Rabah M. Al abdi

Digital optical tomography system for dynamic breast imaging

Diffuse optical tomography has shown promising results as a tool for breast cancer screening and monitoring response to chemotherapy. Dynamic imaging of the transient response of the breast to an external stimulus, such as pressure or a respiratory maneuver, can provide additional information that can be used to detect tumors. We present a new digital continuous-wave optical tomography system designed to simultaneously image both breasts at fast frame rates and with a large number of sources and detectors. The system uses a master-slave digital signal processor-based detection architecture to achieve a dynamic range of 160 dB and a frame rate of 1.7 Hz with 32 sources, 64 detectors, and 4 wavelengths per breast. Included is a preliminary study of one healthy patient and two breast cancer patients showing the ability to identify an invasive carcinoma based on the hemodynamic response to a breath hold.

Optomechanical imaging system for breast cancer detection.

Imaging studies of the breast comprise three principal sensing domains: structural, mechanical, and functional. Combinations of these domains can yield either additive or wholly new information, depending on whether one domain interacts with the other. In this report, we describe a new approach to breast imaging based on the interaction between controlled applied mechanical force and tissue hemodynamics. Presented is a description of the system design, performance characteristics, and representative clinical findings for a second-generation dynamic near-infrared optical tomographic breast imager that examines both breasts simultaneously, under conditions of rest and controlled mechanical provocation. The expected capabilities and limitations of the developed system are described in relation to the various sensing domains for breast imaging.

Validation of near infrared spectroscopic (NIRS) imaging using programmable phantoms

For much of the past decade, we have developed most of the essential hardware and software components needed for practical implementation of dynamic NIRS imaging. Until recently, however, these efforts have been hampered by the lack of calibrating phantoms whose dynamics substantially mimic those seen in tissue. Here we present findings that document the performance of a dynamic phantom based on use of twisted nematic liquid crystal (LC) technology. Programmable time courses of applied voltage cause the opacity of the LC devices, which are embedded in a background matrix consisting of polysiloxane (silicone) admixed with scattering and absorbing materials, to vary in a manner that mimics the spatiotemporal hemodynamic pattern of interest. Methods for producing phantoms with selected absorption and scattering, internal heterogeneity, external geometry, hardness, and number and locations of embedded LCs are described. Also described is a method for overcoming the apparent limitation that arises from LCs being mainly independent of the illumination wavelength. The results presented demonstrate that: the opacity vs. voltage response of LCs are highly stable and repeatable; the dynamic phantom can be driven at physiologically relevant speeds, and will produce time-varying absorption that follows the programmed behavior with high fidelity; image time series recovered from measurements on the phantom have high temporal and spatial location accuracy. Thus the dynamic phantom can fill the need for test media that practitioners may use to confirm the accuracy of computed imaging results, assure the correct operation of imaging hardware, and compare performance of different data analysis algorithms.

The design and characterization of a digital optical breast cancer imaging system

Optical imaging has the potential to play a major role in breast cancer screening and diagnosis due to its ability to image cancer characteristics such as angiogenesis and hypoxia. A promising approach to evaluate and quantify these characteristics is to perform dynamic imaging studies in which one monitors the hemodynamic response to an external stimulus, such as a valsalva maneuver. It has been shown that the response to such stimuli shows MARKED differences between cancerous and healthy tissues. The fast imaging rates and large dynamic range of digital devices makes them ideal for this type of imaging studies. Here we present a digital optical tomography system designed specifically for dynamic breast imaging. The instrument uses laser diodes at 4 different near-infrared wavelengths with 32 sources and 128 silicon photodiode detectors.

Enhanced resting‐state dynamics of the hemoglobin signal as a novel biomarker for detection of breast cancer

