Non-invasive glucose prediction and classification using NIR technology with machine learning

In this paper, a dual wavelength short near-infrared system is described for the detection of glucose levels. The system aims to improve the accuracy of blood glucose detection in a cost-effective and non-invasive way. The accuracy of the method is evaluated using real-time samples collected with the reference finger prick glucose device. A feed forward neural network (FFNN) regression method is employed to predict glucose levels based on the input data obtained from NIR technology. The system calculates glucose evaluation metrics and performs Surveillance error grid (SEG) analysis. The coefficient of determination R 2 and mean absolute error are observed 0.99 and 2.49 mg/dl, respectively. Additionally, the system determines the root mean square error (RMSE) as 3.02 mg/dl. It also shows that the mean absolute percentage error (MAPE) is 1.94% and mean squared error (MSE) is 9.16 ( m g / d l ) 2 for FFNN. The SEG analysis shows that the glucose values measured by the system fall within the clinically acceptable range when compared to the reference method. Finally, the system uses the multi-class classification method of the multilayer perceptron (MLP) and K-nearest neighbors (KNN) classifier to classify glucose levels with an accuracy of 99%.

MR compatible detectors assessment for a 0.35 T MR-linac commissioning

PURPOSE

To assess a large panel of MR compatible detectors on the full range of measurements required for a 0.35 T MR-linac commissioning by using a specific statistical method represented as a continuum of comparison with the Monte Carlo (MC) TPS calculations. This study also describes the commissioning tests and the secondary MC dose calculation validation.

MATERIAL AND METHODS

Plans were created on the Viewray TPS to generate MC reference data. Absolute dose points, PDD, profiles and output factors were extracted and compared to measurements performed with ten different detectors: PTW 31010, 31021, 31022, Markus 34045 and Exradin A28 MR ionization chambers, SN Edge shielded diode, PTW 60019 microdiamond, PTW 60023 unshielded diode, EBT3 radiochromic films and LiF µcubes. Three commissioning steps consisted in comparison between calculated and measured dose: the beam model validation, the output calibration verification in four different phantoms and the commissioning tests recommended by the IAEA-TECDOC-1583.

MAIN RESULTS

The symmetry for the high resolution detectors was higher than the TPS data of about 1%. The angular responses of the PTW 60023 and the SN Edge were - 6.6 and - 11.9% compared to the PTW 31010 at 60°. The X/Y-left and the Y-right penumbras measured by the high resolution detectors were in good agreement with the TPS values except for the PTW 60023 for large field sizes. For the 0.84 × 0.83 cm2 field size, the mean deviation to the TPS of the uncorrected OF was - 1.7 ± 1.6% against - 4.0 ± 0.6% for the corrected OF whereas we found - 4.8 ± 0.8% for passive dosimeters. The mean absolute dose deviations to the TPS in different phantoms were 0 ± 0.4%, - 1.2 ± 0.6% and 0.5 ± 1.1% for the PTW 31010, PTW 31021 and Exradin A28 MR respectively.

CONCLUSIONS

The magnetic field effects on the measurements are considerably reduced at low magnetic field. The PTW 31010 ionization chamber can be used with confidence in different phantoms for commissioning and QA tests requiring absolute dose verifications. For relative measurements, the PTW 60019 presented the best agreement for the full range of field size. For the profile assessment, shielded diodes had a behaviour similar to the PTW 60019 and 60023 while the ionization chambers were the most suitable detectors for the symmetry. The output correction factors published by the IAEA TRS 483 seem to be applicable at low magnetic field pending the publication of new MR specific values.

