Integrated Software Architecture-Based Reliability Prediction for IT Systems

With the increasing importance of reliability in business and industrial IT systems, new techniques for architecture-based software reliability prediction are becoming an integral part of the development process. This dissertation thesis introduces a novel reliability modelling and prediction technique that considers the software architecture with its component structure, control and data flow, recovery mechanisms, its deployment to distributed hardware resources and the system\u27s usage profile

Integrated Software Architecture-Based Reliability Prediction for IT Systems

With the increasing importance of reliability in business and industrial IT systems, new techniques for architecture-based software reliability prediction are becoming an integral part of the development process. This dissertation thesis introduces a novel reliability modelling and prediction technique that considers the software architecture with its component structure, control and data flow, recovery mechanisms, its deployment to distributed hardware resources and the system´s usage profile

Patient-specific image-based bone marrow dosimetry in Lu-177-[DOTA(0),Tyr(3)]-Octreotate and Lu-177-DKFZ-PSMA-617 therapy: investigation of a new hybrid image approach

Background: The bone marrow (BM) is a main organ at risk in Lu-177-PSMA-617 therapy of prostate cancer and Lu-177-Octreotate therapy of neuroendocrine tumours. BM dosimetry is challenging and time-consuming, as different sequential quantitative measurements must be combined. The BM absorbed dose from the remainder of the body (ROB) can be determined from sequential whole-body planar (WB-P) imaging, while quantitative Lu-177-SPECT allows for more robust tumour and organ absorbed doses. The aim was to investigate a time-efficient and patient-friendly hybrid protocol (HP) for the ROB absorbed dose to the BM. It combines three abdominal quantitative SPECT (QSPECT) scans with a single WB-P acquisition and was compared with a reference protocol (RP) using sequential WB-P in combination with sequential QSPECT images. We investigated five patients receiving 7. 4 GBq Lu-177-Octreotate and five patients treated with 3.7 GBq Lu-177-PSMA-617. Each patient had WB-P and abdominal SPECT acquisitions 24 (+ CT), 48, and 72 h post-injection. Blood samples were drawn 30 min, 80 min, 24 h, 48 h, and 72 h post-injection. BM absorbed doses from the ROB were estimated from sequential WB-P images (RP), via a mono-exponential fit and mass-scaled organ-level S values. For the HP, a mono-exponential fit on the QSPECT data was scaled with the activity of one WB-P image acquired either 24, 48, or 72 h post-injection (HP24, HP48, HP72). Total BM absorbed doses were determined as a sum of ROB, blood, major organ, and tumour contributions. Results: Compared with the RP and for Lu-177-Octreotate therapy, median differences of the total BM absorbed doses were 13% (9-17%), 8% (4-15%), and 1% (0-5%) for the HP24, HP48, and HP72, respectively. For Lu-177-PSMA-617 therapy, total BM absorbed doses deviated 10% (2-20%), 3% (0-6%), and 2% (0-6%). Conclusion: For both Lu-177-Octreotate and Lu-177-PSMA-617 therapy, BM dosimetry via sequential QSPECT imaging and a single WB-P acquisition is feasible, if this WB-P image is acquired at a late time point (48 or 72 h post-injection). The reliability of the HP can be well accepted considering the uncertainties of quantitative Lu-177 imaging and BM dosimetry using standardised organ-level S values

3D Monte Carlo bone marrow dosimetry for Lu-177-PSMA therapy with guidance of non-invasive 3D localization of active bone marrow via Tc-99m-anti-granulocyte antibody SPECT/CT

Background: The bone marrow (BM) is a main risk organ during Lu-177-PSMA ligand therapy of metastasized castration-resistant prostate cancer (mCRPC) patients. So far, BM dosimetry relies on S values, which are pre-computed for reference anatomies, simplified activity distributions, and a physiological BM distribution. However, mCRPC patients may show a considerable bone lesion load, which leads to a heterogeneous and patient-specific activity accumulation close to BM-bearing sites. Furthermore, the patient-specific BM distribution might be significantly altered in the presence of bone lesions. The aim was to perform BM absorbed dose calculations through Monte Carlo (MC) simulations and to investigate the potential value of image-based BM localization. This study is based on 11 Lu-177-PSMA-617 therapy cycles of 10 patients (10 first cycles), who obtained a pre-therapeutic Ga-68-PSMA-11 PET/CT; quantitative Lu-177 SPECT acquisitions of the abdomen 24 (+CT), 48, and 72 h p.i.; and a Lu-177 whole-body planar acquisition at 24 h post-therapy. Patient-specific 3D volumes of interest were segmented from the Ga-68-PSMA-11 PET/CT, filled with activity information from the Lu-177 data, and imported into the FLUKA MC code together with the patient CT. MC simulations of the BM absorbed dose were performed assuming a physiological BM distribution according to the ICRP 110 reference male (MC1) or a displacement of active BM from the direct location of bone lesions (MC2). Results were compared with those from S values (SMIRD). BM absorbed doses were correlated with the decrease of lymphocytes, total white blood cells, hemoglobin level, and platelets. For two patients, an additional pre-therapeutic Tc-99m-anti-granulocyte antibody SPECT/CT was performed for BM localization. Results: Median BM absorbed doses were 130, 37, and 11 mGy/GBq for MC1, MC2, and SMIRD, respectively. Significant strong correlation with the decrease of platelet counts was found, with highest correlation for MC2 (MC1: r = − 0.63, p = 0.04; MC2: r = − 0.71, p = 0.01; SMIRD: r = − 0.62, p = 0.04). For both investigated patients, BM localization via Tc-99m-anti-granulocyte antibody SPECT/CT indicated a displacement of active BM from the direct location of lesions similar to model MC2 and led to a reduction in the BM absorbed dose of 40 and 41% compared to MC1. Conclusion: Higher BM absorbed doses were observed for MC-based models; however, for MC2, all absorbed doses were still below 2 Gy. MC1 resulted in critical values for some patients, but is suspected to yield strongly exaggerated absorbed doses by neglecting bone marrow displacement. Image-based BM localization might be beneficial, and future studies are recommended to support an improvement for the prediction of hematoxicities

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Models of Neuronal Stimulus-Response Functions: Elaboration, Estimation, and Evaluation

Rich, dynamic, and dense sensory stimuli are encoded within the nervous system by the time-varying activity of many individual neurons. A fundamental approach to understanding the nature of the encoded representation is to characterize the function that relates the moment-by-moment firing of a neuron to the recent history of a complex sensory input. This review provides a unifying and critical survey of the techniques that have been brought to bear on this effort thus far—ranging from the classical linear receptive field model to modern approaches incorporating normalization and other nonlinearities. We address separately the structure of the models; the criteria and algorithms used to identify the model parameters; and the role of regularizing terms or “priors.” In each case we consider benefits or drawbacks of various proposals, providing examples for when these methods work and when they may fail. Emphasis is placed on key concepts rather than mathematical details, so as to make the discussion accessible to readers from outside the field. Finally, we review ways in which the agreement between an assumed model and the neuron's response may be quantified. Re-implemented and unified code for many of the methods are made freely available

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification