Normal Template Research Articles

Quantitative evaluation of striatal uptake ratios using an adaptive template registration method for 123I-ioflupane dopamine transporter SPECT.

123I-FP-CIT (123I-Ioflupane) SPECT shows strong accumulation in the striatum, but morphological standardization is challenging due to low accumulation outside the striatum, particularly in subjects with marked striatal decline. In this study, morphological standardization without MRI was achieved using the adaptive template registration (ATR) method to create a subject-specific optimized template with weighted images of normal-type and egg-shape-type templates. The accuracy of a quantitative method for calculating the ratio with nonspecific accumulation in the occipital lobe was evaluated by placing voxels-of-interest (VOI) on standardized images, particularly targeting the striatum. The average images of eight subjects, demonstrating normal-type and egg-shape-type tracer accumulation in 123I-Ioflupane SPECT, were utilized as normal and disease templates, respectively. The study included 300 subjects that underwent both 123I-Ioflupane SPECT and MRI for the diagnosis of suspected Parkinson's disease or for exclusion diagnosis. Morphological standardization of SPECT images using structural MRI (MRI-based method) was considered the standard of truth (SOT). Three morphological standardizations without MRI were conducted. The first involved conventional morphological standardization using a normal template (fixed template method), the second employed the ATR method, with a weighted template, and the third used the split-ATR method, processing the left and right striatum separately to address asymmetrical accumulation. VOIs were set on the striatum, caudate, putamen as regions of specific accumulation, and on the occipital lobe as a reference region for nonspecific accumulation. Results showed significant and robust linearity in the striatal accumulation ratios for all templates when compared with the occipital lobe accumulation ratio when using the MRI-based method. Comparing intra-class correlations for different linearities, the ATR method and split-ATR method demonstrated higher linearity in the striatum, caudate, and putamen. The split-ATR method showed similar improvements, although more linearity than some of the ATR methods; the effectiveness of the Split-ATR method may vary by image quality, and further validation of its effectiveness in diverse asymmetric accumulation cases seemed warranted. The use of optimized templates, such as the ATR and split-ATR methods, improved reproducibility in fully automated processing and demonstrated superior linearity compared to that of MRI-based method, in the ratio to the occipital lobe. The ATR method, which enables morphological standardization when using SPECT images only, proved highly reproducible for clinical quantitative analysis of striatal accumulation, facilitating its clinical use.

Posterior Wall Fragments in Acetabular Both-Column Fractures: Morphology, Type, and the Significance of its Projection.

Most both-column acetabular fractures are combined with posterior wall fragments. However, the morphology of this posterior wall is varied, and how to fix this posterior wall remains a controversial topic. To investigate the morphological characteristics of posterior wall fragments of both-column acetabular fractures and select corresponding fixation methods. Data from 352 patients with acetabular fractures admitted to the level one trauma centre in our hospital between January 2006 and December 2022 were collected. The morphology of posterior wall fragments was observed and analyzed in 83 cases of both-column acetabular fractures and classified according to the consistency of posterior wall morphology. A fracture map of the posterior wall was created on a normal template according to the three morphological types of posterior wall fragments. Finally, the high-incidence area of the posterior wall fracture was projected onto the iliac fossa and the medial side of the posterior column to guide the fixation of the posterior wall fragment using the anterior intrapelvic approach. Fractures were divided into four types: I, large posterior wall fragment which was high in the ilium bone (34 cases, 41.0%); II, posterior wall fragment in the acetabular parietal region (18 cases, 21.7%); III, posterior wall marginal fracture (10 cases, 12.0%); and IV, non-combined posterior wall fracture (21 cases, 25.3%). The most common morphologies of the posterior wall fragments of the first two types were mapped and projected onto the anterior iliac inner plate and medial side of the posterior column, where the corresponding area could be used to guide the insertion of the internal fixation. Both-column acetabular fractures combined with posterior wall fractures can be divided into four types according to the morphology of the posterior wall fragment. Understanding the corresponding three-dimensional morphology and projection position of different types of these fragments can help surgeons determine the position and orientation of internal fixation of posterior wall fractures.

Normal cohorts in automated brain atrophy estimation: how many healthy subjects to include?

