartment model, which simultaneously estimates the pixel-wise time-concentration curves and fractional volumes without the need of the pure-pixel assumption. This simplified convex optimization model was solved using a special type of non-negative matrix factorization (NMF) algorithm called the minimum-volume constraint NMF (MVC-NMF). RESULTS To test the model, synthetic datasets were established based on the general pharmacokinetic parameters. On well-designed synthetic data, the proposed model reached lower bias and lower root mean square fitting error compared to the state-of-the-art algorithm in different noise levels. In addition, the real dataset from QIN-BREAST-DCE-MRI was analyzed, and we observed an improved pharmacokinetic parameter estimation to distinguish the treatment response to chemotherapy applied to breast cancer. CONCLUSION Our model improved the accuracy and stability of the tissue-specific estimation of the fractional volumes and kinetic parameters in DCE-MRI data, and improved the robustness to noise, providing more accurate kinetics for more precise prognosis and therapeutic response evaluation using DCE-MRI.

Segmentation of brain tumors is important for medical diagnosis, treatment planning, and disease development. However, the presence of image artifacts such as noise, intensity inhomogeneity, and partial volume effect in real-world images can aggressively affect the segmentation task. The manual segmentation of the tumor is highly error-prone and is a time-consuming task. Hence, in this work, we propose a methodology that can identify and segment the brain tumor slices in magnetic resonance (MRI) images. The work is composed of three main stages namely pre-processing, segmentation, and post-processing. In the pre-processing stage, N4ITK is applied to correct the intensity inhomogeneity and an Anisotropic diffusion filter is used to remove the noise present in MR images. In the segmentation stage, an active contour model that combines the region scalable fitting energy (RSF) and optimized laplacian of gaussian energy (OLoG) is proposed to segment the tumor region from MRI. The proposed segmentation method first presents an LoG energy term optimized by an energy functional that can smooth the homogeneous regions and enhance edge information simultaneously. Next, the optimized LoG energy term is combined with the RSF energy term which utilizes the local region information to drive the curve towards the boundaries. With the addition of the LoG term, the proposed model is insensitive to the positions of the initial contour and produces an accurate segmentation result. Finally, morphological operations and thresholding are used to extract the tumor region from the segmented image which is computed previously. The performance of the proposed segmentation method is evaluated using the BRATS, and J.Cheng dataset. The obtained experimental results demonstrate that our proposed method significantly outperforms the manual process and state of the art methods in brain tumor segmentation.

Purpose This study aims to provide a detailed investigation on the noise penalization factor in Bayesian penalized likelihood (BPL)‐based algorithm, with the utilization of partial volume effect correction (PVC), so as to offer the suitable beta value and optimum standardized uptake value (SUV) parameters in clinical practice for small pulmonary nodules. Methods A National Electrical Manufacturers Association (NEMA) image‐quality phantom was scanned and images were reconstructed using BPL with beta values ranged from 100 to 1000. The recovery coefficient (RC), contrast recovery (CR), and background variability (BV) were measured to assess the quantification accuracy and image quality. In the clinical assessment, lesions were categorized into sub‐centimeter (

Magnetic resonance imaging (MRI) of the right ventricle (RV) offers important diagnostic information, but the accuracy of this information is hampered by the complex geometry of the RV. Here, we propose a novel postprocessing algorithm that corrects for partial-volume effects in the analysis of standard MRI cine images of RV mass (RVm) and evaluate the method in clinical and preclinical data. Self-corrected RVm measurement was compared with conventionally measured RVm in 16 patients who showed different clinical indications for cardiac MRI and in 17 Wistar rats with different degrees of pulmonary congestion. The rats were studied under isoflurane anaesthesia. To evaluate the reliability of the proposed method, the measured end-systolic and end-diastolic RVm were compared. Accuracy was evaluated by comparing preclinical RVm to ex vivo RV weight (RVw). We found that use of the self-correcting algorithm improved reliability compared with conventional segmentation. For clinical data, the limits of agreement (LOAs) were -1.8 ± 8.6g (self-correcting) vs. 5.8 ± 7.8g (conventional), and coefficients of variation (CoVs) were 7.0% (self-correcting) vs. 14.3% (conventional). For preclinical data, LOAs were 21 ± 46 mg (self-correcting) vs. 64 ± 89 mg (conventional), and CoVs were 9.0% (self-correcting) and 17.4% (conventional). Self-corrected RVm also showed better correspondence with the ex vivo RVw: LOAs were -5 ± 80 mg (self-correcting) vs. 94 ± 116 mg (conventional) in end-diastole and -26 ± 74 mg (self-correcting) vs. 31 ± 98 mg (conventional) in end-systole. The new self-correcting algorithm improves the reliability and accuracy of RVm measurements in both clinical and preclinical MRI. It is simple and easy to implement and does not require any additional MRI data.

