Comparable effectiveness of 45- and 20-min post-infusion scalp cooling time in preventing paclitaxel-induced alopecia - a randomized controlled trial.

PURPOSE: Scalp cooling can prevent chemotherapy-induced alopecia (CIA). Previously, the post-infusion cooling time (PICT) could be successfully reduced in docetaxel-treated patients from 90 to 45 and 20 min. Therefore, it seems plausible that the PICT can be shortened for paclitaxel-treated patients as well. METHODS: Patients treated with weekly paclitaxel were included in this multi-centre trial and randomly assigned to a PICT of 45 or 20 min. The results were compared to a standard PICT of 90 min, derived from prospective collected data from the Dutch Scalp Cooling Registry. The primary endpoint was the percentage of patients who decide to not wear a wig or head covering. Secondary endpoints were the degree of CIA assessed with the Dean scale for assessment of hair loss; alopecia graded according to NCI CTC toxicity version 4.03 (CTCAE4.03); tolerance of scalp cooling and perceived distress of CIA. RESULTS: Ninety-one patients were enrolled in this study; 74 patients were evaluable for hair loss. Hair preservation was successful in 27 patients (75%) with a PICT of 45 min and in 31 patients (82%) with a PICT of 20 min. There was no difference in success rate with the standard PICT of 90 min (85%, p = 0.29). Similar success rates were seen when using the Dean scale and CTCAE assessment, with no differences between groups (p = 0.12 and p = 0.38). CONCLUSIONS: A 20 min PICT is as effective as 45 and 90 min to prevent weekly paclitaxel-induced alopecia and should be the new standard of care. TRIAL REGISTER: ClinicalTrials.gov Identifier: NCT03266185.

A computer-aided diagnosing system in the evaluation of thyroid nodules-experience in a specialized thyroid center.

BACKGROUND: The evaluation of thyroid nodules with ultrasonography has created a large burden for radiologists. Artificial intelligence technology has been rapidly developed in recent years to reduce the cost of labor and improve the differentiation of thyroid malignancies. This study aimed to investigate the diagnostic performance of a novel computer-aided diagnosing system (CADs: S-detect) for the ultrasound (US) interpretation of thyroid nodule subtypes in a specialized thyroid center. METHODS: Our study prospectively included 180 thyroid nodules that underwent ultrasound interpretation. The CADs and radiologist assessed all nodules. The ultrasonographic features of different subtypes were analyzed, and the diagnostic performances of the CADs and radiologist were compared. RESULTS: There were seven subtypes of thyroid nodules, among which papillary thyroid cancer (PTC) accounted for 50.6% and follicular thyroid carcinoma (FTC) accounted for 2.2%. Among all thyroid nodules, the CADs presented a higher sensitivity and lower specificity than the radiologist (90.5% vs 81.1%; 41.2% vs 83.5%); the radiologist had a higher accuracy than the CADs (82.2% vs 67.2%) for diagnosing malignant thyroid nodules. The accuracy of the CADs was not as good as that of the radiologist in diagnosing PTCs (70.9% vs 82.1%). The CADs and radiologist presented accuracies of 43.8% and 60.9% in identifying FTCs, respectively. CONCLUSIONS: The ultrasound CADs presented a higher sensitivity for identifying malignant thyroid nodules than experienced radiologists. The CADs was not as good as experienced radiologists in a specialized thyroid center in identifying PTCs. Radiologists maintained a higher specificity than the CADs for FTC detection.

Computer-Assisted Diagnosis System for Breast Cancer in Computed Tomography Laser Mammography (CTLM).

Computed tomography laser mammography (Eid et al. Egyp J Radiol Nucl Med, 37(1): p. 633-643, 1) is a non-invasive imaging modality for breast cancer diagnosis, which is time-consuming and challenging for the radiologist to interpret the images. Some issues have increased the missed diagnosis of radiologists in visual manner assessment in CTLM images, such as technical reasons which are related to imaging quality and human error due to the structural complexity in appearance. The purpose of this study is to develop a computer-aided diagnosis framework to enhance the performance of radiologist in the interpretation of CTLM images. The proposed CAD system contains three main stages including segmentation of volume of interest (VOI), feature extraction and classification. A 3D Fuzzy segmentation technique has been implemented to extract the VOI. The shape and texture of angiogenesis in CTLM images are significant characteristics to differentiate malignancy or benign lesions. The 3D compactness features and 3D Grey Level Co-occurrence matrix (GLCM) have been extracted from VOIs. Multilayer perceptron neural network (MLPNN) pattern recognition has developed for classification of the normal and abnormal lesion in CTLM images. The performance of the proposed CAD system has been measured with different metrics including accuracy, sensitivity, and specificity and area under receiver operative characteristics (AROC), which are 95.2, 92.4, 98.1, and 0.98%, respectively.

Pathology and Neurotoxicity in Dogs after Repeat Dose Exposure to a Serotonin 5-HT1B Inhibitor.

AZD3783, a cationic amphiphilic drug and a potent inhibitor of the 5-hydroxytryptamine (5-HT1B) receptor, was explored as a potential treatment for depression. To support clinical trials, repeat dose toxicity studies in rats and dogs were conducted. Here we report toxicity findings in dogs after dosing from 1 to 3 months. In the 1-month study, there were minimal neuronal vacuolation in the brain, a marked increase in liver enzymes accompanied by hepatocellular degeneration/necrosis and phospholipidosis (PLD), and PLD/cholecystitis in the gallbladder of animals dosed at 47 mg/kg/day. In the 3-month study, neurotoxicity resulted in euthanasia of one animal dosed at 30 mg/kg/day after 86 days. Extensive pathologic changes were seen in all animals in retina epithelium (inclusion bodies), brain (neuronal vacuolation, degeneration, or necrosis and nerve fiber degeneration), spinal ganglia (vacuolation, degeneration, or necrosis), as well as sciatic and optic nerves (degeneration). Pigment-laden macrophages were observed in the lung, kidney, liver, gallbladder, bone marrow, gastrointestinal tract, and lymphoid tissues. Also seen were vitrel and retinal hemorrhage in the eyes. A brain concentration and pathology study showed that the concentration of AZD3783 in the brain was approximately 4 times higher than in the plasma after 4 weeks of dosing, however, they were similar in all regions examined, and did not correlate with areas with pathologic findings. Our findings with AZD3783 in dogs have not been reported previously with other CNS compounds that effect through serotonergic pharmacology.

Chronic Abdominal Discomfort Syndrome (CADS): Defining and Discussing a Novel Diagnosis.

In this article, we propose a new diagnostic paradigm known as Chronic Abdominal Discomfort Syndrome (CADS). Patient's presentation centers around chronic abdominal pain not explained by acute pathology with or without accompanying dyspepsia, bloating, nausea and vomiting among other symptoms. The pathophysiology is noted to be neurogenic, possibly stemming from visceral sympathetic nerves or abdominal wall afferent nerves. Diagnosis is supported by signs or symptoms traversing clinical, diagnostic and functional criteria. Included is a tool which can assist clinicians in diagnosing patients with CADS per those domains. We hope to facilitate primary care physicians' and gastroenterologists' utilization of our criteria to provide guidance for selecting which patients may benefit from further interventions or evaluation by a pain physician. The pain physician may then offer interventions to provide the patient with relief.

Sub-cellular sequestration of alkaline drugs in lysosomes: new insights for pharmaceutical development of lysosomal fluid.

Background and purpose: Lysosomal-targeted drug delivery can open a new strategy for drug therapy. However, there is currently no universally accepted simulated or artificial lysosomal fluid utilized in the pharmaceutical industry or recognized by the United States Pharmacopeia (USP). Experimental procedure: We prepared a simulated lysosomal fluid (SLYF) and compared its composition to a commercial artificial counterpart. The developed fluid was used to test the dissolution of a commercial product (Robitussin®) of a lysosomotropic drug (dextromethorphan) and to investigate in-vitro lysosomal trapping of two model drugs (dextromethorphan and (+/-) chloroquine). Findings/Results: The laboratory-prepared fluid or SLYF contained the essential components for the lysosomal function in concentrations reflective of the physiological values, unlike the commercial product. Robitussin® passed the acceptance criteria for the dissolution of dextromethorphan in 0.1 N HCl medium (97.7% in less than 45 min) but not in the SLYF or the phosphate buffer media (72.6% and 32.2% within 45 min, respectively). Racemic chloroquine showed higher lysosomal trapping (51.9%) in the in-vitro model than dextromethorphan (28.3%) in a behavior supporting in-vivo findings and based on the molecular descriptors and the lysosomal sequestration potential of both. Conclusion and implication: A standardized lysosomal fluid was reported and developed for in-vitro investigations of lysosomotropic drugs and formulations.

Off target toxicities and links with physicochemical properties of medicinal products, including antibiotics, oligonucleotides, lipid nanoparticles (with cationic and/or anionic charges). Data review suggests an emerging pattern.

Toxicology is an essential part of any drug development plan. Circumnavigating the risk of failure because of a toxicity issue can be a challenge, and failure in late development is extremely costly. To identify potential risks, it requires more than just understanding the biological target. The toxicologist needs to consider a compound's structure, it's physicochemical properties (including the impact of the overall formulation), as well as the biological target (e.g., receptor interactions). Understanding the impact of the physicochemical properties can be used to predict potential toxicities in advance by incorporating key endpoints in early screening strategies and/or used to compare toxicity profiles across lead candidates. This review discussed the risks of off-target and/or non-specific toxicities that may be associated with the physicochemical properties of compounds, especially those carrying dominant positive or negative charges, including amphiphilic small molecules, peptides, oligonucleotides and lipids/liposomes/lipid nanoparticles. The latter of which are being seen more and more in drug development, including the recent Covid pandemic, where mRNA and lipid nanoparticle technology is playing more of a role in vaccine development. The translation between non-clinical and clinical data is also considered, questioning how a physicochemical driven toxicity may be more universal across species, which means that such toxicity may be reassuringly translatable between species and as such, this information may also be considered as a support to the 3 R's, particularly in the early screening stages of a drug development plan.

Raman and fluorescence imaging of phospholipidosis induced by cationic amphiphilic drugs in endothelial cells.

Cationic amphiphilic drugs (CADs) are known from lysosomotropism, drug-induced phospholipidosis (DIPL), activation of autophagy, and decreased cell viability, but the relationship between these events is not clear and little is known about DIPL in the endothelium. In this work, the effects of fluoxetine, amiodarone, clozapine, and risperidone on human microvascular endothelial cells (HMEC-1) were studied using a combined methodology of label-free Raman imaging and fluorescence staining. Raman spectroscopy was applied to characterize biochemical changes in lipid profile and their distribution in the cellular compartments, while fluorescence staining (LysoTracker, LipidTOX, LC3B, and JC-1) was used to analyze lysosome volume expansion, activation of autophagy, lipid accumulation, and mitochondrial membrane depolarization. We demonstrated that fluoxetine, amiodarone, and clozapine, but not risperidone, at non-toxic concentrations induced lipid accumulations in the perinuclear and cytoplasmic regions of endothelial cells. Spectroscopic markers of DIPL included a robust increase in the ratio (lipid/(protein + lipid)), an increase in choline-containing lipid, fatty acids, and the presence of cholesterol esters, while starvation-induced activated autophagy revealed a spectroscopic signature associated with subtle changes in the lipid profile only. Interestingly, lysosomal volume expansion, occurrence of DIPL, and activation of autophagy induced by selected CADs all depended on drug-accumulation in acidic pH of lysosome cellular compartments whereas reduced endothelial viability did not, and was attributed to mitochondrial mechanisms as evidenced by a decreased mitochondrial transmembrane potential. In conclusion, drug-induced phospholipidosis in the endothelium did not reduce endothelial viability per se and can be efficiently assayed by Raman imaging.

Development of computer-aided model to differentiate COVID-19 from pulmonary edema in lung CT scan: EDECOVID-net.

The efforts made to prevent the spread of COVID-19 face specific challenges in diagnosing COVID-19 patients and differentiating them from patients with pulmonary edema. Although systemically administered pulmonary vasodilators and acetazolamide are of great benefit for treating pulmonary edema, they should not be used to treat COVID-19 as they carry the risk of several adverse consequences, including worsening the matching of ventilation and perfusion, impaired carbon dioxide transport, systemic hypotension, and increased work of breathing. This study proposes a machine learning-based method (EDECOVID-net) that automatically differentiates the COVID-19 symptoms from pulmonary edema in lung CT scans using radiomic features. To the best of our knowledge, EDECOVID-net is the first method to differentiate COVID-19 from pulmonary edema and a helpful tool for diagnosing COVID-19 at early stages. The EDECOVID-net has been proposed as a new machine learning-based method with some advantages, such as having simple structure and few mathematical calculations. In total, 13 717 imaging patches, including 5759 COVID-19 and 7958 edema images, were extracted using a CT incision by a specialist radiologist. The EDECOVID-net can distinguish the patients with COVID-19 from those with pulmonary edema with an accuracy of 0.98. In addition, the accuracy of the EDECOVID-net algorithm is compared with other machine learning methods, such as VGG-16 (Acc = 0.94), VGG-19 (Acc = 0.96), Xception (Acc = 0.95), ResNet101 (Acc = 0.97), and DenseNet20l (Acc = 0.97).

Reality Construction of Disaster Discourses on Twitter: Analysis of Corpus-Assisted Discourse Study on Forest Fires in Indonesia From 2014-2019.

This paper takes the form of a case study of forest fires that occurred in Indonesia from 2014 to 2019 and were reported on the social media of Twitter. The study was a corpus-assisted discourse study (CADS) using data scraping or text mining on Twitter based on the keyword "kebakaran hutan" [forest fire] and discourse analysis. The actor-network theory was used to map the actors involved. This study concludes that five discourses show a consistently large pattern of Twitter users responding to the problem of forest fires in Indonesia. Regarding the actors, the government takes an essential role of leadership and information arbitrage on Twitter. Seeing as it is the state's responsibility to ensure the safety of all people, the government must appear to be the main holder of control in managing disaster information traffic to avoid irresponsible information or hoaxes disseminated by parties or actors. These results indicate that the availability of information obtained from every conversation of Twitter users can be used as a study or input in the formulation of evidence-based policy about forest fires. It should be given more attention as an alternative means of solving the issue of forest fires, which has become an annual problem in Indonesia.

Nous rapportons ici l'étude des feux de forêts survenus en Indonésie entre 2014 et 2019, tels que rapportés sur Twitter. Nous réalisé une analyse lexicographique des tweets repérés par les mots clés « feux de forêts ¼, à partir des captures d'écran. Les acteurs impliqués ont été cartographiés selon la théorie sociologique de l'acteur-réseau. On peut alors répartir la grande majorité des utilisateurs de Twitter dans 5 catégories. Le gouvernement a des rôles d'information et de modération majeurs dans ce contexte. Ayant pour responsabilité d'assurer la sécurité de la population, il doit apparaître comme le régulateur principal du corpus de l'information, en évitant la dissémination de canulars et autres infoxes. L'ensemble des informations relayées par Twitter peut être utilisé pour construire un discours objectif qui pourrait être utilisé dans la gestion du problème des feux de forêts, qui se reproduisent chaque année en indonésie.

A sex-dependent computer-aided diagnosis system for autism spectrum disorder using connectivity of resting-state fMRI.