ObjectivesThis study investigates the influence of normal cohort (NC) size and the impact of different NCs on automated MRI-based brain atrophy estimation.MethodsA pooled NC of 3945 subjects (NCpool) was retrospectively created from five publicly available cohorts. Voxel-wise gray matter volume atrophy maps were calculated for 48 Alzheimer’s disease (AD) patients (55–82 years) using veganbagel and dynamic normal templates with an increasing number of healthy subjects randomly drawn from NCpool (initially three, and finally 100 subjects). Over 100 repeats of the process, the mean over a voxel-wise standard deviation of gray matter z-scores was established and plotted against the number of subjects in the templates. The knee point of these curves was defined as the minimum number of subjects required for consistent brain atrophy estimation. Atrophy maps were calculated using each NC for AD patients and matched healthy controls (HC). Two readers rated the extent of mesiotemporal atrophy to discriminate AD/HC.ResultsThe maximum knee point was at 15 subjects. For 21 AD/21 HC, a sufficient number of subjects were available in each NC for validation. Readers agreed on the AD diagnosis in all cases (Kappa for the extent of atrophy, 0.98). No differences in diagnoses between NCs were observed (intraclass correlation coefficient, 0.91; Cochran’s Q, p = 0.19).ConclusionAt least 15 subjects should be included in age- and sex-specific normal templates for consistent brain atrophy estimation. In the study’s context, qualitative interpretation of regional atrophy allows reliable AD diagnosis with a high inter-reader agreement, irrespective of the NC used.Clinical relevance statementThe influence of normal cohorts (NCs) on automated brain atrophy estimation, typically comparing individual scans to NCs, remains largely unexplored. Our study establishes the minimum number of NC-subjects needed and demonstrates minimal impact of different NCs on regional atrophy estimation.Key Points• Software-based brain atrophy estimation often relies on normal cohorts for comparisons.• At least 15 subjects must be included in an age- and sex-specific normal cohort.• Using different normal cohorts does not influence regional atrophy estimation.

Template-based Feature Aggregation Network for industrial anomaly detection

Industrial anomaly detection plays a crucial role in ensuring product quality control. Therefore, proposing an effective anomaly detection model is of great significance. While existing feature-reconstruction methods have demonstrated excellent performance, they face challenges with shortcut learning, which can lead to undesirable reconstruction of anomalous features. To address this concern, we present a novel feature-reconstruction model called the Template-based Feature Aggregation Network (TFA-Net) for anomaly detection via template-based feature aggregation. Specifically, TFA-Net first extracts multiple hierarchical features from a pre-trained convolutional neural network for a fixed template image and an input image. Instead of directly reconstructing input features, TFA-Net aggregates them onto the template features, effectively filtering out anomalous features that exhibit low similarity to normal template features. Next, TFA-Net utilizes the template features that have already fused normal features in the input features to refine feature details and obtain the reconstructed feature map. Finally, the defective regions can be located by comparing the differences between the input and reconstructed features. Our template-based feature aggregation schema yields a nontrivial and meaningful feature reconstruction task. The simple, yet efficient, TFA-Net exhibits state-of-the-art detection performance on various real-world industrial datasets. Additionally, it fulfills the real-time demands of industrial scenarios, rendering it highly suitable for practical applications in the industry.

Comparison of Chest Radiograph Captions Based on Natural Language Processing vs Completed by Radiologists

