CT Template Research Articles

125I seed brachytherapy for non-central pelvic recurrence of cervical cancer after external beam radiotherapy

ObjectiveTo investigate the efficacy of 125I seed brachytherapy for non-central pelvic recurrence of cervical cancer after external beam radiotherapy, and to analyze the clinical influential factors.MethodsBetween June 2015 and April 2022, 32 patients with 41 lesions were treated with 125I seed brachytherapy. The seeds were implanted under the guidance of CT and/or 3D-printed template images at a median dose of 100 Gy (range, 80–120 Gy), and the local control rate (LCR) and survival rates were calculated. We used multivariate logistic regression to identify prognosis predictors, and receiver operating characteristic (ROC) curve analysis to determine the optimal cut-off values.ResultsThe median follow-up was 48.52 months (range, 4–86 months), and the 6-, 12-, and 24-month LCR was 88.0%, 63.2%, and 42.1%, respectively. The 1- and 2-year survival rates were 36% and 33%, respectively, and the median survival time was 13.26 months. No significant adverse events occurred. Multivariate regression analysis showed that tumor diameter, tumor stage, and LCR were independent factors influencing survival. ROC curve analysis showed that the area under the curve for tumor diameter and D90 were 0.765 and 0.542, respectively, with cut-off values of 5.3 cm and 108.5 Gy.ConclusionsThe present findings indicate that 125I seed brachytherapy is feasible for treating non-central pelvic recurrence of cervical cancer after external beam radiotherapy. Further, tumor diameter < 5.3 cm and immediate postoperative D90 > 108.5 Gy were associated with better efficacy.

Automatic localisation and per-region quantification of traumatic brain injury on head CT using atlas mapping

Rationale and objectivesTo develop a method for automatic localisation of brain lesions on head CT, suitable for both population-level analysis and lesion management in a clinical setting. Materials and methodsLesions were located by mapping a bespoke CT brain atlas to the patient’s head CT in which lesions had been previously segmented. The atlas mapping was achieved through robust intensity-based registration enabling the calculation of per-region lesion volumes. Quality control (QC) metrics were derived for automatic detection of failure cases. The CT brain template was built using 182 non-lesioned CT scans and an iterative template construction strategy. Individual brain regions in the CT template were defined via non-linear registration of an existing MRI-based brain atlas.Evaluation was performed on a multi-centre traumatic brain injury dataset (TBI) (n = 839 scans), including visual inspection by a trained expert. Two population-level analyses are presented as proof-of-concept: a spatial assessment of lesion prevalence, and an exploration of the distribution of lesion volume per brain region, stratified by clinical outcome. Results95.7% of the lesion localisation results were rated by a trained expert as suitable for approximate anatomical correspondence between lesions and brain regions, and 72.5% for more quantitatively accurate estimates of regional lesion load. The classification performance of the automatic QC showed an AUC of 0.84 when compared to binarised visual inspection scores. The localisation method has been integrated into the publicly available Brain Lesion Analysis and Segmentation Tool for CT (BLAST-CT). ConclusionAutomatic lesion localisation with reliable QC metrics is feasible and can be used for patient-level quantitative analysis of TBI, as well as for large-scale population analysis due to its computational efficiency (<2 min/scan on GPU).

Gastroenteropancreatic neuroendocrine neoplasm imaging: standard reporting templates.

Standardized reporting in radiology has an established role in numerous disease processes, with added benefits in oncology of reduced variability, and generation of a thorough and pertinent report with a focused and relevant conclusion. Many radiologists are not familiar with the imaging patterns of neuroendocrine neoplasm (NEN) spread and recurrence. This paper will present standardized CT, MRI, and PET templates for reporting gastroenteropancreatic (GEP) NENs and explain the rationale for including specific pertinent positive and negative findings, at various stages of disease management, based on site of origin. Basic templates for initial and follow-up anatomic and molecular GEP NEN imaging were created with input from the multidisciplinary Society of Abdominal Radiology (SAR) Neuroendocrine Tumor Disease Focused Panel (NET-DFP). The templates were further modified and finalized after several iterations. Four main report templates were generated for (i) initial anatomic CT or MR imaging studies, (ii) follow-up anatomic CT or MR imaging studies, (iii) initial Somatostatin Receptor (SSTR) or FDG PET imaging studies, and (iv) follow-up SSTR or FDG PET imaging studies. Each study template was formatted to allow its integration into a dictation software directly and be modified as needed, with internalized instructions indicating where a drop-down menu or macro may be used to personalize the template as necessary. These templates were created through a combination of multidisciplinary expert opinion discussion supported by literature review and provide basic structured reporting standards for GEP NEN anatomic and molecular imaging studies.