InAs Nanorod Colloidal Quantum Dots with Tunable Bandgaps Deep into the Short-Wave Infrared

InAs colloidal quantum dots (CQDs) have emerged as candidate lead- and mercury-free solution-processed semiconductors for infrared technology due to their appropriate bulk bandgap, which can be tuned by quantum confinement, and promising charge-carrier transport properties. However, the lack of suitable arsenic precursors and readily accessible synthesis conditions have limited InAs CQDs to smaller sizes (<7 nm), with bandgaps largely restricted to <1400 nm in the near-infrared spectral window. Conventional InAs CQD synthesis requires highly reactive, hazardous arsenic precursors, which are commercially scarce, making the synthesis hard to control and study. Here, we present a controlled synthesis strategy (using only readily available and less reactive precursors) to overcome the practical wavelength limitation of InAs CQDs, achieving monodisperse InAs nanorod CQDs with bandgaps tunable from ∼1200 to ∼1800 nm, thus crossing deep into the short-wave infrared (SWIR) region. By controlling the reactivity through in situ precursor complexation, we isolate the reaction mechanism, producing InAs nanorod CQDs that display narrow excitonic features and efficient carrier multiplication. Our work enables InAs CQDs for a wider range of SWIR applications.

A plastic scintillator and HPGe β-γ coincidence detection system

A network of specialist laboratories support the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) with re-measurements of radionuclide samples, including xenon gas. The measurement of four xenon fission product radionuclides (133Xe, 135Xe, 131mXe and 133mXe) can be used to detect an underground nuclear explosion. Laboratories use a range of techniques to measure the radionuclides, including beta-gamma (β-γ) coincidence spectrometry. These highly-sensitive measurements are capable of detecting concentrations of down to 500 atoms of 133Xe in a few cm3 of xenon. In some detector systems, detection of the metastable isomers (131mXe and 133mXe) can be more challenging due to interferences between the signatures of different radionuclides. Recent work has shown that using high-purity Germanium (HPGe) high-resolution gamma detectors, these interferences can be reduced, lowering the dependence of the detection limits on radionuclide sample isotopic composition. One downside of these detectors is the reduction in detection efficiency, which impacts the overall detection sensitivity; so assessing different detector systems is a priority for radionuclide laboratories. This work presents a coincidence detector system comprising of a plastic scintillator gas cell and a large-crystal high-purity germanium detector. The energy resolution, coincidence detection efficiency, MDA and interference factors are determined from measurements of synthetic radioxenon gas samples.

Embedded Micro-detectors for EUV Exposure Control in FinFET CMOS Technology

An on-wafer micro-detector for in situ EUV (wavelength of 13.5 nm) detection featuring FinFET CMOS compatibility, 1 T pixel and battery-less sensing is demonstrated. Moreover, the detection results can be written in the in-pixel storage node for days, enabling off-line and non-destructive reading. The high spatial resolution micro-detectors can be used to extract the actual parameters of the incident EUV on wafers, including light intensity, exposure time and energy, key to optimization of lithographic processes in 5 nm FinFET technology and beyond.

Influence of Jaw Setting in the Determination of Stereotactic Small-Field Output Factors with Different Detectors

Background

The experimental determination of relative output factors presents the greatest challenge, especially for small fields with different detectors. The aim of this study is to evaluate the influence of jaw positions on small-field output factors for the fields defined by micro-multileaf collimator and circular cones with different detectors.

Materials and Methods

The stereotactic output factors were measured on Primus linear accelerator with BrainLab micro-multileaf collimator (mMLC) and circular cones as add-on tertiary collimators. Square field sizes ranging from 0.6 cm × 0.6 cm to 9.8 cm × 9.8 cm and circular fields of diameter ranging from 1.0 cm to 4.0 cm were defined by mMLC and circular cones, respectively. The influence of jaw position on output factor was assessed for different geometric configurations with three different detectors.

Results

The values obtained with PinPoint ion chamber were consistent with microDiamond detector for fields greater than 24 mm × 24 mm, but an underestimation of 23.9% was noticed in 6 mm x 6 mm field size. For the mMLC defined field size of 6 mm × 6 mm, when the X-Y jaw was moved from 8 mm × 8 mm to 80 mm × 80 mm, an increase in the output by a factor of 1.7 was observed with both microDiamond and stereotactic radiosurgery diode, whereas an increase in output by a factor of 1.9 was noticed with PinPoint ion chamber.

Conclusion

Output factors obtained with different detectors show high differences in the smallest field size for all collimating systems. This study confirms that the position of X and Y jaw above the tertiary collimator significantly influences the small-field output factor.

FPGA implementation of a real-time digital pulse processing analysis for radiation detectors

A new universal, flexible firmware has been implemented on field -programmable gate array (FPGA) for gamma-ray spectroscopy. The firmware of the FPGA runs on a digitizer that we developed ourselves. The present paper describes the detailed architecture of the firmware, including the trapezoidal shaper, peak detection, pulse height analyzer, and pile-up rejection. Gamma-ray spectroscopy measurements are made using a NaI(Tl) detector, CdZnTe detector, and HPGe detector.

A compact instrument for gamma-ray burst detection on a CubeSat platform I: Design drivers and expected performance

The Educational Irish Research Satellite 1 (EIRSAT-1) is a 2U CubeSat being developed under ESA's Fly Your Satellite! programme. The project has many aspects, which are primarily educational, but also include space qualification of new detector technologies for gamma-ray astronomy and the detection of gamma-ray bursts (GRBs). The Gamma-ray Module (GMOD), the main mission payload, is a small gamma-ray spectrometer comprising a 25 mm × 25 mm × 40 mm cerium bromide scintillator coupled to an array of 16 silicon photomultipliers. The readout is provided by IDE3380 (SIPHRA), a low-power and radiation tolerant readout ASIC. GMOD will detect gamma-rays and measure their energies in a range from tens of keV to a few MeV. Monte Carlo simulations were performed using the Medium Energy Gamma-ray Astronomy Library to evaluate GMOD's capability for the detection of GRBs in low Earth orbit. The simulations used a detailed mass model of the full spacecraft derived from a very high-fidelity 3D CAD model. The sky-average effective area of GMOD on board EIRSAT-1 was found to be 10 cm² at 120 keV. The instrument is expected to detect between 11 and 14 GRBs, at a significance greater than 10σ (and up to 32 at 5σ), during a nominal one-year mission. The shape of the scintillator in GMOD results in omni-directional sensitivity which allows for a nearly all-sky field of view.

Oil biodesulfurization: A review of applied analytical techniques

The wide use of fossil fuels and their associated environmental concerns, highlighted the importance of affordable and clean energy (goal 7), as adopted by the Sustainable Development Goals of the United Nations for 2030. For years now, the detection of sulfur components in liquid fuels is performed mainly for environmental and health purposes in compliance with the respective legislations. Towards this, the aerobic and anaerobic biodesulfurization (BDS) process, which entails the use of microorganisms to limit the sulfur concentration is followed. To ensure effective BDS, several traditional analytical methods are utilized, although they require bench-top, bulky, costly, and time-consuming instruments along with skilled personnel. The currently employed analytical methods are mostly chromatographic techniques (e.g. liquid and gas) coupled with various detectors. To start with, high-performance liquid chromatography with ultraviolet detector (HPLC-UV), as well as electrospray ionization-LC-mass spectrometry (ESI-LC-MS) were mostly reported. Additionally, many detectors were coupled to gas chromatography (CG) including atomic emission detector (GC-AED), flame ionization detector (GC-FID), flame photometric detector (GC-FPD), sulfur fluorescence detector (GC-SFD), mass selective detector (GC-MS), etc. The solid-phase microextraction (SPME) technique provides extra capabilities when added to the separation techniques. Towards the continuous interest in oil supercomplex synthesis, other atmospheric and surface desorption ionization techniques, as well as the multidimensional 2D chromatographic systems (GC × GC and LC × LC) were also investigated, due to their unsurpassed resolution power. The current review ends with final remarks per applied methodology and the necessity to respect and protect the human environment and life.

Recent (2018-2020) development in capillary electrophoresis

Development of new capillary electrophoresis (CE) methodology and instrumentation, as well as application of CE to solve new problems, remains an active research area because of the attractive features of CE compared to other separation techniques. In this review, we focus on the representative works about sample preconcentration, separation media or capillary coating development, detector construction, and multidimensional separation in CE, which are judiciously selected from the papers published in 2018–2020.

Cardiac CT: Technological Advances in Hardware, Software, and Machine Learning Applications

Purpose of Review

Multidetector row computed tomography (CT) allows noninvasive imaging of the heart and coronary arteries. The purpose of this review is to briefly summarize recent advances in CT hardware and software technology, and machine learning applications for cardiovascular imaging.

Recent Findings

In the last decades, there have been significant improvements in CT hardware focusing on faster gantry rotation resulting in improved temporal resolution. Concurrent hardware improvements include improved spatial resolution and higher coverage of the patient, enabling faster acquisition. Advances in cardiac CT software include methods for measurement of noninvasive FFR, coronary plaque characterization, and adipose tissue characteristics around the heart. Machine learning approaches using cardiac CT have been shown to improve both risk of prognosis and lesion-specific ischemia.

Summary

Recent advances in CT hardware and software have expanded the clinical utility of CT for cardiovascular imaging. In the next decades, continued advances can be anticipated in these areas, and in machine learning applications in cardiac CT, as they are incorporated into clinical routine for image acquisition, image analysis, and prediction of patient outcomes.

Initial experience with a SiPM-based PET/CT scanner: influence of acquisition time on image quality

Background

A newly introduced PET/CT scanner (Discovery Meaningful Insights—DMI, GE Healthcare) includes the silicon photomultiplier (SiPM) with time-of-flight (TOF) technology first used in the GE SIGNA PET/MRI. In this study, we investigated the impact of various acquisition times on image quality using this SiPM-based PET/CT.

Methods

We reviewed data from 58 participants with cancer who were scanned using the DMI PET/CT scanner. The administered dosages ranged 295.3–429.9 MBq (mean ± SD 356.3 ± 37.4) and imaging started at 71–142 min (mean ± SD 101.41 ± 17.52) after administration of the radiopharmaceutical. The patients’ BMI ranged 19.79–46.16 (mean ± SD 26.55 ± 5.53). We retrospectively reconstructed the raw TOF data at 30, 60, 90, and 120 s/bed and at the standard image acquisition time per clinical protocol (180 or 210 s/bed depending on BMI). Each reconstruction was reviewed blindly by two nuclear medicine physicians and scored 1–5 (1—poor, 5—excellent quality). The liver signal-to-noise ratio (SNR) was used as a quantitative measure of image quality.

Results

The average scores ± SD of the readers were 2.61 ± 0.83, 3.70 ± 0.92, 4.36 ± 0.82, 4.82 ± 0.39, and 4.91 ± 0.91 for the 30, 60, 90, and 120 s/bed and at standard acquisition time, respectively. Inter-reader agreement on image quality assessment was good, with a weighted kappa of 0.80 (95% CI 0.72–0.81). In the evaluation of the effects of time per bed acquisition on semi-quantitative measurements, we found that the only time point significantly different from the standard time were 30 and 60 s (both with P < 0.001). The effects of dose and BMI were not statistically significant (P = 0.195 and 0.098, respectively). There was a significant positive effect of time on SNR (P < 0.001), as well as a significant negative effect of weight (P < 0.001).

Conclusions

Our results suggest that despite significant delays from injection to imaging (due to comparison with standard PET/CT) compared to standard clinical operations and even in a population with average BMI > 25, images can be acquired as fast as 90 s/bed using the SiPM PET/CT and still result in very good image quality (average score > 4).