Objective.Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with the main symptoms of social communication disabilities. ASD is more than four times more common among males than females. The diagnosis of ASD is currently a subjective process by experts the same for males and females. Various studies have suggested the use of brain connectivity features for the diagnosis of ASD. Also, sex-related biological factors have been shown to play a role in ASD etiology and influence the brain connectivity. Therefore, proposing an accurate computer-aided diagnosis system (CADS) for ASD which considers the sex of subjects seems necessary. In this study, we present a sex-dependent connectivity-based CADS for ASD using resting-state functional magnetic resonance imaging. The proposed CADS classifies ASD males from normal males, and ASD females from normal females.Approach.After data preprocessing, group independent component analysis (GICA) was applied to obtain the resting-state networks (RSNs) followed by applying dual-regression to obtain the time course of each RSN for each subject. Afterwards, functional connectivity measures of full correlation and partial correlation and the effective connectivity measure of bivariate Granger causality were computed between time series of RSNs. To consider the role of sex differences in the classification process, male, female, and mixed groups were taken into account, and feature selection and classification were designed for each sex group separately. At the end, the classification accuracy was computed for each sex group.Main results.In the female group, a classification accuracy of 93.3% was obtained using full correlation while in the male group, a classification accuracy of 86.7% was achieved using both full correlation and bivariate Granger causality. Also, in the mixed group, a classification accuracy of 83.3% was obtained using full correlation.Significance.This supports the importance of considering sex in diagnosing ASD patients from normal controls.

Advances in the development of biodegradable coronary stents: A translational perspective.

Implantation of cardiovascular stents is an important therapeutic method to treat coronary artery diseases. Bare-metal and drug-eluting stents show promising clinical outcomes, however, their permanent presence may create complications. In recent years, numerous preclinical and clinical trials have evaluated the properties of bioresorbable stents, including polymer and magnesium-based stents. Three-dimensional (3D) printed-shape-memory polymeric materials enable the self-deployment of stents and provide a novel approach for individualized treatment. Novel bioresorbable metallic stents such as iron- and zinc-based stents have also been investigated and refined. However, the development of novel bioresorbable stents accompanied by clinical translation remains time-consuming and challenging. This review comprehensively summarizes the development of bioresorbable stents based on their preclinical/clinical trials and highlights translational research as well as novel technologies for stents (e.g., bioresorbable electronic stents integrated with biosensors). These findings are expected to inspire the design of novel stents and optimization approaches to improve the efficacy of treatments for cardiovascular diseases.

Impact of the 237th residue on the folding of human carbonic anhydrase II.

The deficiency of human carbonic anhydrase II (HCAII) has been recognized to be associated with a disease called CAII deficiency syndrome (CADS). Among the many mutations, the P237H mutation has been characterized to lead to a significant decrease in the activity of the enzyme and in the Gibbs free energy of folding. However, sequence alignment indicated that the 237th residue of CAII is not fully conserved across all species. The FoldX theoretical calculations suggested that this residue did not significantly contribute to the overall folding of HCAII, since all mutants had small ΔΔG values (around 1 kcal/mol). The experimental determination indicated that at least three mutations affect HCAII folding significantly and the P237H mutation was the most deleterious one, suggesting that Pro237 was important to HCAII folding. The discrepancy between theoretical and experimental results suggested that caution should be taken when using the prediction methods to evaluate the details of disease-related mutations.

Texture appearance model, a new model-based segmentation paradigm, application on the segmentation of lung nodule in the CT scan of the chest.

Lung cancer causes more than one million deaths worldwide each year. Averages of 5-year survival rate of patients with Non-small cell lung cancer (NSCLC), which is the most common type of lung cancer, is 15%. Computer-Aided Detection (CAD) is a very important tool for identifying lung lesions in medical imaging. In general, the process line of a CAD system can be divided into four main stages: preprocessing, localization, feature extraction, and classification. As segmentation is required for localization in computer vision and medical image analysis, this step has become a major and challenging problem, and much research has been done on new segmentation techniques. In recent years, interest in model-based segmentation methods has increased, and the reason for this is even if some object information is lost, such gaps can be filled by using the previous information in the model. This paper proposed Texture Appearance Model (TAM), which is a new model-based method and segments all types of nodule areas accurately and efficiently, including juxta-pleural nodules, without separating the lung from the surrounding area in a CT scan of the lung. In this method, Texture Representation of Image (TRI) is obtained using tissue texture feature extraction and feature selection algorithms. The proposed method has been evaluated in 85 nodules of the dataset, received from the Iranian hospital, in which the ground-truth annotation by physicians and CT imaging data were provided. The results show that the proposed algorithm has an encouraging performance for distinguishing different types of nodules, including pleural, cavity and non-solid nodules, achieving an average dice similarity coefficient (DSC) of 84.75%.

