Representative Regions Of Interest Research Articles

Analysis of respiratory-induced motion trajectories of individual liver segments in patients with hepatocellular carcinoma.

To analyze the respiratory-induced motion trajectories of each liver segment for hepatocellular carcinoma (HCC) to derive a more accurate internal margin and optimize treatment protocol selection. Ten-phase-gated four-dimensional computed tomography (4DCT) scans of 14 patients with HCC were analyzed. For each patient, eight representative regions of interest (ROI) were delineated on each liver segment in all 10 phases. The coordinates of the center of gravity of each ROI were obtained for each phase, and then the respiratory motion in the left-right (LR), anteroposterior (AP), and craniocaudal (CC) directions was analyzed. Two sets of motion in each direction were also compared in terms of only two extreme phases and all 10 phases. Motion of less than 5mm was detected in 12 (86%) and 10 patients (71%) in the LR and AP directions, respectively, while none in the CC direction. Motion was largest in the CC direction with a maximal value of 19.5mm, with significant differences between liver segment 7 (S7) and other segments: S1 (p<0.036), S2 (p<0.041), S3 (p<0.016), S4 (p<0.041), and S5 (p<0.027). Of the 112 segments, hysteresis>1mm was observed in 4 (4%), 2 (2%), and 15 (13%) in the LR, AP, and CC directions, respectively, with a maximal value of 5.0mm in the CC direction. A significant amount of respiratory motion was detected in the CC direction, especially in S7, and S8. Despite the small effect of hysteresis, it can be observed specifically in the right lobe. Therefore, caution is required when using 4DCT to determine IM using only end-inspiration and end-expiration. Understanding the respiratory motion in individual liver segments can be helpful when selecting an appropriate treatment protocol.

Deep learning-based predictive model for pathological complete response to neoadjuvant chemotherapy in breast cancer from biopsy pathological images: a multicenter study.

Introduction: Early predictive pathological complete response (pCR) is beneficial for optimizing neoadjuvant chemotherapy (NAC) strategies for breast cancer. The hematoxylin and eosin (HE)-stained slices of biopsy tissues contain a large amount of information on tumor epithelial cells and stromal. The fusion of pathological image features and clinicopathological features is expected to build a model to predict pCR of NAC in breast cancer. Methods: We retrospectively collected a total of 440 breast cancer patients from three hospitals who underwent NAC. HE-stained slices of biopsy tissues were scanned to form whole-slide images (WSIs), and pathological images of representative regions of interest (ROI) of each WSI were selected at different magnifications. Based on several different deep learning models, we propose a novel feature extraction method on pathological images with different magnifications. Further, fused with clinicopathological features, a multimodal breast cancer NAC pCR prediction model based on a support vector machine (SVM) classifier was developed and validated with two additional validation cohorts (VCs). Results: Through experimental validation of several different deep learning models, we found that the breast cancer pCR prediction model based on the SVM classifier, which uses the VGG16 model for feature extraction of pathological images at ×20 magnification, has the best prediction efficacy. The area under the curve (AUC) of deep learning pathological model (DPM) were 0.79, 0.73, and 0.71 for TC, VC1, and VC2, respectively, all of which exceeded 0.70. The AUCs of clinical model (CM), a clinical prediction model established by using clinicopathological features, were 0.79 for TC, 0.73 for VC1, and 0.71 for VC2, respectively. The multimodal deep learning clinicopathological model (DPCM) established by fusing pathological images and clinicopathological features improved the AUC of TC from 0.79 to 0.84. The AUC of VC2 improved from 0.71 to 0.78. Conclusion: Our study reveals that pathological images of HE-stained slices of pre-NAC biopsy tissues can be used to build a pCR prediction model. Combining pathological images and clinicopathological features can further enhance the predictive efficacy of the model.

EOMES+ Tr1-like Cells Are Enriched in Areas of NLPHL Group II (Patterns D to F) Supporting the Role of Tregs in Disease Recurrence/Progression

Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) is a rare lymphoma subtype characterized by proliferation of lymphocyte-predominant (LP) cells associated with a distinct tumor microenvironment. Six major histopathological growth patterns (A to F) have been described by Fan and colls., based on the cellular composition of the tumor microenvironment and its relationship with the LP cells. Group I (patterns A to C) is comprised of nodules rich in small B-cells and follicular dendritic cells and have been associated with low-risk of disease recurrence/progression, while group II (patterns D to F) is rich in small T-cells, lack follicular dendritic cells and have a higher risk of disease recurrence/progression. Although multiple studies have characterized the tumor microenvironment and its relationship with tumor biology in classic Hodgkin lymphoma and other lymphoma types, these studies are limited for NLPHL. Regulatory T-cells (Tregs), a highly immunosuppressive subset of CD4+ T cells, represent a key cellular player in the tumor microenvironment by limiting antitumor immune responses. Emerging studies suggest substantial heterogeneity in the immunophenotype and suppressive capacities of Tregs. For example, classic Tregs are positive for CD4, CD25 and FOXP3; however, a highly immunosuppressive subset of Tregs, named Tr1-like cells has been recently identified and characterized by a distinctive immunophenotype (CD4+, EOMES+, GZMK+ but Foxp3- CD25-) and distinct cytokine expression. Tr1-like are highly relevant in cancer because they seem to be clonally expanded in solid tumors and its presence and number correlates with disease progression (Bonnal et al. Nat Immunol, 2021). Here, we aimed to investigate the Tregs composition (classic and EOMES+ Tr1-like) in the tumor microenvironment of NLPHL and more specifically, to determine cell densities of Tregs in relation with the different histopathological growth patterns of NLPHL. We hypothesize that the number of Tregs will be higher in those immunoarchitectural patterns with the higher risk of disease recurrence/progression. Patients with a diagnosis of NLPHL between 2017 and 2021 with formalin-fixed paraffin embedded tissue biopsies available in our institution were included in the study. All cases were submitted to a previously optimized and validated multiplex IF panel which was specifically developed to assess classic and EOMES+ Tr-1 like Tregs. The panel included CD3, CD4, CD8, CD20, CD25, EOMES, Foxp3, and Granzyme K. Reactive tonsils were used as a positive control. The slides were imaged using Vectra Polaris system (Akoya Biosciences, Marlborough, MA) and up to 10 representative regions of interest (ROI) were selected from each case. The data was consolidated using Spotfire software. The nonparametric Mann-Whitney test was used to compare ROI representing group I and group II histologic areas. Eleven patients with available pretreatment samples were identified. The majority were male (n=7, 63%), with advanced stage of disease (n=7, 63% Stage III/IV); all patients were alive at last follow-up (median: 42 months). A total of 109 ROIs were analyzed (n=54 in group I and n=55 in group II) with a mean number of 22,723 cells/case, and a mean analyzed area of 1.6 mm2/case. The population of CD4+ T-cells was significantly increased in group I (patterns A-C) when compared to group II (patterns D to F) (median, 640 vs 2100, p=0.0013). Interestingly, the group II was associated with a significantly higher cell density of CD4+ EOMES+ Tr1-like cells when compared to group I (median, 0 vs 1010, p<0.0001) (Figure 1). Although not statistically significant, classical Tregs (CD3+CD4+Foxp3+) were also increased in the group II (median, 24.64 vs 67.77, p=0.094). In summary, increased cell densities of Tregs and specifically EOMES+ Tr1-like are strongly associated with architectural patterns of high-risk for disease recurrence and progression in NLPHL. Our data provide a biological rational to focus on these subset populations in efforts to decrease disease recurrence and progression in NLPHL. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Feasibility of identifying the authenticity of fresh and cooked mutton kebabs using visible and near-infrared hyperspectral imaging

Mutton kebab is an attractive type of meat product with high nutritional value, and is favored by consumers worldwide. However, mutton kebab is often subjected to adulteration due to its high price. Chicken, duck, and pork are frequently used as adulterated substitutes. The purpose of current study aims at developing a methodology based on hyperspectral imaging (HSI, 400–1000 nm) for identifying the authenticity of fresh and cooked mutton kebabs. Kebab samples were individually scanned using HSI system in their fresh and cooked states. Spectra of chicken, duck, pork, and mutton kebabs were first extracted from representative regions of interest (ROIs) identified in their calibrated hyperspectral images. After that, principal component analysis (PCA) was carried out, and results showed that the first three or two PCs were effective for identifying fresh or cooked samples of different meat species. Different effective modeling algorithms including k-nearest neighbor (KNN), partial least squares discriminant analysis (PLS-DA), and support vector machine (SVM) algorithms combined with different preprocessing methods were employed to develop classification models. Performances exhibited that PLS-DA models using raw spectra outperformed the KNN and SVM models, and the accuracies reached both 100 % in prediction sets for fresh and cooked meat kebabs, respectively. Moreover, compared to iteratively variable subset optimization (IVSO), random frog (RF), and successive projections algorithm (SPA) algorithms, the PC loadings successfully screened 14 and 8 effective wavelengths for fresh and cooked meat kebabs, respectively, from the complex original full-band wavelengths. The PC-PLS-DA models showed the optimal predicted performances with overall classification accuracies of 97.5 % and 100 %, sensitivity values of 1.00 and 1.00, specificity values of 0.97 and 1.00, precisions of 0.91 and 1.00, for fresh and cooked mutton kebabs, respectively. Furthermore, the visualization of classification maps confirmed the experimental results intuitively. Overall, it was evident that HSI showed immense potential to identify the authenticity of fresh and cooked mutton kebabs when substituted by different meats including chicken, duck, and pork.