Artificial intelligence (AI) can interpret abnormal signs in chest radiography (CXR) and generate captions, but a prospective study is needed to examine its practical value. To prospectively compare natural language processing (NLP)-generated CXR captions and the diagnostic findings of radiologists. A multicenter diagnostic study was conducted. The training data set included CXR images and reports retrospectively collected from February 1, 2014, to February 28, 2018. The retrospective test data set included consecutive images and reports from April 1 to July 31, 2019. The prospective test data set included consecutive images and reports from May 1 to September 30, 2021. A bidirectional encoder representation from a transformers model was used to extract language entities and relationships from unstructured CXR reports to establish 23 labels of abnormal signs to train convolutional neural networks. The participants in the prospective test group were randomly assigned to 1 of 3 different caption generation models: a normal template, NLP-generated captions, and rule-based captions based on convolutional neural networks. For each case, a resident drafted the report based on the randomly assigned captions and an experienced radiologist finalized the report blinded to the original captions. A total of 21 residents and 19 radiologists were involved. Time to write reports based on different caption generation models. The training data set consisted of 74 082 cases (39 254 [53.0%] women; mean [SD] age, 50.0 [17.1] years). In the retrospective (n = 8126; 4345 [53.5%] women; mean [SD] age, 47.9 [15.9] years) and prospective (n = 5091; 2416 [47.5%] women; mean [SD] age, 45.1 [15.6] years) test data sets, the mean (SD) area under the curve of abnormal signs was 0.87 (0.11) in the retrospective data set and 0.84 (0.09) in the prospective data set. The residents' mean (SD) reporting time using the NLP-generated model was 283 (37) seconds-significantly shorter than the normal template (347 [58] seconds; P < .001) and the rule-based model (296 [46] seconds; P < .001). The NLP-generated captions showed the highest similarity to the final reports with a mean (SD) bilingual evaluation understudy score of 0.69 (0.24)-significantly higher than the normal template (0.37 [0.09]; P < .001) and the rule-based model (0.57 [0.19]; P < .001). In this diagnostic study of NLP-generated CXR captions, prior information provided by NLP was associated with greater efficiency in the reporting process, while maintaining good consistency with the findings of radiologists.

Multiple expressions of “expert” abnormality gist in novices following perceptual learning

With a brief half-second presentation, a medical expert can determine at above chance levels whether a medical scan she sees is abnormal based on a first impression arising from an initial global image process, termed “gist.” The nature of gist processing is debated but this debate stems from results in medical experts who have years of perceptual experience. The aim of the present study was to determine if gist processing for medical images occurs in naïve (non-medically trained) participants who received a brief perceptual training and to tease apart the nature of that gist signal. We trained 20 naïve participants on a brief perceptual-adaptive training of histology images. After training, naïve observers were able to obtain abnormality detection and abnormality categorization above chance, from a brief 500 ms masked presentation of a histology image, hence showing “gist.” The global signal demonstrated in perceptually trained naïve participants demonstrated multiple dissociable components, with some of these components relating to how rapidly naïve participants learned a normal template during perceptual learning. We suggest that multiple gist signals are present when experts view medical images derived from the tens of thousands of images that they are exposed to throughout their training and careers. We also suggest that a directed learning of a normal template may produce better abnormality detection and identification in radiologists and pathologists.

DNA Polymerase ζ without the C-Terminus of Catalytic Subunit Rev3 Retains Characteristic Activity, but Alters Mutation Specificity of Ultraviolet Radiation in Yeast.

DNA polymerase ζ (pol ζ) plays a central role in replicating damaged genomic DNA. When DNA synthesis stalls at a lesion, it participates in translesion DNA synthesis (TLS), which helps replication proceed. TLS prevents cell death at the expense of new mutations. The current model indicates that pol ζ-dependent TLS events are mediated by Pol31/Pol32 pol ζ subunits, which are shared with replicative polymerase pol δ. Surprisingly, we found that the mutant rev3-ΔC in yeast, which lacks the C-terminal domain (CTD) of the catalytic subunit of pol ζ and, thus, the platform for interaction with Pol31/Pol32, retains most pol ζ functions. To understand the underlying mechanisms, we studied TLS in normal templates or templates with abasic sites in vitro in primer extension reactions with purified four-subunit pol ζ versus pol ζ with Rev3-ΔC. We also examined the specificity of ultraviolet radiation (UVR)-induced mutagenesis in the rev3-ΔC strains. We found that the absence of Rev3 CTD reduces activity levels, but does not alter the basic biochemical properties of pol ζ, and alters the mutation spectrum only at high doses of UVR, alluding to the existence of mechanisms of recruitment of pol ζ to UVR-damaged sites independent of the interaction of Pol31/Pol32 with the CTD of Rev3.

Epileptic-seizure onset detection using PARAFAC model with cross-wavelet transformation on multi-channel EEG.