Automatic Bone Segmentation from MRI for Real-Time Knee Tracking in Fluoroscopic Imaging.

Recent progress in real-time tracking of knee bone structures from fluoroscopic imaging using CT templates has opened the door to studying knee kinematics to improve our understanding of patellofemoral syndrome. The problem with CT imaging is that it exposes patients to extra ionising radiation, which adds to fluoroscopic imaging. This can be solved by segmenting bone templates from MRI instead of CT by using a deep neural network architecture called 2.5D U-Net. To train the network, we used the SKI10 database from the MICCAI challenge; it contains 100 knee MRIs with their corresponding annotated femur and tibia bones as the ground truth. Since patella tracking is essential in our application, the SKI10 database was augmented with a new label named UofA Patella. Using 70 MRIs from the database, a 2.5D U-Net was trained successfully after 75 epochs with an excellent final Dice score of 98%, which compared favourably with the best state-of-the-art algorithms. A test set of 30 MRIs were segmented using the trained 2.5D U-Net and then converted into 3D mesh templates by using a marching cube algorithm. The resulting 3D mesh templates were compared to the 3D mesh model extracted from the corresponding labelled data from the augmented SKI10. Even though the final Dice score (98%) compared well with the state-of-the-art algorithms, we initially found that the Euclidean distance between the segmented MRI and SKI10 meshes was over 6 mm in many regions, which is unacceptable for our application. By optimising many of the hyper-parameters of the 2.5D U-Net, we were able to find that, by changing the threshold used in the last layer of the network, one can significantly improve the average accuracy to mm with a variance of mm for most of the MRI mesh templates. These results illustrate that the Dice score is not always a good predictor of the geometric accuracy of segmentation and that fine-tuning hyper-parameters is critical for improving geometric accuracy.

Stroke population–specific neuroanatomical CT-MRI brain atlas

PurposeDevelopment of a freely available stroke population–specific anatomical CT/MRI atlas with a reliable normalisation pipeline for clinical CT.MethodsBy reviewing CT scans in suspected stroke patients and filtering the AIBL MRI database, respectively, we collected 50 normal-for-age CT and MRI scans to build a standard-resolution CT template and a high-resolution MRI template. The latter was manually segmented into anatomical brain regions. We then developed and validated a MRI to CT registration pipeline to align the MRI atlas onto the CT template. Finally, we developed a CT-to-CT-normalisation pipeline and tested its reliability by calculating Dice coefficient (Dice) and Average Hausdorff Distance (AHD) for predefined areas in 100 CT scans from ischaemic stroke patients.ResultsThe resulting CT/MRI templates were age and sex matched to a general stroke population (median age 71.9 years (62.1–80.2), 60% male). Specifically, this accounts for relevant structural changes related to aging, which may affect registration. Applying the validated MRI to CT alignment (Dice > 0.78, Average Hausdorff Distance < 0.59 mm) resulted in our final CT-MRI atlas. The atlas has 52 manually segmented regions and covers the whole brain. The alignment of four cortical and subcortical brain regions with our CT-normalisation pipeline was reliable for small/medium/large infarct lesions (Dice coefficient > 0.5).ConclusionThe newly created CT-MRI brain atlas has the potential to standardise stroke lesion segmentation. Together with the automated normalisation pipeline, it allows analysis of existing and new datasets to improve prediction tools for stroke patients (free download at https://forms.office.com/r/v4t3sWfbKs).

Automated Cerebral Infarct Detection on Computed Tomography Images Based on Deep Learning.

