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Jun 2012

Volume 39, Issue 6 (partial)

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POINT/COUNTERPOINT: The professions of Medical Physics and Clinical Engineering should be combined into a single profession “Clinical Science and Technology”

Wilhelm J. M. van der Putten, Ph.D., Chadd E. Smith, Ph.D., and Colin G. Orton, Ph.D., Moderator

Med. Phys. 39, 2953 (2012); http://dx.doi.org/10.1118/1.3694114 (3 pages)

Online Publication Date: 10 May 2012

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Abstract Unavailable
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87.85.-d Biomedical engineering

RADIATION THERAPY PHYSICS: Potential increase in biological effectiveness from field timing optimization for stereotactic body radiation therapy

Jonathan D. Schmitt, Graham W. Warren, and Iris Z. Wang

Med. Phys. 39, 2956 (2012); http://dx.doi.org/10.1118/1.4709605 (8 pages)

Online Publication Date: 10 May 2012

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Purpose: Stereotactic body radiation therapy (SBRT) is a radiotherapy technique which uses high dose fractions with multiple coplanar and noncoplanar beams. Due to the large fractional doses, treatments are typically protracted and there are more fields than in conventional radiation treatment schemes. The effect of temporal optimization on the biological effectiveness of SBRT is not well established.
Methods: In a cohort of actual SBRT patient treatments, the Lea–Catcheside protraction factor (G-value) was used to determine the optimal (Δ) and the least favorable (V) field. An actual field timing delivered in the clinic was included (C) for comparison. The lethal potential lethal (LPL) model was used to quantify the difference in survival fractions. Published data from three cell lines for non-small cell lung cancers: H460, H660, and H157 were used to acquire the parameters needed by the LPL model. The results are expressed as the ratios (V:Δ)N and (C:Δ)N, where N is the number fractions in the SBRT protocols and Δ, V, and C are the survival fractions calculated from the corresponding temporal patterns.
Results: The results indicate that variability in the dose rate between fields does impact the optimization results. This dependence on dose rate, however, is small compared to the impact from the variability in doses between fields. The optimized field arrangements resembled previous studies, that maximization of cell kill is achieved by orienting the fields in a Δ shape sequence, where the fields with greatest dose are positioned in the center. Minimization of cell kill was achieved with a V-shaped orientation. Smallest dose fields were positioned centrally, and higher dose fields were placed in the beginning and end of the fraction. The survival fraction ratios calculated using the LPL demonstrated that regardless of the cell type the Δ shape had lower cell survival fractions compared to both the clinical example (C) and the V arrangement. For H460, with T1/2 = 0.25 h, an average ratio of (C:Δ)5 = 13.9, suggesting the Δ pattern is approximately 14 times more effective than the clinical plan, after 5 fractions.
Conclusions: Rearranging field timing for a SBRT treatment so that maximal dose is deposited in the central fields of treatment may optimize cell kill and potentially affect overall treatment outcome.
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87.55.de Optimization
87.19.xj Cancer

RADIATION THERAPY PHYSICS: A hybrid electron and photon IMRT planning technique that lowers normal tissue integral patient dose using standard hardware

Florin Rosca

Med. Phys. 39, 2964 (2012); http://dx.doi.org/10.1118/1.4709606 (8 pages)