Finding components from multi-channel EEG signal for localizing and detection of onset of seizure, is a new approach in biomedical signal analysis. Tensor-based approaches are utilized to fit the components into multi-dimensional arrays in recent works. We initially decompose EEG signals into Beta band using discrete wavelet transform (DWT). We compare patient templates with normal template for cross-wavelet analysis to obtain Wavelet cross spectrum (WCS) and Wavelet cross coherence coefficients. Next we apply parallel factorization (PARAFAC) modeling, a three-way tensor-based representation in channel, frequency and time-points dimensions on features. Finally, we utilize the ensemble classifier for detecting seizure-free, onset and seizure classes. The clinical dataset for this work comprises of 5 normal subjects and 6 epileptiform patients. The classification performances of WCS features on PARAFAC model for Seizure detection using Ensemble Bagged-Trees classifier obtains 82.21% accuracy, while for Wavelet Coherence features, it provides higher 84.76% accuracy. The results have been compared with well-known Fine Gaussian SVM, Weighted KNN and Ensemble Subspace KNN classifiers. The aim is to analyze data over three dimensions namely, time, frequency and space (channels). This EEG based analysis is significant and effective as an automatic method for detection of seizure before its actual manifestation.

A Fast Template Matching Scheme of Visible and Infrared Image Under Occluded Scenarios

A fast and robust template matching scheme, called Matching by Slice Transform Matrix Mapping (MSTMM), is proposed for the matching difficulty under occluded scenarios caused by nonlinear intensity differences and structure differences between visible and thermal infrared images. The first step in the MSTMM scheme was to extract information about the distribution of pixels with the same gray level through the developed Expanded Slice Transform with Adaptive Gray Level (EST-AGL). After completing the construction of the EST-AGL matrix for all image patches, different EST-AGL matrices were mapped to different integers or floats through the traditional special integer mapping mechanism or the neural network mapping mechanism. Finally, template matching between visible and thermal infrared images was achieved by evaluating the similarity of correlation mapping surface images through the Normalized Cross Correlation (NCC) algorithm. The proposed EST-AGL method can overcome the nonlinear intensity differences between visible and thermal infrared images by extracting the structural features of the image. The mapping mechanism of the MSTMM scheme can reduce the structural differences between the normal template image and the query image under an occluded scenario by increasing the similarity between the normal image patches and the image patches with occlusion. The proper mapping mechanism ensures the high performance of the MSTMM scheme by using only the simple NCC algorithm instead of other time-consuming anti-occlusion dense feature algorithms in the similarity evaluation stage. The three main experimental results of the MSTMM scheme are as follows: (1) the scheme of MSTMM can achieve template matching in only 0.015 seconds when a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$64\times 64$ </tex-math></inline-formula> template image slides on a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$256\times 256$ </tex-math></inline-formula> query image on a hardware platform with limited resources; (2) the matching success rate of the MSTMM scheme can reach up to 75% among 2107 experimental samples; and (3) the neural network training in the neural network mapping mechanism only takes at least 104.4 seconds on the CPU.

Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization.

Introduction: [18F]-FDG PET is a widely used imaging modality that visualizes cellular glucose uptake and provides functional information on the metabolic state of different tissues in vivo. Various quantification methods can be used to evaluate glucose metabolism in the brain, including the cerebral metabolic rate of glucose (CMRglc) and standard uptake values (SUVs). Especially in the brain, these (semi-)quantitative measures can be affected by several physiological factors, such as blood glucose level, age, gender, and stress. Next to this inter- and intra-subject variability, the use of different PET acquisition protocols across studies has created a need for the standardization and harmonization of brain PET evaluation. In this study we present a framework for statistical voxel-based analysis of glucose uptake in the rat brain using histogram-based intensity normalization.Methods: [18F]-FDG PET images of 28 normal rat brains were coregistered and voxel-wisely averaged. Ratio images were generated by voxel-wisely dividing each of these images with the group average. The most prevalent value in the ratio image was used as normalization factor. The normalized PET images were voxel-wisely averaged to generate a normal rat brain atlas. The variability of voxel intensities across the normalized PET images was compared to images that were either normalized by whole brain normalization, or not normalized.To illustrate the added value of this normal rat brain atlas, 9 animals with a striatal hemorrhagic lesion and 9 control animals were intravenously injected with [18F]-FDG and the PET images of these animals were voxel-wisely compared to the normal atlas by group- and individual analyses.Results: The average coefficient of variation of the voxel intensities in the brain across normal [18F]-FDG PET images was 6.7% for the histogram-based normalized images, 11.6% for whole brain normalized images, and 31.2% when no normalization was applied. Statistical voxel-based analysis, using the normal template, indicated regions of significantly decreased glucose uptake at the site of the ICH lesion in the ICH animals, but not in control animals.Conclusion: In summary, histogram-based intensity normalization of [18F]-FDG uptake in the brain is a suitable data-driven approach for standardized voxel-based comparison of brain PET images.

