bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐F‐P‐09: A Global Medical Physics Collaboration for Implementation of Modern Radiotherapy in Botswana
Authors: Makufa R , Bvochora‐Nsingo M , Karumekayi T , Schneider RJ , Efstathiou JA , Dryden‐Peterson S , Odom A , Shulman A , Pipman Y , Gierga DP
Published: July 2016

Purpose:

The global burden of cancer is considerable, particularly in low and middle‐income countries. Massachusetts General Hospital (MGH) and Botswana‐Harvard AIDS Institute have partnered with the oncology community and government of Botswana to form BOTSOGO (BOTSwana Oncology Global Outreach) to address the rising burden of cancer in Botswana. Currently, radiation therapy (RT) is only available at a single linear accelerator (LINAC) in Gaborone Private Hospital (GPH). BOTSOGO worked to limit the absence of RT during a LINAC upgrade and ensure a safe transition to modern radiotherapy techniques.

Methods:

The existing Elekta Precise LINAC was decommissioned in November 2015 and replaced with a new Elekta VERSA‐HD with IMRT/VMAT/CBCT capability. Upgraded treatment planning and record‐and‐verify systems were also installed. Physicists from GPH and MGH collaborated during an intensive on‐site visit in Botswana during the commissioning process. Measurements were performed using newly purchased Sun Nuclear equipment. Photon beams were matched with an existing model to minimize the time needed for beam modeling and machine down time. Additional remote peer review was also employed. Independent dosimetry was performed by irradiating OSLDs, which were subsequently analyzed at MGH.

Results:

Photon beam quality agreed with reference data within 0.2%. Electron beam data agreed with example clinical data within 3%. Absolute dose calibration was performed using both IAEA and AAPM protocols. Absolute dose measurements with OSLDs agreed within 5%. Quentry cloud‐based software was installed to facilitate remote review of treatment plans. Patient treatments resumed in February 2016. The time without RT was reduced, therefore likely resulting in reduced patient morbidity/mortality.

Conclusion:

A global physics collaboration was utilized to commission a modern LINAC in a resource‐constrained setting. This can be a useful model in other areas with limited resources. Further use of technology and on‐site exchanges will facilitate the introduction of more advanced techniques in Botswana.

We acknowledge funding support from the AAPM International Educational Activities Committee and the NCI Federal Share Proton Beam Program Income Grant.
SU‐F‐P‐11: Long Term Dosimetric Stability of 6 TomoTherapy Systems
Authors: Smilowitz J , Dunkerley D , Geurts M , Hill P , Yadav P
Published: July 2016

Purpose:

The dosimetric stability of six TomoTherapy units was analyzed to investigate changes in performance over time and with system upgrades.

Methods:

Energy and output were tracked using monitor chamber signal, onboard MVCT detector signal and external ion chamber measurements. The systems (and monitoring periods) include 3 Hi‐Art (67, 61 and 65 mos.), 2 HDA (29 and 25 mos.) and one research unit (7 mo.). Dose Control Stability system (DCS) was installed on 4 systems. Output stability is reported as deviation from reference monitor chamber signal for all systems, and from an external chamber for 4 systems. Energy stability was monitored using the relative (center versus off‐axis) MVCT detector signal and/or the ratio of chamber measurements at 2 depths. The results from the clinical systems were used to benchmark the stability of the research unit, which has the same linear accelerator but runs at a higher dose rate.

Results:

The output based on monitor chamber data of all six systems is very stable. Non‐ DCS had a standard deviation of 1.7% and 1.8%. As expected, DCS systems had improved standard deviation: 0.003–0.05%. The energy was also very stable for all units. The standard deviation in exit detector flatness was 0.02–0.3%. Ion chamber output and 20/10 cm ratios supported these results. The stability for the research system, as monitored with a variety of metrics, is on par with the existing systems.

Conclusion:

The output and energy of six TomoTherapy units over a total of almost 10 years is quite stable. For each system, the results are consistent between the different measurement tools and techniques, proving not only the dosimetric stability, but that these quality parameters can be confirmed with various metrics. A research unit operating at a higher dose rate performed as well as the clinical treatment units.

University of Wisconsin and Accuray Inc. (vendor of TomoTherapy systems) have a research agreement which supplies funds for research to the University. This project was partially supporting with these funds.
SU‐F‐P‐24: Radiological Disperse Device
Authors: Alam R
Published: July 2016

Purpose:

We are now living in a society of constant fear of terrorism. This topic is pertaining to give a general knowledge of what is a radiological dispersion device or RDD and in case of its detonation, what are the options open to public for a safe action in terms of reducing the exposure and knowing the proper steps. These RDD are also called dirty bombs.

Methods:

Compared to nuclear weapons, dirty bombs are easy to make. In order for a terrorist organization to construct and detonate a dirty bomb, it must acquire radioactive material by stealing it or buying it through legal or illegal channels. Possible RDD material could come from the millions of radioactive sources used in the industry, for medical purposes and in academic applications mainly for researches. These are, americium‐241, californium‐252, caesium‐137, cobalt‐60, iridium‐192, plutonium‐238, polonium‐210, radium‐226 and strontium‐90.

Results:

Prompt detection of the type of radioactive material used will greatly assist advising people on the protective measures, like sheltering in place, or quickly leaving the immediate area. The effects of radiation are determined by:°the amount of radiation absorbed by body°the type of radiation °the distance from the radiation to an individual°the means of exposure absorbed by the skin, inhaled, or ingested; and length of time exposed.