Impact of Region-of-Interest Size on Immune Profiling Using Multiplex Immunofluorescence Tyramide Signal Amplification for Paraffin-Embedded Tumor Tissues

Introduction: Representative regions of interest (ROIs) analysis from the whole slide images (WSI) are currently being used to study immune markers by multiplex immunofluorescence (mIF) and single immunohistochemistry (IHC). However, the amount of area needed to be analyzed to be representative of the entire tumor in a WSI has not been defined. Methods: We labeled tumor-associated immune cells by mIF and single IHC in separate cohorts of non-small cell lung cancer (NSCLC) samples and we analyzed them as whole tumor area as well as using different number of ROIs to know how much area will be need to represent the entire tumor area. Results: For mIF using the InForm software and ROI of 0.33 mm2 each, we observed that the cell density data from five randomly selected ROIs is enough to achieve, in 90% of our samples, more than 0.9 of Spearman correlation coefficient and for single IHC using ScanScope tool box from Aperio and ROIs of 1 mm2 each, we found that the correlation value of more than 0.9 was achieved using 5 ROIs in a similar cohort. Additionally, we also observed that each cell phenotype in mIF influence differently the correlation between the areas analyzed by the ROIs and the WSI. Tumor tissue with high intratumor epithelial and immune cells phenotype, quality, and spatial distribution heterogeneity need more area analyzed to represent better the whole tumor area. Conclusion: We found that at minimum 1.65 mm2 area is enough to represent the entire tumor areas in most of our NSCLC samples using mIF.

Rapid and non-destructive detection of natural mildew degree of postharvest Camellia oleifera fruit based on hyperspectral imaging

Camellia oleifera fruit is a kind of popular woody oil crops in China, which is susceptible to natural mildew damage during storage. This problem significantly depreciates its value and poses a potential threat to human health. A hyperspectral imaging (HSI) system covered visible and near-infrared (Vis-NIR, 400–1000 nm) range was employed to identify Camellia oleifera fruit with three different natural mildew degrees (slight, moderate, and severe). Spectra were primarily extracted from representative regions of interest (ROIs), and principal component analysis (PCA) of extracted spectra revealed that PC1 and PC2 were effective for the identification. Hyperspectral images were then processed using PC transformation for exploratory visual detection by displaying PC1 and PC2 score images. Three modeling methods including partial least squares-discriminant analysis (PLS-DA), k-nearest neighbor (KNN), and classification and regression tree (CART) were subsequently evaluated in terms of their capacity to establish the natural mildew degree estimation model developed by full spectra. Raw spectra without any preprocessing constructed the optimal PLS-DA model with the highest 90.8% correct classification rate (CCR) of success in external prediction set. After that, key wavelengths selected by competitive adaptive reweighted sampling (CARS) algorithm built an optimal simplified model, achieving the best performance with the highest CCR of 83.3%, AUC value of 0.89, and Kappa coefficient of 0.75 in prediction set. Therefore, CARS-PLS-DA model was finally employed to visually classify the three different natural mildew degrees. As a result, the general natural mildew degrees of Camellia oleifera samples were readily discernible in pixel-wise manner by generating classification maps. The overall results illustrated that HSI offered an alternative way in detecting and visualizing natural mildew degrees of Camellia oleifera fruit.

Variety Identification of Chinese Walnuts Using Hyperspectral Imaging Combined with Chemometrics

Chinese walnuts have extraordinary nutritional and organoleptic qualities, and counterfeit Chinese walnut products are pervasive in the market. The aim of this study was to investigate the feasibility of hyperspectral imaging (HSI) technique to accurately identify and visualize Chinese walnut varieties. Hyperspectral images of 400 Chinese walnuts including 200 samples of Ningguo variety and 200 samples of Lin’an variety were acquired in range of 400–1000 nm. Spectra were extracted from representative regions of interest (ROIs), and principal component analysis (PCA) of spectra showed that the characteristic second principal component (PC2) was potentially effective in variety identification. The PC transformation was also conducted to hyperspectral images to make an exploratory visualization according to pixel-wise PC scores. Three different modeling methods including partial least squares-discriminant analysis (PLS-DA), k-nearest neighbor (KNN), and support vector machine (SVM) were individually employed to develop classification models. Results indicated that raw full spectra constructed PLS-DA model performed best with correct classification rates (CCRs) of 97.33%, 95.33%, and 92.00% in calibration, cross-validation, and prediction sets, respectively. Successful projects algorithm (SPA), competitive adaptive reweighted sampling (CARS), and PC loadings were individually used for effective wavelengths selection. Subsequently, simplified PLS-DA model based on wavelengths selected by CARS yielded the best 96.33%, 95.67% and 91.00% CCRs in the three sets. This optimal CARS-PLS-DA model acquired a sensitivity of 93.62%, a specificity of 88.68%, the area under the receiver operating characteristic curve (AUC) value of 0.91, and Kappa coefficient of 0.82 in prediction set. Classification maps were finally generated by classifying the varieties of each pixel in multispectral images at CARS-selected wavelengths, and the general variety was then readily discernible. These results demonstrated that features extracted from HSI had outstanding ability, and could be applied as a reliable tool for the further development of an on-line identification system for Chinese walnut variety.

Chemometrics in Tandem with Hyperspectral Imaging for Detecting Authentication of Raw and Cooked Mutton Rolls.