Online Publication Date: 10 May 2012

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Purpose: To present a mixed electron and photon IMRT planning technique using electron beams with an energy range of 6–22 MeV and standard hardware that minimizes integral dose to patients for targets as deep as 7.5 cm.
Methods: Ten brain cases, two lung, a thyroid, an abdominal, and a parotid case were planned using two planning techniques: a photon-only IMRT (IMRT) versus a mixed modality treatment (E + IMRT) that includes an enface electron beam and a photon IMRT portion that ensures a uniform target coverage. The electron beam is delivered using a regular cutout placed in an electron cone. The electron energy was chosen to provide a good trade-off between minimizing integral dose and generating a uniform, deliverable plan. The authors choose electron energies that cover the deepest part of PTV with the 65%–70% isodose line. The normal tissue integral dose, the dose for ring structures around the PTV, and the volumes of the 75%, 50%, and 25% isosurfaces were used to compare the dose distributions generated by the two planning techniques.
Results: The normal tissue integral dose was lowered by about 20% by the E + IMRT plans compared to the photon-only IMRT ones for most studied cases. With the exception of lungs, the dose reduction associated to the E + IMRT plans was more pronounced further away from the target. The average dose ratio delivered to the 0–2 cm and the 2–4 cm ring structures for brain patients for the two planning techniques were 89.6% and 70.8%, respectively. The enhanced dose sparing away from the target for the brain patients can also be observed in the ratio of the 75%, 50%, and 25% isodose line volumes for the two techniques, which decreases from 85.5% to 72.6% and further to 65.1%, respectively. For lungs, the lateral electron beams used in the E + IMRT plans were perpendicular to the mostly anterior/posterior photon beams, generating much more conformal plans.
Conclusions: The authors proved that even using the existing electron delivery hardware, a mixed electron/photon planning technique (E + IMRT) can decrease the normal tissue integral dose compared to a photon-only IMRT plan. Different planning approaches can be enabled by the use of an electron beam directed toward organs at risk distal to the target, which are still spared due the rapid dose fall-off of the electron beam. Examples of such cases are the lateral electron beams in the thoracic region that do not irradiate the heart and contralateral lung, electron beams pointed toward kidneys in the abdominal region, or beams treating brain lesions pointed toward the brainstem or optical apparatus. For brain, electron vertex beams can also be used without irradiating the whole body. Since radiation retreatments become more and more common, minimizing the normal tissue integral dose and the dose delivered to tissues surrounding the target, as enabled by E + IMRT type techniques, should receive more attention.
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87.55.dh Tissue response
87.55.dk Dose-volume analysis
87.53.Jw Therapeutic applications, including brachytherapy

ULTRASOUND PHYSICS: 3D ultrasound image segmentation using wavelet support vector machines

Hamed Akbari and Baowei Fei

Med. Phys. 39, 2972 (2012); http://dx.doi.org/10.1118/1.4709607 (13 pages)

Online Publication Date: 10 May 2012

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Purpose: Transrectal ultrasound (TRUS) imaging is clinically used in prostate biopsy and therapy. Segmentation of the prostate on TRUS images has many applications. In this study, a three-dimensional (3D) segmentation method for TRUS images of the prostate is presented for 3D ultrasound-guided biopsy.
Methods: This segmentation method utilizes a statistical shape, texture information, and intensity profiles. A set of wavelet support vector machines (W-SVMs) is applied to the images at various subregions of the prostate. The W-SVMs are trained to adaptively capture the features of the ultrasound images in order to differentiate the prostate and nonprostate tissue. This method consists of a set of wavelet transforms for extraction of prostate texture features and a kernel-based support vector machine to classify the textures. The voxels around the surface of the prostate are labeled in sagittal, coronal, and transverse planes. The weight functions are defined for each labeled voxel on each plane and on the model at each region. In the 3D segmentation procedure, the intensity profiles around the boundary between the tentatively labeled prostate and nonprostate tissue are compared to the prostate model. Consequently, the surfaces are modified based on the model intensity profiles. The segmented prostate is updated and compared to the shape model. These two steps are repeated until they converge. Manual segmentation of the prostate serves as the gold standard and a variety of methods are used to evaluate the performance of the segmentation method.
Results: The results from 40 TRUS image volumes of 20 patients show that the Dice overlap ratio is 90.3% ± 2.3% and that the sensitivity is 87.7% ± 4.9%.
Conclusions: The proposed method provides a useful tool in our 3D ultrasound image-guided prostate biopsy and can also be applied to other applications in the prostate.
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87.63.dh Ultrasonographic imaging
87.57.nm Segmentation
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RADIATION IMAGING PHYSICS: Fast on-site Monte Carlo tool for dose calculations in CT applications

Wei Chen, Daniel Kolditz, Marcel Beister, Robert Bohle, and Willi A. Kalender

Med. Phys. 39, 2985 (2012); http://dx.doi.org/10.1118/1.4711748 (12 pages)