The limited accuracy of cerebral infarct detection on CT images caused by the low contrast of CT hinders the desirable application of CT as a first-line diagnostic modality for screening of cerebral infarct. This research was aimed at utilizing convolutional neural network to enhance the accuracy of automated cerebral infarct detection on CT images. The CT images underwent a series of preprocessing steps mainly to enhance the contrast inside the parenchyma, adjust the orientation, spatially normalize the images to the CT template, and create a t-score map for each patient. The input format of the convolutional neural network was the t-score matrix of a 16 × 16-pixel patch. Non-infarcted and infarcted patches were selected from the t-score maps, on which data augmentation was conducted to generate more patches for training and testing the proposed convolutional neural network. The convolutional neural network attained a 93.9% patch-wise detection accuracy in the test set. The proposed method offers prompt and accurate cerebral infarct detection on CT images. It renders a frontline detection modality of ischemic stroke on an emergent or regular basis.

A statistical lumbar spine geometry model accounting for variations by Age, Sex, Stature, and body mass index

The objective of this study was to develop a statistical lumbar spine geometry model accounting for morphological variations among the adult population. Five lumber vertebrae and lumber spine curvature were collected from CT scans of 82 adult subjects through CT segmentation, landmark identification, and template mesh mapping. Generalized Procrustes Analysis (GPA), Principal Component Analysis (PCA), and multivariate regression analysis were conducted to develop the statistical lumbar spine model. Two statistical models were established to predict the vertebrae geometry and lumbar curvature respectively. Using the statistical models, a lumbar spine finite element (FE) model could be rapidly generated with a given set of age, sex, stature, and body mass index (BMI). The results showed that the lumbar spine vertebral size was significantly affected by stature, sex and age, and the lumbar spine curvature was significantly affected by stature and age. This statistical lumbar spine model could serve as the geometric basis for quantifying effects of human characteristics on lumbar spine injury risks in impact conditions.

Automated atlas-based segmentation for skull base surgical planning.

Computational surgical planning tools could help develop novel skull base surgical approaches that improve safety and patient outcomes. This defines a need for automated skull base segmentation to improve the usability of surgical planning software. The objective of this work was to design and validate an algorithm for atlas-based automated segmentation of skull base structures in individual image sets for skull base surgical planning. Advanced Normalization Tools software was used to construct a synthetic CT template from 6 subjects, and skull base structures were manually segmented to create a reference atlas. Landmark registration followed by Elastix deformable registration was applied to the template to register it to each of the 30 trusted reference image sets. Dice coefficient, average Hausdorff distance, and clinical usability scoring were used to compare the atlas segmentations to those of the trusted reference image sets. The mean for average Hausdorff distance for all structures was less than 2mm (mean for 95th percentile Hausdorff distance was less than 5mm). For structures greater than 2.5mL in volume, the average Dice coefficient was 0.73 (range 0.59-0.82), and for structures less than 2.5mL in volume the Dice coefficient was less than 0.7. The usability scoring survey was completed by three experts, and all structures met the criteria for acceptable effort except for the foramen spinosum, rotundum, and carotid artery, which required more than minor corrections. Currently available open-source algorithms, such as the Elastix deformable algorithm, can be used for automated atlas-based segmentation of skull base structures with acceptable clinical accuracy and minimal corrections with the use of the proposed atlas. The first publicly available CT template and anterior skull base segmentation atlas being released (available at this link: http://hdl.handle.net/1773/46259 ) with this paper will allow for general use of automated atlas-based segmentation of the skull base.

Development of multiplex real-time PCR assays for differential detection of capripoxvirus, parapoxvirus and foot-and-mouth disease virus.

This study reports the development of multiplex real-time PCR assays for differential detection of capripoxvirus (CaPV), parapoxvirus (PaPV) and foot-and-mouth disease virus (FMDV) in sheep, goats and cattle. Three multiplex assays were developed, a capripox (CaP) rule-out assay for simultaneous detection and differentiation of CaPV and PaPV, a FMD rule-out assay for simultaneous detection and differentiation of FMDV and PaPV, and a FMD/CaP rule-out assay for simultaneous detection and differentiation of CaPV, PaPV and FMDV. All multiplex assays included β-actin gene ACTB as an internal positive control to monitor PCR inhibition and accuracy of nucleic acid extractions. The optimized assays were highly specific to the target viruses (CaPV, PaPV and FMDV) with no cross-reactivity against other viruses that cause similar clinical signs. Using positive control plasmids as template, the limit of detection (LOD) of the multiplex assays were estimated as 2 CaPV, 7 PaPV and 15 FMDV copies per assay. The amplification efficiency (AE) and correlation coefficient (R2 ), estimated from the standard curves (Ct vs. log10 template dilution), were 94%-106% and >0.99, respectively, for CaP and FMD rule-out assays, 96%-116% (AE) and >0.98 (R2 ), respectively, for CaP/FMD rule-out assays and 91%-102% and >0.99, respectively, for the corresponding singleplex assays. The diagnostic sensitivity (DSe) of the multiplex assays was assessed on 35 CaPV and 39 FMDV clinical specimens from experimentally infected (CS-E) animals, and 29 CaPV (LSDV), 28 FMDV and 36 PaPV clinical specimens from naturally infected (CS-N) animals; all tested positive (DSe 100%) except two CS-E FMDV specimens that were tested negative by FMD rule-out and the corresponding singleplex (FMDV) assays (37/39; DSe 95%). The newly developed multiplex assays offer a valuable tool for differential detection of clinically indistinguishable CaPV, PaPV and FMDV in suspected animals and animals with mixed infections.

Detection and staging of radio-recurrent prostate cancer using multiparametric MRI.

We determined the sensitivity and specificity of multiparametric magnetic resonance imaging (MP-MRI) in detection of locally recurrent prostate cancer and extra prostatic extension in the post-radical radiotherapy setting. Histopathological reference standard was whole-mount prostatectomy specimens. We also assessed for any added value of the dynamic contrast enhancement (DCE) sequence in detection and staging of local recurrence. This was a single centre retrospective study. Participants were selected from a database of males treated with salvage prostatectomy for locally recurrent prostate cancer following radiotherapy. All underwent pre-operative prostate-specific antigen assay, positron emission tomography CT, MP-MRI and transperineal template prostate mapping biopsy prior to salvage prostatectomy. MP-MRI performance was assessed using both Prostate Imaging-Reporting and Data System v. 2 and a modified scoring system for the post-treatment setting. 24 patients were enrolled. Using Prostate Imaging-Reporting and Data System v. 2, sensitivity, specificity, positive predictive value and negative predictive value was 64%, 94%, 98% and 36%. MP-MRI under staged recurrent cancer in 63%. A modified scoring system in which DCE was used as a co-dominant sequence resulted in improved diagnostic sensitivity (61%-76%) following subgroup analysis. Our results show MP-MRI has moderate sensitivity (64%) and high specificity (94%) in detecting radio-recurrent intraprostatic disease, though disease tends to be under quantified and under staged. Greater emphasis on dynamic contrast images in overall scoring can improve diagnostic sensitivity. MP-MRI tends to under quantify and under stage radio-recurrent prostate cancer. DCE has a potentially augmented role in detecting recurrent tumour compared with the de novo setting. This has relevance in the event of any future modified MP-MRI scoring system for the irradiated gland.

Transcriptional regulation of protein S gene

Background: Protein S (PS) is a known Vitamin K dependent plasma glycoprotein that is produced in many human tissues including the liver. Furthermore, it has an important function in the coagulation cascade as an anticoagulant cofactor when it binds active protein C. The deficiency of PS may lead to the development of deep vein thrombosis. There are many transcription factors which play an important role in the regulation of the transcription of PS. One of these regulatory factors is the liver specific transcription factor hepatocyte nuclear factor 1 (HNF1), a binding site which is located in the 638 base pair promoter area at the 5' end of the PS gene. HNF1 and PS is not well understood and to confirm the importance of HNF1 in regulating expression of PS small interfering ribonucleic acid (siRNA) which will knockout the HNF1 gene expression can be used, and the effect on PS expression monitored. The levels of expression of HNF1 and PS can be determined by real time polymerase chain reaction. Materials and Methods: Preparation of total ribonucleic acid for complementary DNA synthesis, Evaluation the quality of HepG2 ribonucleic acid by agarose gel electrophores is, Real time polymerase chain reaction, Acrylamide gel electrophoresis. Results: HepG2 rRNA bands shows a good quality of RNA expression, Analysis of the total RNA quantity can be determined by spectrophotometric analysis, The best housekeeping genes were UBC and YWHAZ therefore, there has been used as a reference for the primers samples in efficiency test. HNF1 and PROS1 shows a good expression but with low efficiency which is not required to carry further gene knockdown experiment, SYBR green dye is less sensitive than TaqMan because it presents a non specific detection (primer dimers) were all dsDNA products are detected including primer dimers, contaminating DNA, and PCR product from mis annealed primer. Conclusion: The primer pairs are not efficient to carry further gene knockdown experiment and required to design another HNF1 and PROS1 primers. The efficiency of the PCR should be 90%-100% meaning doubling of the amplicon at each cycle. This corresponds to a slope of -3.1 to -3.6 in the Ct vs log template amount standard curve. To obtain accurate and reproducible results, reactions should have efficiency as close to 100% as possible.