Authentication assurance of meat or meat products is critical in the meat industry. Various methods including DNA- or protein-based techniques are accurate for assessing meat authenticity, however, they are destructive, expensive, or laborious. This study explores the feasibility of chemometrics in tandem with hyperspectral imaging (HSI) for identifying raw and cooked mutton rolls substitution by pork and duck rolls. Raw or cooked samples (n = 180) of three meat species were prepared to collect hyperspectral images in range of 400–1000 nm. Spectra were extracted from representative regions of interest (ROIs), and spectral principal component analysis (PCA) revealed that PC1 and PC2 were effective for the identification. Different methods including standard normal variable (SNV), first and second derivatives, and normalization were individually employed for spectral preprocessing, and modeling methods of partial least squares-discriminant analysis (PLS-DA) and support vector machines (SVM) were also individually applied to develop classification models for both the raw and the cooked. Results showed that PLS-DA model developed by raw spectra presented the highest 100% correct classification rate (CCR) of success in all sets. After that, effective wavelengths selected by successive projections algorithm (SPA) built optimal simplified models which didn’t influence the modeling results compared with full spectra regardless of the meat roll states. Therefore, SPA-PLS-DA models were subsequently used to visualize the raw and cooked meat rolls classification. As a consequence, the general meat species of both raw and cooked meat rolls were readily discernible in pixel-wise manner by generating classification maps. The results showed that HSI combined with chemometrics can be used to identify the authentication of raw and cooked mutton rolls substituted by pork and duck rolls accurately. This promising methodology provides a reference which can be extended to the classification or grading of other meat rolls.

Long-term changes in mandibular bone microchemical quality after radiation therapy and underlying systemic malignancy: A pilot study

Radiation therapy (RT) is a treatment option for head and neck cancer (HNC), but 2% of RT patients may experience damage to the jawbone, resulting in osteoradionecrosis (ORN). The ORN can manifest years after RT exposure. Changes in the local microchemical bone quality prior to the clinical manifestation of ORN could play a key role in ORN pathogenesis. Chemical bone quality can be analyzed using Fourier transform infrared spectroscopy (FTIR), that is applied to examine the effects of cancer, chemotherapy, and RT on the quality of human mandibular bone. Cortical mandibular bone samples were harvested from dental implant beds of 23 individuals, i.e., patients with surgically and radiotherapeutically treated HNC (RT-HNC, [Formula: see text]), surgically and radiochemotherapeutically treated HNC (CH-RT-HNC, [Formula: see text]), only surgically treated HNC (SRG-HNC, [Formula: see text]), and healthy controls ([Formula: see text]). Infrared spectra were acquired from two representative regions of interest in cortical mandibular bone. Spectral parameters, i.e., mineral-to-matrix ratio (MM), carbonate-to-matrix ratio (CM), carbonate-to-phosphate ratio (CP), collagen maturity (cross-linking), crystallinity, acid phosphate substitution (APS), and advanced glycation end products (AGEs), were analyzed for each sample. Amide I region of the CH-RT-HNC group differed from the control group in cluster analysis ([Formula: see text]). Apart from a minor variation trend in collagen maturity ([Formula: see text]), there were no other significant differences between the groups. Thus, the effect of radiochemotherapy on mandibular bone composition should be further investigated. In future trials, this study design is potential when the effects of the cancer burden and different HNC treatment modalities on jawbone composition are studied, in order to reveal ORN pathogenesis.

Influence of resolution on the X-ray CT-based measurements of metallic AM lattice structures

Additive manufactured (AM) lattice structures have become very prominent in recent times especially in air and spacecraft industry for their lower weight and specific mechanical properties. Their stiffness and strength can be controlled by their geometrical properties, such as the shape and dimensions of the unit cell. Geometrical and dimensional accuracy of the AM lattices is therefore one of the most important requirements to meet the desired functionality as there could be significant deviations in the as-produced part from the designed model; thus, their measurements are of great significance. X-ray computed tomography (CT) has emerged as a promising solution in the field of industrial quality control over the last few years due to its non-destructive approach. However, CT measurement accuracy depends on various parameters (part material, system, operator, environment, data post-processing), among which the resolution or voxel size of the CT data is crucial. In this work, the influence of resolution on the measurement of metallic lattice structure is studied by means of simulations and real CT experiments. The optimized CT acquisition settings are obtained with the help of simulated radiographs and design-of-experiment approach. Three different resolutions are achieved by placing the part at different positions from the X-ray source. The computer-aided design (CAD) model comparison reveals that the majority of surface has a deviation of ± 0.2 mm and the results are slightly affected by the resolution. The wall thickness analysis provides a global observation of the strut and node thicknesses. Individual struts are measured with representative regions of interest (ROIs) considering the manufacturing direction. The measurement results are significantly affected by the resolution (or voxel size) of the CT data. Simulated CT scans with different resolutions have been performed for systematic error estimation in relation to the voxel size.

Correlation of Placental Magnetic Resonance Imaging With Histopathologic Diagnosis: Detection of Aberrations in Structure and Water Diffusivity.