Online Publication Date: 10 May 2012

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Purpose: Monte Carlo (MC) simulation is an established technique for dose calculation in diagnostic radiology. The major drawback is its high computational demand, which limits the possibility of usage in real-time applications. The aim of this study was to develop fast on-site computed tomography (CT) specific MC dose calculations by using a graphics processing unit (GPU) cluster.
Methods: GPUs are powerful systems which are especially suited to problems that can be expressed as data-parallel computations. In MC simulations, each photon track is independent of the others; each launched photon can be mapped to one thread on the GPU, thousands of threads are executed in parallel in order to achieve high performance. For further acceleration, the authors considered multiple GPUs. The total computation was divided into different parts which can be calculated in parallel on multiple devices. The GPU cluster is an MC calculation server which is connected to the CT scanner and computes 3D dose distributions on-site immediately after image reconstruction. To estimate the performance gain, the authors benchmarked dose calculation times on a 2.6 GHz Intel Xeon 5430 Quad core workstation equipped with two NVIDIA GeForce GTX 285 cards. The on-site calculation concept was demonstrated for clinical and preclinical datasets on CT scanners (multislice CT, flat-detector CT, and micro-CT) with varying geometry, spectra, and filtration. To validate the GPU-based MC algorithm, the authors measured dose values on a 64-slice CT system using calibrated ionization chambers and thermoluminesence dosimeters (TLDs) which were placed inside standard cylindrical polymethyl methacrylate (PMMA) phantoms.
Results: The dose values and profiles obtained by GPU-based MC simulations were in the expected good agreement with computed tomography dose index (CTDI) measurements and reference TLD profiles with differences being less than 5%. For 109 photon histories simulated in a 256 × 256 × 12 voxel thorax dataset with voxel size of 1.36 × 1.36 × 3.00 mm3, calculation times of about 70 and 24 min were necessary with single-core and multiple-core central processing unit (CPU) solutions, respectively. Using GPUs, the same MC calculations were performed in 1.27 min (single card) and 0.65 min (two cards) without a loss in quality. Simulations were thus speeded up by factors up to 55 and 36 compared to single-core and multiple-core CPU, respectively. The performance scaled nearly linearly with the number of GPUs. Tests confirmed that the proposed GPU-based MC tool can be easily adapted to different types of CT scanners and used as service providers for fast on-site dose calculations.
Conclusions: The Monte Carlo software package provides fast on-site calculation of 3D dose distributions in the CT suite which makes it a practical tool for any type of CT-specific application.
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87.50.wj Dosimetry/exposure assessment
87.57.Q- Computed tomography
87.57.nf Reconstruction
87.57.cf Spatial resolution

RADIATION THERAPY PHYSICS: On proton CT reconstruction using MVCT-converted virtual proton projections

Dongxu Wang, T. Rockwell Mackie, and Wolfgang A. Tomé

Med. Phys. 39, 2997 (2012); http://dx.doi.org/10.1118/1.4711752 (12 pages)

Online Publication Date: 10 May 2012

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Purpose: To describe a novel methodology of converting megavoltage x-ray projections into virtual proton projections that are otherwise missing due to the proton range limit. These converted virtual proton projections can be used in the reconstruction of proton computed tomography (pCT).
Methods: Relations exist between proton projections and multispectral megavoltage x-ray projections for human tissue. Based on these relations, these tissues can be categorized into: (a) adipose tissue; (b) nonadipose soft tissues; and (c) bone. These three tissue categories can be visibly identified on a regular megavoltage x-ray computed tomography (MVCT) image. With an MVCT image and its projection data available, the x-ray projections through heterogeneous anatomy can be converted to the corresponding proton projections using predetermined calibration curves for individual materials, aided by a coarse segmentation on the x-ray CT image. To show the feasibility of this approach, mathematical simulations were carried out. The converted proton projections, plotted on a proton sinogram, were compared to the simulated ground truth. Proton stopping power images were reconstructed using either the virtual proton projections only or a blend of physically available proton projections and virtual proton projections that make up for those missing due to the range limit. These images were compared to a reference image reconstructed from theoretically calculated proton projections.
Results: The converted virtual projections had an uncertainty of ±0.8% compared to the calculated ground truth. Proton stopping power images reconstructed using a blend of converted virtual projections (48%) and physically available projections (52%) had an uncertainty of ±0.86% compared with that reconstructed from theoretically calculated projections. Reconstruction solely from converted virtual proton projections had an uncertainty of ±1.1% compared with that reconstructed from theoretical projections. If these images are used for treatment planning, the average proton range uncertainty is estimated to be less than 1.5% for an imaging dose in the milligray range.
Conclusions: The proposed method can be used to convert x-ray projections into virtual proton projections. The converted proton projections can be blended with existing proton projections or can be used solely for pCT reconstruction, addressing the range limit problem of pCT using current therapeutic proton machines.
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87.57.Q- Computed tomography
87.57.nm Segmentation
87.57.nf Reconstruction
06.20.fb Standards and calibration

ULTRASOUND PHYSICS: Ultrasound-guided identification of cardiac imaging windows

Garry Liu, Xiu-Ling Qi, Normand Robert, Alexander J. Dick, and Graham A. Wright

Med. Phys. 39, 3009 (2012); http://dx.doi.org/10.1118/1.4711757 (10 pages)

Online Publication Date: 10 May 2012

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Purpose: Currently, the use of cine magnetic resonance imaging (MRI) to identify cardiac quiescent periods relative to the electrocardiogram (ECG) signal is insufficient for producing submillimeter-resolution coronary MR angiography (MRA) images. In this work, the authors perform a time series comparison between tissue Doppler echocardiograms of the interventricular septum (IVS) and concurrent biplane x-ray angiograms. Our results indicate very close agreement between the diastasis gating windows identified by both the IVS and x-ray techniques.
Methods: Seven cath lab patients undergoing diagnostic angiograms were simultaneously scanned during a breath hold by ultrasound and biplane x-ray for six to eight heartbeats. The heart rate of each patient was stable. Dye was injected into either the left or right-coronary vasculature. The IVS was imaged using color tissue Doppler in an apical four-chamber view. Diastasis was estimated on the IVS velocity curve. On the biplane angiograms, proximal, mid, and distal regions were identified on the coronary artery (CA). Frame by frame correlation was used to derive displacement, and then velocity, for each region. The quiescent periods for a CA and its subsegments were estimated based on velocity. Using Pearson’s correlation coefficient and Bland–Altman analysis, the authors compared the start and end times of the diastasis windows as estimated from the IVS and CA velocities. The authors also estimated the vessel blur across the diastasis windows of multiple sequential heartbeats of each patient.
Results: In total, 17 heartbeats were analyzed. The range of heart rate observed across patients was 47–79 beats per minute (bpm) with a mean of 57 bpm. Significant correlations (R > 0.99; p < 0.01) were observed between the IVS and x-ray techniques for the identification of the start and end times of diastasis windows. The mean difference in the starting times between IVS and CA quiescent windows was −12.0 ms. The mean difference in end times between IVS and CA quiescent windows was −3.5 ms. In contrast, the correlation between RR interval and both the start and duration of the x-ray gating windows were relatively weaker: R = 0.63 (p = 0.13) and R = 0.86 (p = 0.01). For IVS gating windows, the average estimated vessel blurs during single and multiple heartbeats were 0.5 and 0.66 mm, respectively. For x-ray gating windows, the corresponding values were 0.26 and 0.44 mm, respectively.
Conclusions: In this study, the authors showed that IVS velocity can be used to identify periods of diastasis for coronary arteries. Despite variability in mid-diastolic rest positions over multiple steady rate heartbeats, vessel blurring of 0.5–1 mm was found to be achievable using the IVS gating technique. The authors envision this leading to a new cardiac gating system that, compared with conventional ECG gating, provides better resolution and shorter scan times for coronary MRA.
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87.63.D- Ultrasonography
87.19.Wx Pneumodyamics, respiration
87.61.-c Magnetic resonance imaging
87.19.Hh Cardiac dynamics

INFRARED AND MICROWAVE IMAGING: Investigations of cabin design in UV phototherapy

David Robert Grimes, Colin J Martin, and Graeme Phanco

Med. Phys. 39, 3019 (2012); http://dx.doi.org/10.1118/1.4711812 (7 pages)

Online Publication Date: 10 May 2012

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Purpose: UVR phototherapy cabins exist in a huge variety of configurations and geometries. An accurate dose model has been developed which can be used to examine the question of cabin design to investigate factors influencing dose on a patient.
Methods: This work extends the existing dose model to entire cabins and investigates how cabin and reflector geometry influence resultant dose.
Results: The model predictions are in line with what is measured. It is found that the length and angle of the reflectors have a large influence on received dose.
Conclusions: The influence of cabin geometry is important in estimating patient dose, and the findings of this work are applicable to future cabin designs.
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87.50.wp Therapeutic applications
87.50.wj Dosimetry/exposure assessment

NUCLEAR MEDICINE PHYSICS: Histogram matching for the generation of ventilation-perfusion difference images in SPECT lung scanning: A phantom study

Jye Smith, Marissa Bartlett, and Paul Thomas

Med. Phys. 39, 3026 (2012); http://dx.doi.org/10.1118/1.4712220 (5 pages)

Online Publication Date: 10 May 2012

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Purpose: Diagnosis of acute pulmonary embolism (PE) is commonly done by acquiring SPECT scans of lung ventilation and of lung perfusion. The two image sets are compared, to identify regions which are ventilated but not perfused (“mismatched defects”). This paper describes the application of histogram matching to the calculation of a ventilation/perfusion difference image, and an investigation of the feasibility of the technique using phantom data.
Methods: An empty balloon was inserted into the lung compartment of an anthropomorphic torso phantom. The lungs were filled with polystyrene beads and with water containing 0.20 kBq/ml of 99mTc. Two scans were acquired to mimic a matched ventilation/perfusion pair. Then, 30 ml of water containing 0.01 kBq/ml of 99mTc was injected into the balloon and the phantom was rescanned. This was repeated four more times, adding 30 ml each time. Each perfusion scan thus had a mismatched defect of a different size. A CT scan was also performed after each perfusion scan, to verify the size and location of the balloon. Histogram matching was applied to each perfusion scan, which was then subtracted from the ventilation scan, yielding a difference image in which voxels with positive values identified mismatched defects. For each scan, a volume of interest (VOI) was automatically generated on the defect and was also copied across to the contralateral side to determine target to background ratios.
Results: All mismatched defects were clearly visible in the difference images, including the smallest, which corresponded in size to a small subsegmental defect. Voxel values for the mismatched defects ranged from 17 to 26, compared with contralateral regions, which had voxel values of 0 or 1.
Conclusions: Histogram matching provides a simple, automatic data-driven method for scaling ventilation and perfusion studies without user intervention.
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87.57.uh Single photon emission computed tomography (SPECT)
87.57.nf Reconstruction
87.57.nm Segmentation
87.19.X- Diseases

RADIATION MEASUREMENT PHYSICS: Establishing a standard calibration methodology for MOSFET detectors in computed tomography dosimetry

S. L. Brady and R. A. Kaufman

Med. Phys. 39, 3031 (2012); http://dx.doi.org/10.1118/1.4712221 (10 pages)

Online Publication Date: 10 May 2012

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Purpose: The use of metal-oxide-semiconductor field-effect transistor (MOSFET) detectors for patient dosimetry has increased by ∼25% since 2005. Despite this increase, no standard calibration methodology has been identified nor calibration uncertainty quantified for the use of MOSFET dosimetry in CT. This work compares three MOSFET calibration methodologies proposed in the literature, and additionally investigates questions relating to optimal time for signal equilibration and exposure levels for maximum calibration precision.
Methods: The calibration methodologies tested were (1) free in-air (FIA) with radiographic x-ray tube, (2) FIA with stationary CT x-ray tube, and (3) within scatter phantom with rotational CT x-ray tube. Each calibration was performed at absorbed dose levels of 10, 23, and 35 mGy. Times of 0 min or 5 min were investigated for signal equilibration before or after signal read out.
Results: Calibration precision was measured to be better than 5%–7%, 3%–5%, and 2%–4% for the 10, 23, and 35 mGy respective dose levels, and independent of calibration methodology. No correlation was demonstrated for precision and signal equilibration time when allowing 5 min before or after signal read out. Differences in average calibration coefficients were demonstrated between the FIA with CT calibration methodology 26.7 ± 1.1 mV cGy−1 versus the CT scatter phantom 29.2 ± 1.0 mV cGy−1 and FIA with x-ray 29.9 ± 1.1 mV cGy−1 methodologies. A decrease in MOSFET sensitivity was seen at an average change in read out voltage of ∼3000 mV.
Conclusions: The best measured calibration precision was obtained by exposing the MOSFET detectors to 23 mGy. No signal equilibration time is necessary to improve calibration precision. A significant difference between calibration outcomes was demonstrated for FIA with CT compared to the other two methodologies. If the FIA with a CT calibration methodology was used to create calibration coefficients for the eventual use for phantom dosimetry, a measurement error ∼12% will be reflected in the dosimetry results. The calibration process must emulate the eventual CT dosimetry process by matching or excluding scatter when calibrating the MOSFETs. Finally, the authors recommend that the MOSFETs are energy calibrated approximately every 2500–3000 mV.
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87.57.Q- Computed tomography
06.20.fb Standards and calibration
87.57.uq Dosimetry
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Medical Physics is an official science journal of the AAPM and of the COMP/CCPM/IOMP
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Departments of Radiology, Radiation Oncology, Biophysics, Community and Public Health, Medical College of Wisconsin
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