PET attenuation correction for flexible MRI surface coils in hybrid PET/MRI using a 3D depth camera

PET attenuation correction for flexible MRI radio frequency surface coils in hybrid PET/MRI is still a challenging task, as position and shape of these coils conform to large inter-patient variabilities. The purpose of this feasibility study is to develop a novel method for the incorporation of attenuation information about flexible surface coils in PET reconstruction using the Microsoft Kinect V2 depth camera. The depth information is used to determine a dense point cloud of the coil’s surface representing the shape of the coil. From a CT template—acquired once in advance—surface information of the coil is extracted likewise and converted into a point cloud. The two point clouds are then registered using a combination of an iterative-closest-point (ICP) method and a partially rigid registration step. Using the transformation derived through the point clouds, the CT template is warped and thereby adapted to the PET/MRI scan setup. The transformed CT template is converted into an attenuation map from Hounsfield units into linear attenuation coefficients. The resulting fitted attenuation map is then integrated into the MRI-based patient-specific DIXON-based attenuation map of the actual PET/MRI scan. A reconstruction of phantom PET data acquired with the coil present in the field-of-view (FoV), but without the corresponding coil attenuation map, shows large artifacts in regions close to the coil. The overall count loss is determined to be around 13% compared to a PET scan without the coil present in the FoV. A reconstruction using the new μ-map resulted in strongly reduced artifacts as well as increased overall PET intensities with a remaining relative difference of about 1% to a PET scan without the coil in the FoV.

An Investigation into the Trueness and Precision of Copy Denture Templates Produced by Rapid Prototyping and Conventional Means.

To assess the trueness and precision of copy denture templates produced using traditional methods and 3D printing. Six copies of a denture were made using: 1. Conventional technique with silicone putty in an impression tray (CT). 2. Conventional technique with no impression tray (CNT). 3. 3D scanning and printing (3D). Scan trueness and precision was investigated by scanning a denture six times and comparing five scans to the sixth. Then the scans of the six CT, CNT and 3D dentures were compared by aligning, in turn, the copies of each denture to the scanned original. Outcome measures were the mean surface-to-surface distance, standard deviation of that distance and the maximum distance. Student's unpaired t-tests with Bonferroni correction were used to analyse the results. The repeated scans of the original denture showed a scan trueness of 0.013mm (SD 0.002) and precision of 0.013mm (SD 0.002). Trueness: CT templates, 0.168mm (0.047), CNT templates 0.195mm (0.034) and 3D 0.103mm (0.021). Precision: CT templates 0.158mm (0.037), CNT 0.233mm (0.073), 3D 0.090mm (0.017). For each outcome measure the 3D templates demonstrated an improvement which was statistically significant (p⟨0.05). 3D printed copy denture templates reproduced the original with greater trueness and precision than conventional techniques.

Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately?

In brain PET/MR applications, accurate attenuation maps are required for accurate PET image quantification. An implemented attenuation correction (AC) method for brain imaging is the single-atlas approach that estimates an AC map from an averaged CT template. As an alternative, we propose to use a zero echo time (ZTE) pulse sequence to segment bone, air and soft tissue. A linear relationship between histogram normalized ZTE intensity and measured CT density in Hounsfield units () in bone has been established thanks to a CT-MR database of 16 patients. Continuous AC maps were computed based on the segmented ZTE by setting a fixed linear attenuation coefficient (LAC) to air and soft tissue and by using the linear relationship to generate continuous μ values for the bone. Additionally, for the purpose of comparison, four other AC maps were generated: a ZTE derived AC map with a fixed LAC for the bone, an AC map based on the single-atlas approach as provided by the PET/MR manufacturer, a soft-tissue only AC map and, finally, the CT derived attenuation map used as the gold standard (CTAC). All these AC maps were used with different levels of smoothing for PET image reconstruction with and without time-of-flight (TOF). The subject-specific AC map generated by combining ZTE-based segmentation and linear scaling of the normalized ZTE signal into was found to be a good substitute for the measured CTAC map in brain PET/MR when used with a Gaussian smoothing kernel of corresponding to the PET scanner intrinsic resolution. As expected TOF reduces AC error regardless of the AC method. The continuous ZTE-AC performed better than the other alternative MR derived AC methods, reducing the quantification error between the MRAC corrected PET image and the reference CTAC corrected PET image.