18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) estimate brain activities from different aspects, including regional glucose uptake (rGU) by 18FDG-PET, regional cerebral blood flow (rCBF) by arterial spin labeling, and dynamic changes of deoxyhemoglobin by blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI). However, the relationships between them remain incompletely understood. In the current study, twenty-four subjects (14 males, 10 females) were recruited and investigated the correlation among rGU, rCBF, and BOLD fMRI-derived metrics reflecting the neural activity, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) by hybrid PET/fMRI. Correlation analyses were performed across subject and across space at both voxel level and region level, considering partial volume effects by adjusting for gray matter volume. Each pair of metrics showed significant across-space correlations. rGU against ReHo showed the highest mean correlation coefficients. rGU had higher correlations with three resting-state (RS) fMRI metrics than did ASL-rCBF. However, the across-subject correlations were not significant among functional modalities (rGU, rCBF, and RS-fMRI BOLD data) at either voxel level or region level even with a liberal threshold, except for significant across-subject correlation between RS-fMRI metrics (ALFF, ReHo, and DC). These comprehensive findings from hybrid PET/MR might provide complementary information to reveal the underlying mechanisms of the brain activity and open new perspective to interpret pathologic conditions.

Kawa Abdulla Mahmood, Rezheen Jamal Rashid, Salah Mohammed Fateh, Naser Abdullah Mohammed University of Sulaimani, College of Medicine, Department of Surgery-Diagnostic Imaging Unit, Sulaymaniyah, Kurdistan Region, IraqCorrespondence: Kawa Abdulla Mahmood Tel +9647701545538Email kawa.mahmood@univsul.edu.iqPurpose: To estimate the role of patient preparation using castor oil on the ADC value of focal liver lesion.Patients and Methods: Retrospective case-control study over more than two years. Magnetic resonance imaging (MRI) scan, including diffusion-weighted imaging (DWI) of the upper abdomen performed for 87 cases and 71 controls in patients with focal hepatic hemangiomas. Cases were prepared using castor oil prior to the scan without identifiable unwanted effect, while controls did not receive any special preparation. Since liver hemangioma is a common lesion, it was selected and used as a sample. Apparent Diffusion Coefficient (ADC) values of focal liver lesion were calculated in cases and controls.Results: The mean ADC value of liver hemangioma was lower in cases compared to controls; the mean ADC value was (2.21± 0.39x10ˉ3mm2/s) in cases and (2.51± 0.49x10ˉ3mm2/s) in controls. Left lobes were more affected by lesions; the mean ADC value of the left lobe lesions was (2.26± 0.37 x10ˉ3mm2/s) and (2.86± 0.43 x10ˉ3mm2/s) in cases and controls, respectively. The ADC value of lesions in the right lobe was (2.19± 0.39x10ˉ3mm2/s) in cases and (2.39± 0.45x10ˉ3mm2/s) in controls. There was a significant segmental ADC variation; lesions at segments II, III, IVb, and V demonstrated illusive ADC elevation in controls.Conclusion: There is erroneous elevation of lobar and segmental ADC value of liver hemangiomas in non prepared patients. This Potential source of error (peristalsis, partial volume, and paramagnetic gas effect of gastrointestinal tract) on hepatic lesions’ ADC value can be avoided by proper preparation using castor oil prior to MRI scanning.Keywords: liver hemangioma, apparent diffusion coefficient value, patient preparation, castor oil