Selecting Power-Efficient Signal Features for a Low-Power Fall Detector

Falls are a serious threat to the health of older people. A wearable fall detector can automatically detect the occurrence of a fall and alert a caregiver or an emergency response service so they may deliver immediate assistance, improving the chances of recovering from fall-related injuries. One constraint of such a wearable technology is its limited battery life. Thus, minimization of power consumption is an important design concern, all the while maintaining satisfactory accuracy of the fall detection algorithms implemented on the wearable device. This paper proposes an approach for selecting power-efficient signal features such that the minimum desirable fall detection accuracy is assured. Using data collected in simulated falls, simulated activities of daily living, and real free-living trials, all using young volunteers, the proposed approach selects four features from a set of ten commonly used features, providing a power saving of 75.3%, while limiting the error rate of a binary classification decision tree fall detection algorithm to 7.1%.Falls are a serious threat to the health of older people. A wearable fall detector can automatically detect the occurrence of a fall and alert a caregiver or an emergency response service so they may deliver immediate assistance, improving the chances of recovering from fall-related injuries. One constraint of such a wearable technology is its limited battery life. Thus, minimization of power consumption is an important design concern, all the while maintaining satisfactory accuracy of the fall detection algorithms implemented on the wearable device. This paper proposes an approach for selecting power-efficient signal features such that the minimum desirable fall detection accuracy is assured. Using data collected in simulated falls, simulated activities of daily living, and real free-living trials, all using young volunteers, the proposed approach selects four features from a set of ten commonly used features, providing a power saving of 75.3%, while limiting the error rate of a binary classification decision tree fall detection algorithm to 7.1%.

Freezing of Gait Detection in Parkinson's Disease: A Subject-Independent Detector Using Anomaly Scores

Freezing of gait (FoG) is common in Parkinsonian gait and strongly relates to falls. Current clinical FoG assessments are patients' self-report diaries and experts' manual video analysis. Both are subjective and yield moderate reliability. Existing detection algorithms have been predominantly designed in subject-dependent settings. In this paper, we aim to develop an automated FoG detector for subject independent. After extracting highly relevant features, we apply anomaly detection techniques to detect FoG events. Specifically, feature selection is performed using correlation and clusterability metrics. From a list of 244 feature candidates, 36 candidates were selected using saliency and robustness criteria. We develop an anomaly score detector with adaptive thresholding to identify FoG events. Then, using accuracy metrics, we reduce the feature list to seven candidates. Our novel multichannel freezing index was the most selective across all window sizes, achieving sensitivity (specificity) of (). On the other hand, freezing index from the vertical axis was the best choice for a single input, achieving sensitivity (specificity) of () for ankle and () for back sensors. Our subject-independent method is not only significantly more accurate than those previously reported, but also uses a much smaller window (e.g., versus ) and/or lower tolerance (e.g., versus ).Freezing of gait (FoG) is common in Parkinsonian gait and strongly relates to falls. Current clinical FoG assessments are patients' self-report diaries and experts' manual video analysis. Both are subjective and yield moderate reliability. Existing detection algorithms have been predominantly designed in subject-dependent settings. In this paper, we aim to develop an automated FoG detector for subject independent. After extracting highly relevant features, we apply anomaly detection techniques to detect FoG events. Specifically, feature selection is performed using correlation and clusterability metrics. From a list of 244 feature candidates, 36 candidates were selected using saliency and robustness criteria. We develop an anomaly score detector with adaptive thresholding to identify FoG events. Then, using accuracy metrics, we reduce the feature list to seven candidates. Our novel multichannel freezing index was the most selective across all window sizes, achieving sensitivity (specificity) of (). On the other hand, freezing index from the vertical axis was the best choice for a single input, achieving sensitivity (specificity) of () for ankle and () for back sensors. Our subject-independent method is not only significantly more accurate than those previously reported, but also uses a much smaller window (e.g., versus ) and/or lower tolerance (e.g., versus ).