In Vitro Experimental Study of the Effect of Adjusting the Guide Sleeve Height and Using a Visual Direction-Indicating Guide on Implantation Accuracy

We used a single-variable method to analyze the influence of the guide sleeve height of a conventional template on implantation accuracy invitro and improve the function of short-sleeve templates by adding a visual direction-indicating guide (VDING). We created 100 copies of a volunteer's dentition plaster model. The normal template (NT) and the VDING template (VT) were made with guide sleeves 2, 5, 8, and 10mm in height. Additionally, a freehand (FH) group and a group with an FH-based visual guide were used. Simulated implantation in an emulated head model was performed in each group. After surgery, cone-beam computed tomography images of the plaster were used for registration, and the accuracy was compared among the groups. When the NT sleeve height was 5mm or less, increased deviation was found, and the results for some of the accuracy indicators were not different from those in the FH group. The accuracy of sleeves 5mm or less in height was better in the VT group than in the NT or FH group. Use of the NT with a guide sleeve height of 5mm or less can introduce large deviations in implantation, which can be prevented by the VT. However, the use of the VDING alone was not sufficient.

572-P: Lower Insulin Secretion Is Associated with Parahippocampal Gyrus Atrophy in Elderly Patients with Type 2 Diabetes Mellitus

Objectives: Alzheimer's disease (AD) is increasingly recognized as an important comorbidity of diabetes mellitus and is often accompanied by parahippocampal gyrus atrophy (PGA). But the associations between diabetes-related parameters and PGA are not well known. Voxel-based morphometry (VBM) recently became a popular tool for the early diagnosis of AD. One of the clinically useful tools using magnetic resonance imaging (MRI) is the Voxel-based Specific Regional Analysis system for AD (VSRAD) that evaluates the degree of volume loss of parahippocampal gyrus by comparing grey matter with the original normal database template. We examined the risk factors for PGA by using VSRAD in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 137 patients aged ≥ 50 years with T2DM (mean age 67.8 ± 9.8 years) underwent brain MRI scans and comprehensive health examinations. Volume of interest (VOI) was measured using VSRAD for each patient. We examined associations between the severity of VOI atrophy and diabetes-related parameters such as HbA1c, fasting plasma glucose (FPG), C-peptide (CPR) index (plasma CPR/FPG x 100) and Hasegawa Dementia Scale-Revised (HDS-R) score, consisting of 9 simple questions with a maximum score of 30. PGA was defined as the VOI atrophy more than 1.0. Results: Mean HbA1c was 9.3 ± 2.2%. HDS-R (median (range)) score was 28 (12 - 30). CPR index (median (range)) was 1.29 (0.03 - 8.88). The severity of VOI atrophy was more than 1.0 in 36 patients. The VOI atrophy was negatively correlated with HDS-R score (R = - 0.261, p &amp;lt; 0.02). By a using multivariate logistic regression analysis, age (OR 1.08, 95% CI 1.03 - 1.14) and CPR index (OR 0.477, 95% CI 0.233 - 0.977) were significantly associated with PGA. Conclusions: The HDS-R score was significantly correlated with the VOI atrophy. Older age and lower insulin secretion were significantly associated with PGA in patients with T2DM. Disclosure Y. Adachi: None. K. Ota: None. R. Ishii: None. K. Cho: None. Y. Hiramatsu: None. S. Masuda: None. S. Koseki: None. T. Hayashi: None. N. Komatsu: None. E. Ueda: None. Y. Mizuguchi: None. I. Minami: None. T. Yamada: None. T. Watanabe: None.