Noninvasive methods to identify placental pathologic conditions are being sought in order to recognize these conditions at an earlier stage leading to improved clinical interventions and perinatal outcomes. The objective of this study was to examine fixed tissue slices of placenta by T2- and diffusion-weighted magnetic resonance imaging (MRI) and correlate the images with placental pathologic findings defined by routine gross and histologic examination. Four formalin-fixed placentas with significant placental pathology (maternal vascular malperfusion, chronic villitis of unknown etiology, and massive perivillous fibrin deposition) and 2 histologically normal placentas were evaluated by high-resolution MRI. Representative placental slices were selected (2 cm long and 10 mm wide) and rehydrated. Imaging was performed on a Bruker Avance 14.1 T microimager. Diffusion-weighted images were acquired from 16 slices using slice thickness 0.5 mm and in-plane resolution approximately 100 µm × 100 µm. T2 maps were obtained from the same slices. T2 relaxation time and apparent diffusion coefficient (ADC) were acquired from representative regions of interest and compared between normal and diseased placentas. In T2- and diffusion-weighted images, the placental microstructure differed subjectively between diseased and normal placentas. Furthermore, diseased placentas showed statistically significantly longer mean T2 relaxation times and generally higher mean ADC. Diffusion- and T2-weighted MRI can potentially be used to detect significant placental pathology by using T2 relaxation time and ADC as markers of altered placental microstructure.

Dose Reduction for Sinus and Temporal Bone Imaging Using Photon-Counting Detector CT With an Additional Tin Filter.

The aim of this study was to quantitatively demonstrate radiation dose reduction for sinus and temporal bone examinations using high-resolution photon-counting detector (PCD) computed tomography (CT) with an additional tin (Sn) filter. A multienergy CT phantom, an anthropomorphic head phantom, and a cadaver head were scanned on a research PCD-CT scanner using ultra-high-resolution mode at 100-kV tube potential with an additional tin filter (Sn-100 kV) and volume CT dose index of 10 mGy. They were also scanned on a commercial CT scanner with an energy-integrating detector (EID) following standard clinical protocols. Thirty patients referred to clinically indicated sinus examinations, and two patients referred to temporal bone examinations were scanned on the PCD-CT system after their clinical scans on an EID-CT. For the sinus cohort, PCD-CT scans were performed using Sn-100 kV at 4 dose levels at 10 mGy (n = 9), 8 mGy (n = 7), 7 mGy (n = 7), and 6 mGy (n = 7), and the clinical EID-CT was performed at 120 kV and 13.7 mGy (mean CT volume dose index). For the temporal bone scans, PCD-CT was performed using Sn-100 kV (10.1 mGy), and EID-CT was performed at 120 kV and routine clinical dose (52.6 and 66 mGy). For both PCD-CT and EID-CT, sinus images were reconstructed using H70 kernel at 0.75-mm slice thickness, and temporal bone images were reconstructed using a U70 kernel at 0.6-mm slice thickness. In addition, iterative reconstruction with a dedicated sharp kernel (V80) was used to obtain high-resolution PCD-CT images from a sinus patient scan to demonstrate improved anatomic delineation. Improvements in spatial resolution from the dedicated sharp kernel was quantified using modulation transfer function measured with a wire phantom. A neuroradiologist assessed the H70 sinus images for visualization of critical anatomical structures in low-dose PCD-CT images and routine-dose EID-CT images using a 5-point Likert scale (structural detection obscured and poor diagnostic confidence, score = 1; improved anatomic delineation and diagnostic confidence, score = 5). Image contrast and noise were measured in representative regions of interest and compared between PCD-CT and EID-CT, and the noise difference between the 2 acquisitions was used to estimate the dose reduction in the sinus and temporal bone patient cohorts. The multienergy phantom experiment showed a noise reduction of 26% in the Sn-100 kV PCD-CT image, corresponding to a total dose reduction of 56% compared with EID-CT (clinical dose) without compromising image contrast. The PCD-CT images from the head phantom and the cadaver scans demonstrated a dose reduction of 67% and 83%, for sinus and temporal bone examinations, respectively, compared with EID-CT. In the sinus cohort, PCD-CT demonstrated a mean dose reduction of 67%. The 10- and 8-mGy sinus patient images from PCD-CT were significantly superior to clinical EID-CT for visualization of critical sinus structures (median score = 5 ± 0.82 and P = 0.01 for lesser palatine foramina, median score = 4 ± 0.68 and P = 0.039 for nasomaxillary sutures, and median score = 4 ± 0.96 and P = 0.01 for anterior ethmoid artery canal). The 6- and 7-mGy sinus patient images did not show any significant difference between PCD-CT and EID-CT. In addition, V80 (sharp kernel, 10% modulation transfer function = 18.6 cm) PCD-CT images from a sinus patient scan increased the conspicuity of nasomaxillary sutures compared with the clinical EID-CT images. The temporal bone patient images demonstrated a dose reduction of up to 85% compared with clinical EID-CT images, whereas visualization of inner ear structures such as the incudomalleolar joint were similar between EID-CT and PCD-CT. Phantom and cadaver studies demonstrated dose reduction using Sn-100 kV PCD-CT compared with current clinical EID-CT while maintaining the desired image contrast. Dose reduction was further validated in sinus and temporal bone patient studies. The ultra-high resolution capability from PCD-CT allowed improved anatomical delineation for sinus imaging compared with current clinical standard.