Psychotropic Drugs Show Anticancer Activity by Disrupting Mitochondrial and Lysosomal Function.

Background and Purpose: Drug repositioning is a promising strategy for discovering new therapeutic strategies for cancer therapy. We investigated psychotropic drugs for their antitumor activity because of several epidemiological studies reporting lower cancer incidence in individuals receiving long term drug treatment. Experimental Approach: We investigated 27 psychotropic drugs for their cytotoxic activity in colorectal carcinoma, glioblastoma and breast cancer cell lines. Consistent with the cationic amphiphilic structure of the most cytotoxic compounds, we investigated their effect on mitochondrial and lysosomal compartments. Results: Penfluridol, ebastine, pimozide and fluoxetine, fluspirilene and nefazodone showed significant cytotoxicity, in the low micromolar range, in all cell lines tested. In MCF7 cells these drugs caused mitochondrial membrane depolarization, increased the acidic vesicular compartments and induced phospholipidosis. Both penfluridol and spiperone induced AMPK activation and autophagy. Neither caspase nor autophagy inhibitors rescued cells from death induced by ebastine, fluoxetine, fluspirilene and nefazodone. Treatment with 3-methyladenine partially rescued cell death induced by pimozide and spiperone, whereas enhanced the cytotoxic activity of penfluridol. Conversely, inhibition of lysosomal cathepsins significantly reduced cell death induced by ebastin, penfluridol, pimozide, spiperone and mildly in fluoxetine treated cells. Lastly, Spiperone cytotoxicity was restricted to colorectal cancer and breast cancer and caused apoptotic cell death in MCF7 cells. Conclusions: The cytotoxicity of psychotropic drugs with cationic amphiphilic structures relied on simultaneous mitochondrial and lysosomal disruption and induction of cell death that not necessarily requires apoptosis. Since dual targeting of lysosomes and mitochondria constitutes a new promising therapeutic approach for cancer, particularly those in which the apoptotic machinery is defective, these data further support their clinical development for cancer therapy.

Lysosomotropic cationic amphiphilic drugs inhibit adipocyte differentiation in 3T3-L1K cells via accumulation in cells and phospholipid membranes, and inhibition of autophagy.

Some cationic amphiphilic drugs (CADs) have been individually reported to interfere with the differentiation of immune system cells, such as macrophages and dendritic cells. To investigate the possible generic nature of this process, in this study we aimed to see whether these drugs are capable of interfering with the differentiation of adipocytes. Further, we investigated whether this feature might be connected to the lysosomotropic character of these drugs, and their disturbance of intracellular membrane trafficking rather than to the individual pharmacologic properties of each drug. Thus, for the selected set of compounds consisting of seven structurally and pharmacologically diverse CADs and three non-CAD controls we have measured the impact on differentiation of 3T3-L1K murine preadipocytes to adipocytes. We conclude that CADs indeed inhibit adipocyte differentiation, as shown morphologically, at the level of lipid droplet formation and on the expression of genetic markers of adipocytes. Furthermore, the intensity of this inhibitory effect was found to strongly positively correlate with the extent of drug accumulation in adipocytes, with their affinity for phospholipid membranes, as well as with their ability to induce phospholipidosis and inhibit autophagy.

Effect of caffeic acid derivatives on polychlorinated biphenyls induced hepatotoxicity in male mice.

Chronic exposure to coplanar polychlorinated biphenyls (PCBs), a potent inducer of toxic reactive oxygen species (ROS), in the environment and food can cause liver diseases. It remains unknown whether caffeic acid derivatives (CADs) exerted protective effect on PCB-induced hepatotoxicity. We sought to evaluate the activities of 3 CADs on PCB169-induced oxidative stress and DNA damage in the liver. Male ICR mice were administered with 1 µmol/mL PCB169 at 5 mL/kg body weight for 2 weeks. The mice were given CADs by gastric gavage for 3 weeks. We found that PCB169 decreased the growth rate and reduced the levels of superoxide dismutase (SOD), glutathione (GSH) and GSH peroxidase (GPx). It increased the liver weight, malondialdehyde (MDA) and 8-hydroxy-2'-deoxyguanosine (8-OHdG) levels and CYP1A1 activity in the liver tissues and plasma of mice (P<0.05). Pretreatment of mice with CADs restored the above parameters to normal levels. There was a synergistic protective effect between CADs in preventing MDA and 8-OHdG formation and inducing CYP1A1 and phase II metabolism enzyme (SOD, GPx) activities (P<0.05). In conclusion, PCB169 induced hepatotoxicity and pretreatment with CADs had synergistic protective effects on liver damage.