PURPOSE The work presented here demonstrates an application of diffuse optical tomography (DOT) to the problem of breast-cancer diagnosis. The potential for using spatial and temporal variability measures of the hemoglobin signal to identify useful biomarkers was studied. METHODS DOT imaging data were collected using two instrumentation platforms the authors developed, which were suitable for exploring tissue dynamics while performing a simultaneous bilateral exam. For each component of the hemoglobin signal (e.g., total, oxygenated), the image time series was reduced to eight scalar metrics that were affected by one or more dynamic properties of the breast microvasculature (e.g., average amplitude, amplitude heterogeneity, strength of spatial coordination). Receiver-operator characteristic (ROC) analyses, comparing groups of subjects with breast cancer to various control groups (i.e., all noncancer subjects, only those with diagnosed benign breast pathology, and only those with no known breast pathology), were performed to evaluate the effect of cancer on the magnitudes of the metrics and of their interbreast differences and ratios. RESULTS For women with known breast cancer, simultaneous bilateral DOT breast measures reveal a marked increase in the resting-state amplitude of the vasomotor response in the hemoglobin signal for the affected breast, compared to the contralateral, noncancer breast. Reconstructed 3D spatial maps of observed dynamics also show that this behavior extends well beyond the tumor border. In an effort to identify biomarkers that have the potential to support clinical aims, a group of scalar quantities extracted from the time series measures was systematically examined. This analysis showed that many of the quantities obtained by computing paired responses from the bilateral scans (e.g., interbreast differences, ratios) reveal statistically significant differences between the cancer-positive and -negative subject groups, while the corresponding measures derived from individual breast scans do not. ROC analyses yield area-under-curve values in the 77%-87% range, depending on the metric, with sensitivity and specificity values ranging from 66% to 91%. An interesting result is the initially unexpected finding that the hemodynamic-image metrics are only weakly dependent on the tumor burden, implying that the DOT technique employed is sensitive to tumor-induced changes in the vascular dynamics of the surrounding breast tissue as well. Computational modeling studies serve to identify which properties of the vasomotor response (e.g., average amplitude, amplitude heterogeneity, and phase heterogeneity) principally determine the values of the metrics and their codependences. Findings from the modeling studies also serve to clarify the influence of spatial-response heterogeneity and of system-design limitations, and they reveal the impact that a complex dependence of metric values on the modeled behaviors has on the success in distinguishing between cancer-positive and -negative subjects. CONCLUSIONS The authors identified promising hemoglobin-based biomarkers for breast cancer from measures of the resting-state dynamics of the vascular bed. A notable feature of these biomarkers is that their spatial extent encompasses a large fraction of the breast volume, which is mainly independent of tumor size. Tumor-induced induction of nitric oxide synthesis, a well-established concomitant of many breast cancers, is offered as a plausible biological causal factor for the reported findings.

Development of a dynamic optical tomographic breast imaging system with digital detection techniques

Breast cancer characteristics such as angiogenesis and hypoxia can be quantified by using optical tomography imaging to observe the hemodynamic response to an external stimulus. A digital near-infrared tomography system has been developed specifically for the purpose of dynamic breast imaging. It simultaneously acquires four frequency encoded wavelengths of light at 765, 808, 827, and 905nm in order to facilitate the functional imaging of oxy- and deoxy-hemoglobin, lipid concentration and water content. The system uses 32 source fibers to simultaneously illuminate both breasts. There are 128 detector fibers, 64 fibers for each breast, which deliver the detected light to silicon photo-detectors. The signal is conditioned by variable gain amplifiers and filters and is quantized by an analog to digital converter (ADC). The sampled signal is then passed on for processing using a Digital Signal Processor (DSP) prior to display on a host computer. The system can acquire 2.23 frames per second with a dynamic range of 236 dB.

Computer-aided autism diagnosis via second-order difference plot area applied to EEG empirical mode decomposition

Autism spectrum disorder (ASD) is a name for a group of neurodevelopmental conditions that are characterized by some degree of impairment in social interaction, verbal and non-verbal communication, and difficulty in symbolic capacity and repetitive behaviors. The only protocol followed currently for ASD diagnosis is the qualitative behavioral assessment by experts through internationally established descriptive scaling standards. The assessment can, therefore, be affected by the degree of the evaluator experience as well as by the level of the descriptive standard robustness. This paper presents an EEG-based quantitative approach intended for automatic discrimination between children with typical neurodevelopment and children with ASD. The suggested work relies on second-order difference plot (SODP) area as a discriminative feature: First, every EEG channel in a 64 electrode cap—for every volunteer—is decomposed into intrinsic mode functions (IMFs) by empirical mode decomposition (EMD). Next, the second-order difference plot for the first ten intrinsic mode functions—of every channel—is sketched. Third, the value of the elliptical area —for every plot—is calculated. The 95% confidence ellipse area is used as the discriminative feature. Fourth, paired t-student test is applied to the vectors consisting of discriminative feature values for counterpart channels/IMFs (e.g., channel FPz/IMF7 in autistic and neurotypical) for all volunteers. Finally, principal component analysis (PCA) and neural network (NN) are applied to the SODP area feature matrix for two-class classification (ASD and neurotypical). Moreover, the 3D mapping of EEG SODP area values was implemented and analyzed. The obtained results show that the conducted t-student tests yield values of less than 0.05, and that the NN two-class classification based on SODP features leads to a 94.4% accuracy, which indicates significant differences between SODP area values of children with neurotypical development and those diagnosed with ASD. The obtained results have also been emphasized by the analysis of the findings of the performed 3D mapping.