Anisotropic-Scale Junction Detection and Matching for Indoor Images

Junctions play an important role in characterizing local geometrical structures of images, and the detection of which is a longstanding but challenging task. Existing junction detectors usually focus on identifying the location and orientations of junction branches while ignoring their scales, which, however, contain rich geometries of images. This paper presents a novel approach for junction detection and characterization, which especially exploits the locally anisotropic geometries of a junction and estimates its scales by relying on an a-contrario model. The output junctions are with anisotropic scales, saying that a scale parameter is associated with each branch of a junction and are thus named as anisotropic-scale junctions (ASJs). We then apply the new detected ASJs for matching indoor images, where there are dramatic changes of viewpoints and the detected local visual features, e.g., key-points, are usually insufficient and lack distinctive ability. We propose to use the anisotropic geometries of our junctions to improve the matching precision of indoor images. The matching results on sets of indoor images demonstrate that our approach achieves the state-of-the-art performance on indoor image matching.Junctions play an important role in characterizing local geometrical structures of images, and the detection of which is a longstanding but challenging task. Existing junction detectors usually focus on identifying the location and orientations of junction branches while ignoring their scales, which, however, contain rich geometries of images. This paper presents a novel approach for junction detection and characterization, which especially exploits the locally anisotropic geometries of a junction and estimates its scales by relying on an a-contrario model. The output junctions are with anisotropic scales, saying that a scale parameter is associated with each branch of a junction and are thus named as anisotropic-scale junctions (ASJs). We then apply the new detected ASJs for matching indoor images, where there are dramatic changes of viewpoints and the detected local visual features, e.g., key-points, are usually insufficient and lack distinctive ability. We propose to use the anisotropic geometries of our junctions to improve the matching precision of indoor images. The matching results on sets of indoor images demonstrate that our approach achieves the state-of-the-art performance on indoor image matching.

Summarizing Unconstrained Videos Using Salient Montages

We present a novel method to summarize unconstrained videos using salient montages (i.e., a "melange" of frames in the video as shown in Fig. 1, by finding "montageable moments" and identifying the salient people and actions to depict in each montage. Our method aims at addressing the increasing need for generating concise visualizations from the large number of videos being captured from portable devices. Our main contributions are (1) the process of finding salient people and moments to form a montage, and (2) the application of this method to videos taken "in the wild" where the camera moves freely. As such, we demonstrate results on head-mounted cameras, where the camera moves constantly, as well as on videos downloaded from YouTube. In our experiments, we show that our method can reliably detect and track humans under significant action and camera motion. Moreover, the predicted salient people are more accurate than results from state-of-the-art video salieny method [1] . Finally, we demonstrate that a novel "montageability" score can be used to retrieve results with relatively high precision which allows us to present high quality montages to users.We present a novel method to summarize unconstrained videos using salient montages (i.e., a "melange" of frames in the video as shown in Fig. 1, by finding "montageable moments" and identifying the salient people and actions to depict in each montage. Our method aims at addressing the increasing need for generating concise visualizations from the large number of videos being captured from portable devices. Our main contributions are (1) the process of finding salient people and moments to form a montage, and (2) the application of this method to videos taken "in the wild" where the camera moves freely. As such, we demonstrate results on head-mounted cameras, where the camera moves constantly, as well as on videos downloaded from YouTube. In our experiments, we show that our method can reliably detect and track humans under significant action and camera motion. Moreover, the predicted salient people are more accurate than results from state-of-the-art video salieny method [1] . Finally, we demonstrate that a novel "montageability" score can be used to retrieve results with relatively high precision which allows us to present high quality montages to users.