Modified drilling template for placement of cervical anterior transpedicular screws

Objective To evaluate the accuracy in placement of cervical anterior transpedicular screws (ATPS) under the guidance of our modified drilling template. Methods Eight wet cadaveric specimens of adult cervical spine, 4 male and 4 female ones, were used for this experiment. Data of CT thin layer scanning of the cervical specimens in DICOM format were imported into software Mimics 17.0. After 3D models of the cervical vertebrae were reconstructed, the optimal trajectory was designed for ATPS placement in the transparent mode of the 3D models. Normal and our modified drilling templates for ATPS placement were designed and manufactured by 3D printing. The 2 kinds of drilling templates were used to assist ATPS placement onto one cervical vertebra, with laterality randomized. Altogether 64 pieces of ATPS were placed, with 32 ones for each drilling template. Postoperative CT scanning was conducted to evaluate the accuracy in ATPS placement. The 2 kinds of ATPS template were compared in terms of the deviations between actual and ideal trajectories in direction (caudal-angle and extroversive-angle) and position (X and Y axes) of the entry point. Results Our modified drilling template led to one screw penetrating the pedicle cortical bone while the normal drilling template led to 4 screws penetrating the pedicle cortical bone, yielding an accuracy rate of 96.9% and of 87.5% respectively. The extroversive-angle deviation (0.72°±0.69°), caudal-angle deviation (0.91°±0.70°), X axis shift (0.53±0.40 mm) and Y axis shift (0.54±0.42 mm) related to the modified template were all significantly smaller than those related to the normal template (1.16°±0.70°, 1.49°±0.68°, 0.88±0.40 mm, 1.22±0.42 mm, respectively) (P<0.05). Conclusion Compared with a normal ATPS template, our modified drilling template for ATPS may be advantageous in better fitness, greater stability, increased accuracy in screw placement, and protection of adjacent discs. Key words: Cervical vertebrae; Bone screws; 3D printing technology; Template

Disorganized Patterns of Sulcal Position in Fetal Brains with Agenesis of Corpus Callosum.

Fetuses with isolated agenesis of the corpus callosum (ACC) are associated with a broad spectrum of neurodevelopmental disability that cannot be specifically predicted in prenatal neuroimaging. We hypothesized that ACC may be associated with aberrant cortical folding. In this study, we determined altered patterning of early primary sulci development in fetuses with isolated ACC using novel quantitative sulcal pattern analysis which measures deviations of regional sulcal features (position, depth, and area) and their intersulcal relationships in 7 fetuses with isolated ACC (27.1 ± 3.8 weeks of gestation, mean ± SD) and 17 typically developing (TD) fetuses (25.7 ± 2.0 weeks) from normal templates. Fetuses with ACC showed significant alterations in absolute sulcal positions and relative intersulcal positional relationship compared to TD fetuses, which were not detected by traditional gyrification index. Our results reveal altered sulcal positional development even in isolated ACC that is present as early as the second trimester and continues throughout the fetal period. It might originate from altered white matter connections and portend functional variances in later life.

Quantitative Folding Pattern Analysis of Early Primary Sulci in Human Fetuses with Brain Abnormalities.

Aberrant gyral folding is a key feature in the diagnosis of many cerebral malformations. However, in fetal life, it is particularly challenging to confidently diagnose aberrant folding because of the rapid spatiotemporal changes of gyral development. Currently, there is no resource to measure how an individual fetal brain compares with normal spatiotemporal variations. In this study, we assessed the potential for automatic analysis of early sulcal patterns to detect individual fetal brains with cerebral abnormalities. Triplane MR images were aligned to create a motion-corrected volume for each individual fetal brain, and cortical plate surfaces were extracted. Sulcal basins were automatically identified on the cortical plate surface and compared with a combined set generated from 9 normal fetal brain templates. Sulcal pattern similarities to the templates were quantified by using multivariate geometric features and intersulcal relationships for 14 normal fetal brains and 5 fetal brains that were proved to be abnormal on postnatal MR imaging. Results were compared with the gyrification index. Significantly reduced sulcal pattern similarities to normal templates were found in all abnormal individual fetuses compared with normal fetuses (mean similarity [normal, abnormal], left: 0.818, 0.752; P < .001; right: 0.810, 0.753; P < .01). Altered location and depth patterns of sulcal basins were the primary distinguishing features. The gyrification index was not significantly different between the normal and abnormal groups. Automated analysis of interrelated patterning of early primary sulci could outperform the traditional gyrification index and has the potential to quantitatively detect individual fetuses with emerging abnormal sulcal patterns.