A Neonatal Bimodal MR-CT Head Template.

Neonatal MR templates are appropriate for brain structural analysis and spatial normalization. However, they do not provide the essential accurate details of cranial bones and fontanels-sutures. Distinctly, CT images provide the best contrast for bone definition and fontanels-sutures. In this paper, we present, for the first time, an approach to create a fully registered bimodal MR-CT head template for neonates with a gestational age of 39 to 42 weeks. Such a template is essential for structural and functional brain studies, which require precise geometry of the head including cranial bones and fontanels-sutures. Due to the special characteristics of the problem (which requires inter-subject inter-modality registration), a two-step intensity-based registration method is proposed to globally and locally align CT images with an available MR template. By applying groupwise registration, the new neonatal CT template is then created in full alignment with the MR template to build a bimodal MR-CT template. The mutual information value between the CT and the MR template is 1.17 which shows their perfect correspondence in the bimodal template. Moreover, the average mutual information value between normalized images and the CT template proposed in this study is 1.24±0.07. Comparing this value with the one reported in a previously published approach (0.63±0.07) demonstrates the better generalization properties of the new created template and the superiority of the proposed method for the creation of CT template in the standard space provided by MR neonatal head template. The neonatal bimodal MR-CT head template is freely downloadable from https://www.u-picardie.fr/labo/GRAMFC.

Novel Multimodal Atlas Template for Spatial Normalization of Whole-Brain Images of Newborns

Due to the complications of the brain study in the first two years of life, the investigations conducted in the field of neonatal brain are limited. An efficient means for obtaining information about the neonatal brain is the brain template. In this paper, we represent the results of our research in the field of MR and CT atlas templates. At first, we construct a new MR atlas by utilizing a set of high-resolution T1-weighted MR images captured from a group of newborns with the gestational ages of 39 to 42 weeks at the examination date. Afterwards, we construct an original CT template, which is practically consistent with the MR atlas, by utilizing a set of high-resolution CT images captured from a group of newborns with the identical gestational ages. In spite of multifarious clinical applications, no modern CT template had been proposed to facilitate the normalization of neonatal CT images before we concentrated on providing the neonatal CT atlas. The developed atlases are evaluated qualitatively and quantitatively, for instance through the visual inspection and assessment of the anatomical local deviations. At the presence of both MR and CT modalities, further improvement could be attained in the medical diagnoses by the simultaneous utilization of the presented templates.

Direct Evaluation of MR-Derived Attenuation Correction Maps for PET/MR of the Mouse Myocardium

Attenuation correction (AC) must be applied to provide accurate measurements of PET tracer activity concentrations. Due to the limited space available in PET/MR scanners, MR-derived AC (MRAC) is used as a substitute for transmission source scanning. In preclinical PET/MR, there has been limited exploration of MRAC, as the magnitude of AC in murine imaging is much smaller than that required in clinical scans. We investigated if a simple 2 class (air and tissue) segmentation-based MRAC approach could provide adequate AC for mouse PET imaging. To construct the default MRAC ${\mu }$ maps, MR images were thresholded and segmented using ASIPRO software (Siemens Molecular Imaging), which defined the mouse body region as tissue with a uniform linear attenuation coefficient ( ${\mu }$ ) of $0.095~\hbox{cm}^{ - 1}$ , and the background and lungs as air, with a ${\mu }$ value of $0~\hbox{cm}^{ - 1}$ . To correct for the misassignment of the lungs as air, two further MRAC ${\mu }$ maps were tested: 1) MRAC (tissue) approach, which changed the lung region designation from air to tissue ( ${\mu } = 0.095~\hbox{cm}^{ - 1}$ ) and 2) MRAC (lung) approach, which treated the lungs as an additional tissue class, with a ${\mu }$ value of $0.032~\hbox{cm}^{ - 1}$ . All ${\mu }$ maps were then forward projected to create attenuation sinograms for image reconstruction. Standard uptake value (SUV) maps of the myocardium were derived for 10 mice with and without AC applied using gold standard transmission scans (TXAC), the 3 MRAC methods and PET emission scans (EmAC). All AC methods produced significantly different myocardial SUVs to those produced without AC when compared across the mouse group ( ${\rm p} ). Similar ( $ ) SUV were derived with all AC methods, with the best agreement to TXAC achieved using the MRAC (tissue) method, giving a mean difference of $0.9{\pm }2.4\% $ in myocardial SUV when compared across all mice. SUV differences of up to 40%, however, were seen in areas adjacent to the RF coil in images produced using all AC methods, except for TXAC. A 2 class MRAC approach can therefore provide acceptable AC for myocardial imaging in mice, although additional CT templates of coils and animals beds would be recommended to further improve image quantification.