Fetal QT Interval Estimation Using Sequential Hypothesis Testing

Objective: Recent studies utilizing fetal magnetocardiography have demonstrated the efficacy of corrected QT interval (QTc) measurement for in utero diagnosis and prognosis of long QT syndrome, a leading cause of sudden death in early life. The objective of the study was to formulate and test a novel statistical estimation method to detect the end of the fetal T-wave and thereby improve the accuracy of fetal QT interval measurement. Methods: To detect the end of the T-wave, we apply a sequential composite hypothesis test to decide when the T-wave has returned to baseline. The method uses the generalized likelihood ratio test in conjunction with a low-rank spatiotemporal model that exploits the repetitive nature of cardiac signals. The unknown model parameters are determined using maximum likelihood estimation. Results: In realistic simulations, the detector was shown to be accurate to within 10 ms (95% prediction interval), even at noise-to-signal ratios as high as 6. When applied to real data from normal fetuses, the detector agreed well with measurements made by cardiologists ( 1.4 6.9 ms). Conclusions: The method was effective and practical. Detector performance was excellent despite the continual presence of strong maternal interference. Significance: This detector serves as a valuable adjunct to traditional measurement based on subjective assessment.Objective: Recent studies utilizing fetal magnetocardiography have demonstrated the efficacy of corrected QT interval (QTc) measurement for in utero diagnosis and prognosis of long QT syndrome, a leading cause of sudden death in early life. The objective of the study was to formulate and test a novel statistical estimation method to detect the end of the fetal T-wave and thereby improve the accuracy of fetal QT interval measurement. Methods: To detect the end of the T-wave, we apply a sequential composite hypothesis test to decide when the T-wave has returned to baseline. The method uses the generalized likelihood ratio test in conjunction with a low-rank spatiotemporal model that exploits the repetitive nature of cardiac signals. The unknown model parameters are determined using maximum likelihood estimation. Results: In realistic simulations, the detector was shown to be accurate to within 10 ms (95% prediction interval), even at noise-to-signal ratios as high as 6. When applied to real data from normal fetuses, the detector agreed well with measurements made by cardiologists ( 1.4 6.9 ms). Conclusions: The method was effective and practical. Detector performance was excellent despite the continual presence of strong maternal interference. Significance: This detector serves as a valuable adjunct to traditional measurement based on subjective assessment.

(99m)Tc-MDP bone scintigraphy of the hand: comparing the use of novel cadmium zinc telluride (CZT) and routine NaI(Tl) detectors

Background

Cadmium zinc telluride (CZT) solid-state detectors have been recently introduced in the field of nuclear medicine in cardiology and breast imaging. The aim of the current study was to evaluate the performance of the novel detectors (CZT) compared to that of the routine NaI(Tl) in bone scintigraphy. A dual-headed CZT-based camera dedicated originally to breast imaging has been used, and in view of the limited size of the detectors, the hands were chosen as the organ for assessment. This is a clinical study.

Methods

Fifty-eight consecutive patients (total 116 hands) referred for bone scan for suspected hand pathology gave their informed consent to have two acquisitions, using the routine camera and the CZT-based camera. The latter was divided into full-dose full-acquisition time (FD CZT) and reduced-dose short-acquisition time (RD CZT) on CZT technology, so three image sets were available for analysis. Data analysis included comparing the detection of hot lesions and identification of the metacarpophalangeal, proximal interphalangeal, and distal interphalangeal joints.

Results

A total of 69 hot lesions were detected on the CZT image sets; of these, 61 were identified as focal sites of uptake on NaI(Tl) data. On FD CZT data, 385 joints were identified compared to 168 on NaI(Tl) data (p < 0.001). There was no statistically significant difference in delineation of joints between FD and RD CZT data as the latter identified 383 joints.

Conclusions

Bone scintigraphy using a CZT-based gamma camera is associated with improved lesion detection and anatomic definition. The superior physical characteristics of this technique raised a potential reduction in administered dose and/or acquisition time without compromising image quality.