Detection of minimal residual disease in childhood B-acute lymphoblastic leukemia by 4-color flowcytometry

Monitoring of minimal residual disease (MRD) is currently considered the most powerful predictor of outcome in acute lymphoblastic leukemia (ALL). Achievement of a negative MRD state assessed by multicolor flowcytometry (MFC) is an important predictor of disease-free survival (DFS) and overall survival (OS) in ALL patients. We sought to determine whether panels of antibodies combination are more suitable for detection of MRD in Childhood ALL. Eighty-four (84) patients with ALL (B-lineage subtype) were enrolled in this study. Normal template for B cell precursors was established in 15 controlparticipants using 4-four panels of monoclonal Antibodies (Mo Abs),{CD22, CD45, CD58 and CD97 in combination with CD10, CD19, CD34}. At diagnosis, CD22 exhibited the lowest incidence of expression in only 50% of all patients, while CD45, CD58, and CD97 were expressed in 80.9, 59.5 and 92.8%, respectively. Analysis of MRD was performed for each Mo Abs combination at day 0 and day 14 post-induction of chemotherapy by 4-color (FCM). The incidence of MRD was 61.9, 70.6, 60.0 and 55.1% for CD22, CD45, CD58 and CD97, respectively. In B-ALL patients, (CD10/CD19/CD34/CD45)+(CD10/CD19/CD34/CD97) represented the highest incidence of expression of leukemic cells markers with a significant correlation with blasts count, suggesting that these are more specific for MRD detection. Also FCM is relatively cost effective for detection of MRD in ALL patients and its applicability in routine leukemia lab is valuable. MRD evaluation at the end of the induction therapy (i.e. day 35 or 42 according to the different schedules) is advised. Also, Ig/T cell receptor gene rearrangements and gene fusions analyzed by polymerase chain reaction (PCR) are preferred.

Detection of Minimal Residual Disease in Childhood B-Acute Lymphoblastic Leukemia by 4-Color Flow Cytometry

Monitoring of minimal residual disease (MRD) is today considered the most powerful predictor of outcome in acute leukemias, including acute lymphoblastic leukemia (ALL). The study aimed to determine whether panel of antibodies combination are more suitable than others for detection of MRD in Childhood B-lineage ALL. Eighty four (84) patients of ALL (B-lineage subtype) were enrolled in this study. Normal template for B. Cell precursors were been established in 15 control Patients by using 4 panels of monoclonal Abs (Mo Abs), {CD22, CD45, CD58 and CD97 in combination with CD10, CD19, CD34}. At diagnosis CD22 having the lowest incidence expression between the patients in 50% only, but CD45, CD58, and CD97 were expressed in 80.9%, 52.3% and 92.8% respectively. Analysis of MRD was performed for each Mo Abs combination at day 0 and day 14 post induction of chemotherapy by 4-color flow cytometer (FCM). The incidence of MRD were 61.9%, 70.6%, 60.0% and 55.5% for CD22,CD45,CD58 and CD97 respectively. Seventy-six from total 84 cases studied (90.0%) had at least one LAIP. Of these, 22 (29.0%) had only one LAIP and 54 cases (71.0%) had ≥ 2 LAIPS Conclusion: In the B-ALL patients (CD10/CD19/CD34/CD45)+ and (CD10/CD19/CD34/CD97)+, represented the highest incidence markers expression of leukemic cells with a significant correlation with blasts count, so it's the more specific for MRD detection.

Fully Automated Quantification of the Striatal Uptake Ratio of [(99m)Tc]-TRODAT with SPECT Imaging: Evaluation of the Diagnostic Performance in Parkinson's Disease and the Temporal Regression of Striatal Tracer Uptake.