Objective detection of chronic stress using physiological parameters

AbstractThe aim of this study was to design a system to diagnose chronic stress, based on blunted reactivity of the autonomic nervous system (ANS) to cognitive load (CL). The system concurrently measures CL-induced variations in pupil diameter (PD), heart rate (HR), pulse wave amplitude (PWA), galvanic skin response (GSR), and breathing rate (BR). Measurements were recorded from 58 volunteers whose stress level was identified using the State-Trait Anxiety Inventory. Number-multiplication questions were used as CLs. HR, PWA, GSR, and PD were significantly (p < 0.05) changed during CL. CL-induced changes in PWA (16.87 ± 21.39), GSR (− 13.71 ± 7.86), and PD (11.56 ± 9.85) for non-stressed subjects (n = 36) were significantly different (p < 0.05) from those in PWA (2.92 ± 12.89), GSR (− 6.87 ± 9.54), and PD (4.51 ± 10.94) for stressed subjects (n = 22). ROC analysis for PWA, GSR, and PD illustrated their usefulness to identify stressed subjects. By inputting all features to different classification algorithms, up to 91.7% of sensitivity and 89.7% of accuracy to identify stressed subjects were achieved using 10-fold cross-validation. This study was the first to document blunted CL-induced changes in PWA, GSR, and PD in stressed subjects, compared to those in non-stressed subjects. Preliminary results demonstrated the ability of our system to objectively detect chronic stress with good accuracy, suggesting the potential for monitoring stress to prevent dangerous stress-related diseases. Graphical abstractChronic stress degrads the autonomic nervous system reaction to cognitive loads. Measurement of reduced changes in physiological signals during asking math questions was useful to identify people with high STAI score (stressed subjects)

The Impact of Applying Quality Management Practices on Patient Centeredness in Jordanian Public Hospitals: Results of Predictive Modeling:

Targeting the patient’s needs and preferences has become an important contributor for improving care delivery, enhancing patient satisfaction, and achieving better clinical outcomes. This study aimed to examine the impact of applying quality management practices on patient centeredness within the context of health care accreditation and to explore the differences in the views of various health care workers regarding the attributes affecting patient-centered care. Our study followed a cross-sectional survey design wherein 4 Jordanian public hospitals were investigated several months after accreditation was obtained. Total 829 clinical/nonclinical hospital staff members consented for study participation. This sample was divided into 3 main occupational categories to represent the administrators, nurses, as well as doctors and other health professionals. Using a structural equation modeling, our results indicated that the predictors of patient-centered care for both administrators and those providing clinical care were participation in the accreditation process, leadership commitment to quality improvement, and measurement of quality improvement outcomes. In particular, perceiving the importance of the hospital’s engagement in the accreditation process was shown to be relevant to the administrators (gamma = 0.96), nurses (gamma = 0.80), as well as to doctors and other health professionals (gamma = 0.71). However, the administrator staff (gamma = 0.31) was less likely to perceive the influence of measuring the quality improvement outcomes on the delivery of patient-centered care than nurses (gamma = 0.59) as well as doctors and other health care providers (gamma = 0.55). From the nurses’ perspectives only, patient centeredness was found to be driven by building an institutional framework that supports quality assurance in hospital settings (gamma = 0.36). In conclusion, accreditation is a leading factor for delivering patient-centered care and should be on a hospital’s agenda as a strategy for continuous quality improvement.

Evaluation of mental stress by measuring four physiological signals simultaneously

P gel dosimeters are tissue equivalent martial that fabricated from radiation sensitive chemicals which, upon irradiation, polymerize as a function of absorbed radiation dose. Polymer gel dosimeters can uniquely record the radiation dose distribution in three-dimensions (3D). A novel composition of polymer gel dosimeters based on radiation-induced polymerization of N-(hydroxymethyl) acrylamide (NHMA) is introduced in this study for radiotherapy treatment planning. The dosimeters were irradiated by 10 MV photon beam of a medical linear accelerator at a constant dose rate of 600 cGy/min with doses up to 30 Gy. The polymerization degree is directly proportional to absorbed dose received by the polymer gel. Nuclear magnetic resonance (NMR) and nuclear magnetic imaging (NMR) were used to investigate the relaxation rate (R2) of water proton of irradiated NHMA gel which is associated to the degree of polymerization of polymer gel dosimeters. R2 increases with absorbed dose for all gel dosimeters in the dose range between 0 and 30 Gy. Dose rate, energy of radiation and the stability of the polymerization after irradiation were investigated. No appreciable effects of these parameters on the performance of the novel gel dosimeters were observed.