3D Ti-6Al-4V constructs produced by additive manufacturing induce osteoblast differentiation in vitro and regenerate bone in vivo without exogenous factors

3D Ti-6Al-4V constructs produced by additive manufacturing induce osteoblast differentiation in vitro and regenerate bone in vivo without exogenous factors

A Default Normal Chest CT Structured Reporting Field for Coronary Calcifications Does Not Cause Excessive False-Negative Reporting

PurposeThe aim of this study was to compare the accuracy of coronary atherosclerosis reporting before and after the implementation of a structured reporting chest CT template. MethodsA noncardiac, noncontrast chest CT structured reporting template was developed and mandated for department-wide use at a large academic center. The template included the statement “There are no coronary artery calcifications.” All noncardiac, noncontrast chest CT examinations reported over 3 days, 1 month after template implementation (structured template group), and from a 3-day period 1 year prior (control group) were retrospectively collected. Final radiology reports were reviewed and designated positive or negative for coronary calcifications. CT images were reviewed in consensus by 2 radiologists, who scored each case for the presence or absence of coronary calcifications, blinded to the original report. Statistical analysis was performed using Pearson χ2 and Fisher exact tests. ResultsSixty-five percent (69 of 106) of structured template group and 58% (62 of 106) of control group cases had coronary calcifications. Reports from the structured template group were more likely to correctly state the presence or absence of coronary atherosclerosis compared with those from the control group (96.2% vs 85.8%; odds ratio, 4.2; 95% confidence interval, 1.3–13.1; P = .008). Structured template group reports were less likely to be falsely negative compared with control group reports (3.8% vs 11.7%; odds ratio, 3.4; 95% confidence interval, 1.0–10.8; P = .03). ConclusionsImplementing a structured reporting template improves reporting accuracy of coronary calcifications.

Googling Stroke ASPECTS to Determine Disability: Exploratory Analysis from VISTA-Acute Collaboration.

The summed Alberta Stroke Program Early CT Score (ASPECTS) is useful for predicting stroke outcome. The anatomical information in the CT template is rarely used for this purpose because traditional regression methods are not adept at handling collinearity (relatedness) among brain regions. While penalized logistic regression (PLR) can handle collinearity, it does not provide an intuitive understanding of the interaction among network structures in a way that eigenvector method such as PageRank can (used in Google search engine). In this exploratory analysis we applied graph theoretical analysis to explore the relationship among ASPECTS regions with respect to disability outcome. The Virtual International Stroke Trials Archive (VISTA) was searched for patients who had infarct in at least one ASPECTS region (ASPECTS ≤9, ASPECTS=10 were excluded), and disability (modified Rankin score/mRS). A directed graph was created from a cross correlation matrix (thresholded at false discovery rate of 0.01) of the ASPECTS regions and demographic variables and disability (mRS>2). We estimated the network-based importance of each ASPECTS region by comparing PageRank and node strength measures. These results were compared with those from PLR. There were 185 subjects, average age 67.5± 12.8 years (55% Males). Model 1: demographic variables having no direct connection with disability, the highest PageRank was M2 (0.225, bootstrap 95% CI 0.215-0.347). Model 2: demographic variables having direct connection with disability, the highest PageRank were M2 (0.205, bootstrap 95% CI 0.194-0.367) and M5 (0.125, bootstrap 95% CI 0.096-0.204). Both models illustrate the importance of M2 region to disability. The PageRank method reveals complex interaction among ASPECTS regions with respects to disability. This approach may help to understand the infarcted brain network involved in stroke disability.