Scanner influence on the mechanical response of QCT-based finite element analysis of long bones

Patient-specific QCT-based finite element (QCTFE) analyses enable highly accurate quantification of bone strength. We evaluated CT scanner influence on QCTFE models of long bones.A femur, humerus, and proximal femur without the head were scanned with K2HPO4 phantoms by seven CT scanners (four models) using typical clinical protocols. QCTFE models were constructed. The geometrical dimensions, as well as the QCT-values expressed in Hounsfield unit (HU) distribution was compared. Principal strains at representative regions of interest (ROIs), and maximum principal strains (associated with fracture risk) were compared. Intraclass correlation coefficients (ICCs) were calculated to evaluate strain prediction reliability for different scanners. Repeatability was examined by scanning the femur twice and comparing resulting QCTFE models.Maximum difference in geometry was 2.3%. HU histograms before phantom calibration showed wide variation between QCT scans; however, bone density histogram variability was reduced after calibration and algorithmic manipulation. Relative standard deviation (RSD) in principal strains at ROIs was <10.7%. ICC estimates between scanners were >0.9. Fracture-associated strain had 6.7%, 8.1%, and 13.3% maximum RSD for the femur, humerus, and proximal femur, respectively. The difference in maximum strain location was <2 mm. The average difference with repeat scans was 2.7%.Quantification of strain differences showed mean RSD bounded by ∼6% in ROIs. Fracture-associated strains in “regular” bones showed a mean RSD bounded by ∼8%. Strains were obtained within a ±10% difference relative to the mean; thus, in a longitudinal study only changes larger than 20% in the principal strains may be significant. ICCs indicated high reliability of QCTFE models derived from different scanners.

COMPUTED TOMOGRAPHIC FINDINGS IN 24 DOGS WITH LIPOSARCOMA.

Computed tomography (CT) continues to become more widely available for assessment of tumors in dogs, yet there are no studies describing the CT appearance of canine liposarcomas. In this retrospective, multicenter study, CT images of dogs with histologically confirmed liposarcomas were reviewed for size, location, attenuation, contrast enhancement, border definition, internal homogeneity, local infiltration, and mineralization. A total of 24 dogs with 26 liposarcomas were sampled. Mean attenuation was +15.2 (SD = 22.3) Hounsfield units (HU) with a range of -36 to +47.5 HU based on representative regions of interest. Twenty tumors (77%) contained focal areas of fat attenuation. All masses enhanced with contrast medium administration, which is distinct from what has been reported previously in infiltrative lipomas. Other CT features associated with canine liposarcomas included heterogeneous internal attenuation (81%) and lack of a clearly defined capsule (38%) suggesting infiltration of local structures. Six tumors (23%) had foci of mineralization. Findings from the current study indicated that liposarcoma should be considered as a differential diagnosis for mixed-attenuation, contrast-enhancing masses in dogs that contain at least one focus of fat attenuation on precontrast images; however, presence of foci of fat attenuation was not a necessary finding for the diagnosis of canine liposarcoma.

T1ρ Hip Cartilage Mapping in Assessing Patients With Cam Morphology: How Can We Optimize the Regions of Interest?