Purpose. We aimed at improving the existing methods for the fully automatic quantification of striatal uptake of [99mTc]-TRODAT with SPECT imaging. Procedures. A normal [99mTc]-TRODAT template was first formed based on 28 healthy controls. Images from PD patients (n = 365) and nPD subjects (28 healthy controls and 33 essential tremor patients) were spatially normalized to the normal template. We performed an inverse transform on the predefined striatal and reference volumes of interest (VOIs) and applied the transformed VOIs to the original image data to calculate the striatal-to-reference ratio (SRR). The diagnostic performance of the SRR was determined through receiver operating characteristic (ROC) analysis. Results. The SRR measured with our new and automatic method demonstrated excellent diagnostic performance with 92% sensitivity, 90% specificity, 92% accuracy, and an area under the curve (AUC) of 0.94. For the evaluation of the mean SRR and the clinical duration, a quadratic function fit the data with R 2 = 0.84. Conclusions. We developed and validated a fully automatic method for the quantification of the SRR in a large study sample. This method has an excellent diagnostic performance and exhibits a strong correlation between the mean SRR and the clinical duration in PD patients.

Vervet MRI atlas and label map for fully automated morphometric analyses.

Currently available non-human primate templates typically require input of a skull-stripped brain for structural processing. This can be a manually intensive procedure, and considerably limits their utility. The purpose of this study was to create a vervet MRI population template, associated tissue probability maps (TPM), and a label atlas to facilitate true fully automated Magnetic Resonance Imaging (MRI) structural analyses for morphometric analyses. Structural MRI scans of ten vervet monkeys (Chlorocebus aethiops) scanned at three time points were used in this study. An unbiased population average template was created using a symmetric diffeomorphic registration (SyN) procedure. Skull stripping, segmentation, and label map generation were performed using the publically available rhesus INIA19 MRI template and NeuroMap label atlas. A six-class TPM and a six-layer two-class normalization template was created from the vervet segmentation for use within the Statistical Parametric Mapping (SPM) framework. Fully automated morphologic processing of all of the vervet MRI scans was then performed using the vervet TPM and vervet normalization template including skull-stripping, segmentation and normalization. The vervet template creation procedure resulted in excellent skull stripping, segmentation, and NeuroMap atlas labeling with 720 structures successfully registered. Fully automated processing was accomplished for all vervet scans, demonstrating excellent skull-stripping, segmentation, and normalization performance. We describe creation of an unbiased vervet structural MRI population template and atlas. The template includes an associated six-class TPM and DARTEL six-layer two-class normalization template for true fully automated skull-stripping, segmentation, and normalization of vervet structural T1-weighted MRI scans. We provide the most detailed vervet label atlas currently available based on the NeuroMaps atlas with 720 labels successfully registered. We additionally describe a novel method for atlas label generation that capitalizes on previous work in this area using high-dimensional highly accurate image matching procedures for inter-species morphologic normalization.

Elaboration of the SPM template for the standardization of SPECT images with 123I-Ioflupane

PurposeStatistical parametric mapping (SPM) is a widely used procedure for normalization of functional images. The aim of this study is the development of a normalization template of 123I-Ioflupane SPECT-imaging DaTSCAN®, GE Healthcare), not available in SPM5, and to validate it by comparing with other quantification methods. Material and methodsIn order to write the template we retrospectively selected 26 subjects who had no evidence of nigrostriatal degeneration and whose age distribution was similar to that of the patients in the usual practice of our Department: 2 subjects (7.6%) were <35 years, 9 between 35 and 65 years (34.6%) and 15>65 years (57.7%). All the studies were normalized with the T1-template, available in SPM5, and an average value of the image was obtained for each voxel. For validation we analyzed 60 patients: 30 with idiopathic Parkinson's disease patients (iPD) with right involvement (66.83±12.20 years) and 30 with essential tremor patients (ET) (67.27±8.33 years). Specific uptake rates (SUR) of different striatal regions were compared after image normalization with our template and the application of a semiautomated VOIs-map was created with Analyze v9.0 (©BIR, Mayo Clinic), against two quantification methods: a) manual adjustment of a ROIs-map drawn in Analyze, and b) semi-automated method (HERMES-BRASS) with normalization and implementation of VOIs-map. ResultsNo statistically significant differences in the iPD/ET discriminatory capacity among the three methods analyzed were observed (p<0.001). The correlation of SUR after normalization with our “template” was higher than that obtained by method b) (R>0.871, p<0.001). This difference was greater in patients with PD. ConclusionsOur study demonstrates the efficacy of our SPM “template” for 123I-Ioflupane SPECT-imaging, obtained from normalization with “T1-template”.