Arrays of Segmented, Tapered Light Guides for Use with Large, Planar Scintillation Detectors

Metabolic imaging techniques can potentially improve detection and diagnosis of cancer in women with radiodense and/or fibrocystic breasts. Our group has previously developed a high-resolution positron emission tomography imaging and biopsy device (PEM-PET) to detect and guide the biopsy of suspicious breast lesions. Initial testing revealed that the imaging field-of-view (FOV) of the scanner was smaller than the physical size of the detector's active area, which could hinder sampling of breast areas close to the chest wall. The purpose of this work was to utilize segmented, tapered light guides for optically coupling the scintillator arrays to arrays of position-sensitive photomultipliers to increase both the active FOV and identification of individual scintillator elements. Testing of the new system revealed that the optics of these structures made it possible to discern detector elements from the complete active area of the detector face. In the previous system the top and bottom rows and left and right columns were not identifiable. Additionally, use of the new light guides increased the contrast of individual detector elements by up to 129%. Improved element identification led to a spatial resolution increase by approximately 12%. Due to attenuation of light in the light guides the detector energy resolution decreased from 18.5% to 19.1%. Overall, these improvements should increase the field-of-view and spatial resolution of the dedicated breast-PET system.

Infrared Solar Physics

The infrared solar spectrum contains a wealth of physical data about our Sun, and is explored using modern detectors and technology with new ground-based solar telescopes. The scientific motivation behind exploring these wavelengths is presented, along with a brief look at the rich history of observations here. Several avenues of solar physics research exploiting and benefiting from observations at infrared wavelengths from roughly 1000 nm to 12 400 nm are discussed, and the instrument and detector technology driving this research is briefly summarized. Finally, goals for future work at infrared wavelengths are presented in conjunction with ground and space-based observations.

[Evaluation and choice of imaging protocols on the Elekta XVI(®) kilovoltage cone-beam computed tomography imaging system]

PURPOSE

This work proposes an evaluation of the Elekta XVI(®) kilovoltage cone-beam computed tomography imaging system. The average dose delivered for each acquisition protocol proposed by default by the manufacturer was measured with several detectors and compared to theoretical dose values given by Elekta. At the same time, an evaluation of image quality for pelvic protocols correlated to dose measurements in homogeneous and heterogeneous mediums allowed to optimize the use of the XVI(®) system.

MATERIALS AND METHODS

The dose was measured for each acquisition protocol (varying filters, FOV and collimations) with four detectors (CT pencil ion chamber, 0.3 and 0.125 cm(3) cylindrical ion chambers, radiothermoluminescent dosimeters) in a CTDI phantom. The dose evaluation in a heterogeneous medium was performed in an experimental anthropomorphic phantom simulating a male pelvis. Image quality was assessed with a Catphan(®) 600 phantom.

RESULTS

The average dose measured in a homogeneous medium was about 17 mGy and 25 mGy per acquisition for Pelvis and Prostate protocols and about 17 mGy and 1 mGy for Lung and Head protocols. The study performed with different detectors showed that doses obtained were of the same order of magnitude (± 10 %) and agreed with those supplied by the manufacturer. The evaluation of image quality correlated to the average dose measured allowed to optimize the use of XVI(®) acquisition protocols. Measurement results in a heterogeneous medium showed a dose decrease by a factor 1.5 for bone and by a factor 2 for titanium.

CONCLUSION

The study showed that theoretical values proposed by the manufacturer could be used to estimate the average dose delivered to the patient by the kV-CBCT imaging system. The analysis of all the results led to the implementation of a procedure allowing to optimize and account for the dose delivered to the patient by the CBCT imaging system and to report it in the patient folder.

Restrahlen to T-rays - 100 years of terahertz radiation

Although a reliable source of subpicosecondterahertz (THz) pulses, or T-rays, wasdemonstrated in the late 1980s, it was notuntil 1995, when they were used forimaging, that their full potential wasrealized. However, much of the publicityat that time seemed to suggest that verylittle research had taken place in the THz(or far-infrared) region before then. Withthe - largely new - present-day interest inbiological applications of THz radiation itis apposite to review the opening up ofthis spectral region over the past hundredyears. This paper attempts to show many ofthe significant developments in sources,detectors and spectroscopic systems for theTHz region and includes brief descriptionsof some of the more important applicationsand outcomes of the research.T-rays are only one of a number of verysignificant arrivals on the THz scene inrecent years. It does seem an ideal timeto pursue the exciting biologicalapplications of THz radiation which are tobe discussed at this Workshop.