T1ρ MRI has been shown feasible to detect the biochemical status of hip cartilage, but various region-of-interest strategies have been used, compromising the reproducibility and comparability between different institutions and studies. The purposes of this study were (1) to determine representative regions of interest (ROIs) for cartilage T1ρ mapping in hips with a cam deformity; and (2) to assess intra- and interobserver reliability for cartilage T1ρ mapping in hips with a cam deformity. The local ethics committee approved this prospective study with written informed consent obtained. Between 2010 and 2013, in 54 hips (54 patients), T1ρ 1.5-T MRI was performed. Thirty-eight hips (38 patients; 89% male) with an average age of 35 ± 7.5 years (range, 23-51 tears) were diagnosed with a cam deformity; 16 hips (16 patients; 87% male) with an average age of 34 ± 7 years (range, 23-47 years) were included in the control group. Of the 38 patients with a cam deformity, 20 were pain-free and 18 symptomatic patients underwent surgery after 6 months of failed nonsurgical management of antiinflammatories and physical therapy. Exclusion criteria were radiologic sings of osteoarthritis with Tönnis Grade 2 or higher as well as previous hip surgery. Three region-of-interest (ROI) selections were analyzed: Method 1: as a whole; Method 2: as 36 to 54 small ROIs (sections of 30° in the sagittal plane and 3 mm in the transverse plane); Method 3a: as six ROIs (sections of 90° in the sagittal plane and one-third of the acetabular depth in the transverse plane: the anterosuperior and posterosuperior quadrants, divided into lateral, intermediate, and medial thirds); and Method 3b: as the ratio (anterosuperior over posterosuperior quadrant). ROIs in Method 3 represent the region of macroscopic cartilage damage, described in intraoperative findings. To asses interobserver reliability, 10 patients were analyzed by two observers (HA, GM). For intraobserver reliability, 20 hip MRIs were analyzed twice by one observer (HA). To assess interscan reliability, three patients underwent two scans within a time period of 2 weeks and were analyzed twice by one observer (HA). T1ρ values were compared using Student's t test. Interclass correlation coefficient (ICC) and root mean square coefficient of variation (RMS-CV) were used to analyze intraobserver, interobserver, and interscan reliability. Patients with a cam deformity showed increased T1ρ values in the whole hip cartilage (mean: 34.0 ± 3.8 ms versus 31.4 ± 3.0 ms; mean difference: 2.5; 95% confidence interval [CI], 4.7-0.4; p = 0.019; Method 1), mainly anterolateral (2), in the lateral and medial thirds of the anterosuperior quadrant (mean: 32.3 ± 4.9 ms versus 29.4 ± 4.1 ms; mean difference: 3.0; 95% CI, 5.8-0.2; p = 0.039 and mean 36.5 ± 5.6 ms versus 32.6 ± 3.8 ms; mean difference: 3.8; 95% CI, 6.9-0.8; p = 0.014), and in the medial third of the posterosuperior quadrant (mean: 34.4 ± 5.5 ms versus 31.1 ± 3.9 ms; mean difference: 3.1; 95% CI, 6.2-0.1; p = 0.039) (3a). The ratio was increased in the lateral third (mean: 1.00 ± 0.12 versus 0.90 ± 0.15; mean difference: 0.10; 95% CI, 0.18-0.2; p = 0.018) (3b). ICC and RMS-CV were 0.965 and 4% (intraobserver), 0.953 and 4% (interobserver), and 0.988 (all p < 0.001) and 9% (inter-MR scan), respectively. Cartilage T1ρ MRI mapping in hips is feasible at 1.5 T with strong inter-, intraobserver, and inter-MR scan reliability. The six ROIs (Method 3) showed a difference of T1ρ values anterolateralquadrant, consistent with the dominant area of cartilage injury in cam femoroacetabular impingement, and antero- and posteromedial, indicating involvement of the entire hip cartilage health. The six ROIs (Method 3) have been shown feasible to assess cartilage damage in hips with a cam deformity using T1ρ MRI. We suggest applying this ROI selection for further studies using quantitative MRI for assessment of cartilage damage in hips with a cam deformity to achieve better comparability and reproducibility between different studies. The application of this ROI selection on hips with other deformities (eg, pincer deformity, developmental dysplasia of the hip, and acetabular retroversion) has to be analyzed and potentially adapted. Level III, diagnostic study.

Vascular coupling in resting-state fMRI: evidence from multiple modalities.

Resting-state functional magnetic resonance imaging (rs-fMRI) provides a potential to understand intrinsic brain functional connectivity. However, vascular effects in rs-fMRI are still not fully understood. Through multiple modalities, we showed marked vascular signal fluctuations and high-level coupling among arterial pressure, cerebral blood flow (CBF) velocity and brain tissue oxygenation at <0.08 Hz. These similar spectral power distributions were also observed in blood oxygen level-dependent (BOLD) signals obtained from six representative regions of interest (ROIs). After applying brain global, white-matter, cerebrospinal fluid (CSF) mean signal regressions and low-pass filtering (<0.08 Hz), the spectral power of BOLD signal was reduced by 55.6% to 64.9% in all ROIs (P=0.011 to 0.001). The coherence of BOLD signal fluctuations between an ROI pair within a same brain network was reduced by 9.9% to 20.0% (P=0.004 to <0.001), but a larger reduction of 22.5% to 37.3% (P=0.032 to <0.001) for one not in a same network. Global signal regression overall had the largest impact in reducing spectral power (by 52.2% to 61.7%) and coherence, relative to the other three preprocessing steps. Collectively, these findings raise a critical question of whether a large portion of rs-fMRI signals can be attributed to the vascular effects produced from upstream changes in cerebral hemodynamics.

Determination of the mechanical properties of lumbar porcine vertebrae with 2D digital image correlation.

To evaluate the strain fields and to calculate the modulus of elasticity and Poisson's ratio of trabecular bone of the 6 lumbar vertebrae of the porcine spine by a 2-dimensional digital image correlation (2D DIC). This study was performed through a 2D DIC technique and the specimens were tested under compression. The resulting images were analyzed numerically by 2D DIC. Then, representative regions of interest were examined. The strain fields were determined and stress-strain curves were obtained. The full field measurement of the strain in the lumbar bone spine was evaluated and with this data, the Young's modulus and Poisson's ratio were determined. This research highlights the potential applications of noninvasive acquisition techniques in biomechanical analysis. This is useful in the mechanical characterization of bony structures and in the design of prostheses.