In Silico Studies of the Relationship Between Chemical Structure and Drug Induced Phospholipidosis.

Drug-induced phospholipidosis (PLD) is a side effect of the administration of cationic amphiphilic drugs (CADs). It is desirable to identify and screen compounds with the potential to induce PLD as early as possible in drug development. Recently, a number of in silico methods have been developed to predict PLD. These models are low-cost and high-throughput strategies; however, they produce a high number of false positive predictions. The aim of this study was to assess the predictive performance of existing in silico approaches and to develop new strategies for the rapid identification of the potential PLD-inducers. Studies on 450 chemicals confirmed the high false positive rate of prediction of models based only on log P and pKa values. Modification of the methods by incorporating structural information gave moderate improvements in the prediction performance. Therefore, a new strategy, based on molecular fragments captured by SMARTS strings was developed. These structural fragments were able to identify potential PLD-inducers and achieved a high sensitivity of 85 %. The results showed that the phospholipidosis is linked directly to the molecular structure of chemical; therefore the SMARTS pattern methodology could be used as a first line of screening of PLD potential during the drug discovery process.

Gaussian Weighted Projection for Visualization of Cardiac Calcification.

At our institution, we are using dual-energy digital radiography (DEDR) as a cost-effective screening tool for the detection of cardiac calcification. We are evaluating DEDR using CT as the gold standard. We are developing image projection methods for the generation of digitally reconstructed radiography (DRR) from CT image volumes. Traditional visualization methods include maximum intensity projection (MIP) and average-based projection (AVG) that have difficulty to show cardiac calcification. Furthermore, MIP can over estimate the calcified lesion as it displays the maximum intensity along the projection rays regardless of tissue types. For AVG projection, the calcified tissue is usually overlapped with bone, lung and mediastinum. In order to improve the visualization of calcification on DRR images, we developed a Gaussian-weighted projection method for this particular application. We assume that the CT intensity values of calcified tissues have a Gaussian distribution. We then use multiple Gaussian functions to fit the intensity histogram. Based on the mean and standard deviation parameters, we incorporate a Gaussian weighted function into the perspective projection and display the calcification exclusively. Our digital and physical phantom studies show that the new projection method can display tissues selectively. In addition, clinical images show that the Gaussian-weighted projection method better visualizes cardiac calcification than either the AVG or MIP method and can be used to evaluate DEDR as a screening tool for the detection of coronary artery diseases.

Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification.

We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DR) for the detection of coronary artery calcification. CT is an established tool for the diagnosis of coronary artery diseases (CADs). Dual-energy digital radiography could be a cost-effective alternative for screening coronary artery calcification. In order to utilize CT as the "gold standard" to evaluate the ability of DR images for the detection and localization of calcium, we developed an automatic intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DR images. To generate digital rendering radiographs (DRR) from the CT volumes, we developed three projection methods, i.e. Gaussian-weighted projection, threshold-based projection, and average-based projection. We tested normalized cross correlation (NCC) and normalized mutual information (NMI) as similarity measurement. We used the Downhill Simplex method as the search strategy. Simulated projection images from CT were fused with the corresponding DR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with mean errors of less 0.8 mm and 0.2 degree for both NCC and NMI. The registration accuracy of the physical phantoms is 0.34 ± 0.27 mm. Color overlay and 3D visualization of the clinical data show that the two images are registered well. This is consistent with the improvement of the NMI values from 0.20 ± 0.03 to 0.25 ± 0.03 after registration. The automatic 3D-to-2D registration method is accurate and robust and may provide a useful tool to evaluate the dual-energy DR images for the detection of coronary artery calcification.