The fornix is the primary efferent pathway of the hippocampus and plays a central role in memory circuitry. Diffusion tensor imaging has shown changes in the fornix with typical development and aging. Here, the fornix was investigated in 903 healthy young adult participants aged 22–36 years old from the high-spatial resolution 1.25 mm isotropic Human Connectome Project (HCP) diffusion dataset. Manual deterministic tractography was used to assess relationships between fornix diffusion parameters and age, sex, laterality, hippocampus volume, memory scores, and genetic effects in a subgroup of mono- and dizygotic twins. Fornix diffusion metrics were weakly correlated with age over the given age span. While significant hemispheric and sex differences were observed (greater fractional anisotropy (FA) and volume in the right hemisphere; greater FA and volume in females), there was great overlap between the groups. Hippocampus volume measurements showed greater volume in the right hemisphere, were found to be larger in males, and were weakly correlated with fornix FA and volume. Interestingly, all fornix diffusion measurements correlated strongly with fornix volume, suggesting the presence of partial volume effects despite the high-spatial resolution of the data. Both fornix diffusion parameters and hippocampal volumes were able to explain some variance (0.6–5.5%) in the memory tests evaluated. The fornix diffusion parameters were influenced by both genetic and shared environmental factors, displaying greater variability in dizygotic than in monozygotic twins. These findings provide a comprehensive depiction of the fornix in healthy, young individuals, upon which future typical development/aging and pathological studies could anchor.

PURPOSE Our purpose was to assess our proposed new synthetic MRI (synMRI) technique, combined with T2-based water suppression (T2wsup), to reduce cerebral spinal fluid (CSF)-partial volume effects (PVEs). These PVEs are problematic in the T2-weighted fluid-attenuation inversion recovery (FLAIR) images obtained by conventional synMRI techniques. METHODS Our T2wsup was achieved by subtracting additionally acquired long TE spin echo (SE) images of water signals dominant from the originally acquired images after T2 decay correction and a masking on the long TE image using the water volume (Vw) map to preserve tissue SNR, followed by quantitative mapping and then calculation of the synthetic images. A simulation study based on a two-compartment model including tissue and water in a voxel and a volunteer MR study were performed to assess our proposed method. Parameters of long TE and a threshold value in the masking were assessed and optimized experimentally. Quantitative parameter maps of standard and with T2wsup were generated, then wsup-synthetic FLAIR and SE images were calculated using those suitable combinations and compared. RESULTS Our simulation clarified that the CSF-PVE artifacts in the standard synthetic FLAIR increase T2 as the water volume increases in a voxel, and the volunteer MR brain study demonstrated that the hyperintense artifacts on synthetic images were reduced to

Purpose The human cerebellum plays an important role in the functional activity of the cerebrum, ranging from motor to cognitive systems given its relaying role between the spinal cord and cerebrum. The cerebellum poses many challenges to Magnetic Resonance Spectroscopic Imaging (MRSI) due to its caudal location, susceptibility to physiological artifacts, and partial volume artifacts resulting from its complex anatomical structure. Thus, in the present study, we propose a high-resolution MRSI acquisition scheme for the cerebellum. Methods A zoom or reduced field of view (rFOV) metabolite-cycled MRSI acquisition at 3 Tesla, with a grid of 48 × 48, was developed to achieve a nominal resolution of 62.5 μL. Single-slice rFOV MRSI data were acquired from the cerebellum of 5 healthy subjects with a nominal resolution of 2.5 × 2.5 × 10 mm3 in 9.6 min. Spectra were quantified using the LCModel package. A spatially unbiased atlas template of the cerebellum was used to analyze metabolite distributions in the cerebellum. Results The superior quality of the achieved spectra-enabled generation of high-resolution metabolic maps of total N-acetylaspartate, total Creatine (tCr), total Choline (tCho), glutamate+glutamine, and myo-inositol, with Cramér-Rao lower bounds below 50%. A template-based regions of interest (ROI) analysis resulted in spatially dependent metabolite distributions in 9 ROIs. The group-averaged high-resolution metabolite maps across subjects increased the contrast-to-noise ratio between cerebellum regions. Conclusion These findings indicate that very high-resolution metabolite probing of the cerebellum is feasible using rFOV or zoomed MRSI at 3 Tesla.

Purpose To develop a rapid T2 mapping protocol using optimized spiral acquisition, accelerated reconstruction, and model fitting. Materials and methods A T2-prepared stack-of-spiral gradient echo (GRE) pulse sequence was applied. A model-based approach joined with compressed sensing was compared with the two methods applied separately for accelerated reconstruction and T2 mapping. A 2-parameter-weighted fitting method was compared with 2- or 3-parameter models for accurate T2 estimation under the influences of noise and B1 inhomogeneity. The performance was evaluated using both digital phantoms and healthy volunteers. Mitigating partial voluming with cerebrospinal fluid (CSF) was also tested. Results Simulations demonstrates that the 2-parameter-weighted fitting approach was robust to a large range of B1 scales and SNR levels. With an in-plane acceleration factor of 5, the model-based compressed sensing-incorporated method yielded around 8% normalized errors compared to references. The T2 estimation with and without CSF nulling was consistent with literature values. Conclusion This work demonstrated the feasibility of a T2 quantification technique with 3D high-resolution and whole-brain coverage in 2–3 min. The proposed iterative reconstruction method, which utilized the model consistency, data consistency and spatial sparsity jointly, provided reasonable T2 estimation. The technique also allowed mitigation of CSF partial volume effect.

Cortical bone and its microstructure are crucial for bone strength, especially at the long bone diaphysis. However, it is still not well‐defined how imaging procedures can be used as predictive tools for mechanical bone properties. This study evaluated the capability of several high‐resolution imaging techniques to capture cortical bone morphology and assessed the correlation with the bone's mechanical properties. The microstructural properties (cortical thickness [Ct.Th], porosity [Ct.Po], area [Ct.Ar]) of 11 female tibial diaphysis (40–90 years) were evaluated by dual‐energy X‐ray absorptiometry (DXA), high‐resolution peripheral‐quantitative‐computed‐tomography (HR‐pQCT), micro‐CT (μCT) and histomorphometry. Stiffness and maximal torque to failure were determined by mechanical testing. T‐Scores determined by DXA ranged from 0.6 to −5.6 and a lower T‐Score was associated with a decrease in Ct.Th (p ≤ 0.001) while the Ct.Po (p ≤ 0.007) increased, and this relationship was independent of the imaging method. With decreasing T‐Score, histology showed an increase in Ct.Po from the endosteal to the periosteal side (p = 0.001) and an exponential increase in the ratio of osteons at rest to those after remodelling. However, compared to histomorphometry, HR‐pQCT and μCT underestimated Ct.Po and Ct.Th. A lower T‐Score was also associated with significantly reduced stiffness (p = 0.031) and maximal torque (p = 0.006). Improving the accuracy of Ct.Po and Ct.Th did not improve prediction of the mechanical properties, which was most closely related to geometry (Ct.Ar). The ex‐vivo evaluation of mechanical properties correlated with all imaging modalities, with Ct.Th and Ct.Po highly correlated with the T‐Score of the tibial diaphysis. Cortical microstructural changes were underestimated with the lower resolution of HR‐pQCT and μCT compared to the histological ‘gold standard’. The increased accuracy did not result in an improved prediction for local bone strength in this study, which however might be related to the limited number of specimens and thus needs to be evaluated in a larger collective., Cortical bone loss has been identified as a main source of osteoporotic and age‐related bone substance loss and fracture risk. In this study, we evaluated the cortical microstructural properties of tibias with different imaging modalities (dual‐energy X‐ray absorptiometry [DXA], high‐resolution peripheral‐quantitative‐computed‐tomography [HR‐pQCT], micro‐CT [μCT] and histomorphometry) and directly compared them to their biomechanical properties. Notably, cortical parameters and especially Cortical Porosity (Co.Po) were underestimated with high‐resolution imaging CT compared to the ‘gold standard’ histology which in turn also allowed evaluation of osteonal remodeling activity. However, the improved analysis of cortical thickness and porosity did not result in an improvement in bone strength prediction. Cortical area still translated better into local bone strength indicating size and shape in a single parameter due to the simplicity of the geometry at this skeletal site.