Online extraction and single trial analysis of regions contributing to erroneous feedback detection

Understanding how the brain processes errors is an essential and active field of neuroscience. Real time extraction and analysis of error signals provide an innovative method of assessing how individuals perceive ongoing interactions without recourse to overt behaviour. This area of research is critical in modern Brain–Computer Interface (BCI) design, but may also open fruitful perspectives in cognitive neuroscience research. In this context, we sought to determine whether we can extract discriminatory error-related activity in the source space, online, and on a trial by trial basis from electroencephalography data recorded during motor imagery. Using a data driven approach, based on interpretable inverse solution algorithms, we assessed the extent to which automatically extracted error-related activity was physiologically and functionally interpretable according to performance monitoring literature. The applicability of inverse solution based methods for automatically extracting error signals, in the presence of noise generated by motor imagery, was validated by simulation. Representative regions of interest, outlining the primary generators contributing to classification, were found to correspond closely to networks involved in error detection and performance monitoring. We observed discriminative activity in non-frontal areas, demonstrating that areas outside of the medial frontal cortex can contribute to the classification of error feedback activity.

On-Board CBCT Imaging Using 2.5 MV Beam on a Radiation Therapy Linac for Metal Artifact Reduction

Purpose/Objective(s): Highly attenuating metallic objects such as dental fillings, hip/shoulder prosthesis, fiducial markers, cause severe streaking artifacts in on-board kV CBCT imaging and can lead to errors in imageguided patient setup. The purpose of this work is to reduce metal artifact in on-board CBCT imaging using new 2.5 MV beam available on a radiation therapy Linac. Materials/Methods: A head phantom with a copper bar inserted in the center was scanned with the 2.5 MV beam. With a full gantry rotation, 68 projection views were collected for a total of 20 MU. For comparison, a CBCT scan was also performed using the on-board kV imaging system. The peak voltage for kV scanning was 100 kVp. Due to the sparse projections of MV scanning, we performed iterative image reconstruction on both kV and MV data respectively. Several representative regions of interest were selected for evaluation of metal artifacts and contrast. Results: The mean CT numbers of the bright and dark metal artifacts in kV CBCT are 9000HU and -3000HU. In comparison, there are no bright metal artifacts and the mean CT number of dark metal artifacts is reduced to -460HU in MV CBCT. The mean CT numbers of the bone and metal are 1000HU, 5000HU for kV, and 380HU, 3600HU for MV. The mean CT numbers for three low contrast regions are -800HU, -600HU, -400HU for kV, and -460HU,-300HU, -100HU for MV. Conclusions: Using the new 2.5 MV beam for on-board CBCT imaging, we have significantly reduced metal artifacts compared with kV imaging, although with a decrease in soft-tissue contrast. Combining kV and MV imaging may lead to improved soft-tissue contrast with negligible metal artifact. Author Disclosure: Q. Xu: None. R. Li: None. Y. Yang: None. L. Xing: None.

Reversible, irreversible and effective transverse relaxation rates in normal aging brain at 3 T

Quantitative transverse relaxation rates in normal aging brain are essential to investigate pathologies associated with iron accumulation and tissue degeneration. Since absolute values depend on imaging methods and magnetic field strengths, continuous evaluation of specific reference values remains requisite.Multi-echo turbo spin echo and multi-echo gradient recalled echo imaging sequences were applied to 66 healthy subjects (18–84years) at 3T to quantify the irreversible (R2), effective (R2*) and reversible (R2'=R2*−R2) transverse relaxation rates. Representative regions-of-interest (ROIs) were determined automatically in gray matter (GM) and white matter (WM) on T1-weighted scans. Phantom experiments of different sized iron-oxide particles were conducted to explore the correlation of R2' related to R2 for the evaluation of the size of iron deposits.R2 decreased with age for the majority of ROIs, but increased for putamen, head of caudate nucleus and nucleus accumbens. R2* and R2' increased with age in deep GM structures except for the thalamus. R2* and R2' showed a distinct dependency on fiber orientation in exemplary WM regions. R2', R2 and R2* were strongly linear proportional to age-related iron content in deep GM with slopes of 0.88, 0.18 and 1.08 in [1/s/mg Fe per 100g wet tissue] and intercepts of 1.69, 9.25 and 10.69 in [1/s], respectively. Linear and non-linear curve fitting of R2' vs. R2 in phantoms revealed increased slopes with increasing particle size. In vivo, averaged R2' vs. R2 data points of patients with Parkinson's disease and progressive supranuclear palsy were above the fitted curves of healthy subjects suggesting larger sized iron deposits in these neurodegenerative diseases.Decreased R2 with age may reflect physiological tissue degeneration, whereas increased R2* and R2' with age most likely denote physiological iron accumulation. The low intercept of R2' vs. iron content suggests a nearly sole sensitivity of R2' to iron in deep GM, potentially allowing a more specific estimation of the iron content than R2 or R2*. Since R2* and R2' depend on the fiber orientation, their feasibility to estimate iron content in WM is challenging. The analysis of R2' related to R2 may provide valuable information about the size of iron deposits.