Purpose Intratumoral dose response can be detected using serial fluoro-2-deoxyglucose-(FDG) positron emission tomography (PET)/computed tomography (CT) imaging feedback during treatment and used to guide adaptive dose painting by number (DPbN). However, to reliably implement this technique, the effect of uncertainties in quantitative PET/CT imaging feedback on tumor voxel dose-response assessment and DPbN needs to be determined and reduced. Methods Three major uncertainties, induced by (a) PET imaging partial volume effect (PVE) and (b) tumor deformable image registration (DIR), and (c) variation of the time interval between FDG injection and PET image acquisition (TI), were determined using serial FDG-PET/CT images acquired during chemoradiotherapy of 18 head and neck cancer patients. PET imaging PVE was simulated using the discrepancy between with and without iterative deconvolution-based PVE corrections. Effect of tumor DIR uncertainty was simulated using the discrepancy between two DIR algorithms, including one with and one without soft-tissue mechanical correction for the voxel displacement. The effect of TI variation was simulated using linear interpolation on the dual-point PET/CT images. Tumor voxel pretreatment metabolic activity (SUV0 ) and dose-response matrix (DRM) discrepancies induced by each of the three uncertainties were quantified, respectively. Adverse effects of tumor voxel SUV0 and DRM discrepancies on tumor control probability (TCP) in DPbN were assessed. Results Partial volume effect and TI variations of 10 mins induced a mean ± standard deviation (SD) of tumor voxel SUV0 discrepancies to be -0.7% ± 9.2% and 0% ± 4.8%, respectively. Tumor voxel DRM discrepancies induced by PVE, tumor DIR discrepancy, and TI variations were 0.6% ± 8.9%, 1.7% ± 9.1%, and 0% ± 7%, respectively. Partial volume effect induced SUV0 and DRM discrepancies correlated significantly with the tumor shape and FDG uptake heterogeneity. Tumor DIR uncertainty-induced DRM discrepancy correlated significantly with the tumor volume and shrinkage during treatment. Among the three uncertainties, PVE dominated the adverse effects on the TCP, with a mean ± SD of TCP reduction to be 12.7% ± 9.8% for all tumors if no compensation was applied for. Conclusions Effect of uncertainties in quantitative FDG-PET/CT imaging feedback on intratumoral dose-response quantification was not negligible. These uncertainties primarily caused by PVE and tumor DIR were highly dependent on individual tumor shape, volume, shrinkage during treatment, and pretreatment SUV heterogeneity, which can be managed individually. The adverse effects of these uncertainties could be minimized by using proper PVE corrections and DIR methods and compensated for in the clinical implementation of DPbN.

Segmentation of spine Magnetic Resonance Images (MRIs) has become an indispensable process in the diagnosis of lumbar disc degeneration, causing low back pain. Over the last decade of years, computer-directed diagnosis of disease, as well as computer-guided spine surgery, is based on the two-dimensional (2D) analysis of mid-sagittal slice of MRI. This work proposes an automatic strategy to extract the 3D segmentation of the normal disc as well as degenerated lumbar intervertebral discs (IVDs) from T2-weighted Turbo Spin Echo MRI of the spine using Connected Component (CC) analysis algorithm and statistical shape analysis. The challenges faced by the IVD segmentation includes (i) partial volume effects (ii) intensity inhomogeneity (iii) grey level overlap of different soft tissues. The proposed method first pre-processes the dataset and enables it for the application of the CC algorithm. The CC (subsets of pixels of the disc) of the spine MRI is extracted and apply statistical shape analysis for the refinement of the segmentation results to detect IVDs. Experimental results of the proposed method show a robust segmentation, accomplishing the dice similarity index of 92.4% and thus achieving a low error rate. Other performance measures such as Precision, Accuracy, JaccardIdx, JaccardDist, Global Consistency Error, Variation of Information, etc were also evaluated. The algorithm is evaluated quantitatively using adequate experiments on a dataset of 15 MRI scans, of different scenarios such as healthy and degenerate disc and this proposed method is verified as a promising accurate method for the automatic segmentation of IVD.

Purpose: Pseudocontinuous arterial spin labeling (pCASL) allows for noninvasive measurement of regional cerebral blood flow (CBF), which has the potential to serve as biomarker for neurodegenerative and cardiovascular diseases. This work aimed to implement and validate pCASL on the dedicated MRI system within the population-based Rotterdam Study, which was installed in 2005 and for which software and hardware configurations have remained fixed. Methods: Imaging was performed on two 1.5T MRI systems (General Electric); (I) the Rotterdam Study system, and (II) a hospital-based system with a product pCASL sequence. An in-house implementation of pCASL was created on scanner I. A flow phantom and three healthy volunteers (