Conclusion:

In any facility it is now much more important to keep a log list of all radioactive materials in use. In case there is a dirty bomb explosion, the chaos and economic cost could be enormous. The economic cost for the evaluation of the contamination, survey of people and surroundings and the after treatment, decontamination cost and effort will be a big challenge in any country. So awareness and preparation is the start to face this new type of challenge.
SU‐F‐P‐27: The Study of Actual DVH for Target and OARs During the Radiotherapy of Non‐Small Cell Lung Cancer
Authors: Ma C , Yin Y
Published: July 2016

Purpose:

To analyze the changes of the volume and dosimetry of target and organs at risk (OARs) by comparing the daily CBCT images and planning CT images of the patients with Non‐Small Cell Lung Cancer (NSCLC) and analyze the difference between planned dose and accumulated dose.

Methods:

This study retrospectively analyzed eight cases of non‐small cell lung cancer patients who accepted CRT or IMRT treatment and KV‐CBCT. For each patient, the prescription dose was 60Gy and the fraction dose was 2Gy. Deform the daily CBCT images to planning CT images by the mapping of registration to compare the planning dose with cumulative dose of targets and organs at risk in RayStation.

Results:

The average volume of GTV of 8 patients with CBCT was 88.26% of the original volume. The average plan dose of GTV was 64.49±2.40Gy. The accumulated dose of GTV was 60.13±2.70Gy (P≤0.05). The average volume of PTV to reach the prescription dose was 95.59% for original plan and 81.47% for accumulated plan (P≤0.05). The volume changes of the left and right lung of the original volume was 88.95% and 80.32%, respectively. The average dose of the left and right lung of original plan was 9.31±1.75Gy and 4.33±1.10Gy, respectively(P≥0.05). The average accumulated dose was 9.63±1.96Gy and 4.63±1.36Gy, respectively(P≥0.05). The average plan dose and accumulated dose of heart was 6.88±1.70Gy and 6.38±0.91Gy, respectively (P≥0.05). The average plan maximum dose and accumulated dose for spinal cord was 24.62±5.91Gy and 26.00±5.14Gy, respectively (P≥0.05).

Conclusion:

The changes of target anatomical structure with NSCLC make difference between the planned dose and cumulative dose. With the dose deformation method, the dose gap can be found between planning dose and delivery dose.
SU‐F‐P‐33: Combining Research and Professional Practice in the Clinical Setting: A Medical Physicist Personal Experience
Authors: López‐Tarjuelo J
Published: July 2016

Purpose:

To initiate a discussion on the current and evolving role of Medical Physicists based on author's professional and research experience in patient safety and quality control.

Methods:

Several professionals of the departments of Medical Physics and Radiation Oncology, chiefly devoted to clinical tasks, began a research program on patient safety and quality control in a framework provided by the implementation of intraoperative radiotherapy (IORT). We performed studies on virtual simulation for IORT, in vivo dosimetry, failure mode and effect analysis (FMEA), statistical process control (SPC), and receiver operating characteristics of dosimetric equipment. This was done with the support of our research foundation and different grants while continuing with our departmental clinical routine involving about 1600 annual treatments with two linacs and different brachytherapy techniques.

Results:

We published 5 papers in international journals in the last two years. This author conducted a doctoral research which resulted in a dissertation in 2015. The extra time spent after treatments was essential to succeed. Funding and support achieved via our foundation played a crucial role; but this would have not been possible without punctual external mentoring and partnership. FMEA conclusions were able to be implemented only with staff commitment; however, conclusions concerning equipment cannot be easily communicated to manufacturers. These tasks required extra training in the appropriated methods.

Conclusion:

Research needed the support of a dedicated foundation, which would have been very difficult to obtain with the sole participation of our departments. FMEA and SPC results may need engagement of staff and manufacturers, respectively, hard to achieve without strong recommendations or even a regulatory framework. All these fields need evolution of Medical Physicists’ roles and additional training. Devotion to both clinical tasks and research could be unfeasible for Medical Physicists in the clinical setting without the appropriate rearrangement of their schedules and tasks.

Supported by grants IPT‐300000‐2010‐3 and PI11/01659. ERDF funds and Spanish Government.
SU‐F‐P‐38: Professional Practice Evaluation and Quality Improvement
Authors: Rong J
Published: July 2016

Purpose:

In 2008, The Joint Commission (JC) implemented a standard mandating clearly defined quality improvement metrics to be factored into the evaluation of medical practitioners’ professional performance as part of the process of granting and maintaining medical staff privileges in a hospital. Specifically, there are two processes for a credentialed medical staff member to go through: Ongoing Professional Practice Evaluation (OPPE) and Focused Professional Practice Evaluation (FPPE). This is an unfamiliar area to many of our medical physicists. The process of implementing Professional Practice Evaluation (PPE) into clinical practice is rather complex. It requires a considerable amount of work and collaboration. The quality metrics are typically different for physicists than physicians, and are specialty specific (therapy physicists vs. imaging physicists). However, in the future, some clinical medical physicists will likely be involved in this process for quality improvement. This presentation will provide an update to clinical medical physicists regarding OPPE and FPPE as well as discuss how to implement PPE in medical physics practice.

Methods:

Provide an overall of JC requirements and OPPE/FPPE.Discuss quality improvement metrics for clinical medical physicists.Evaluate methods/tools for meaningful data collection.Demonstrate the process of implementing PPE into clinical practice.

Results:

By understanding the concepts of OPPE and FPPE and the JC requirements, the clinical medical physicists will be better prepared for going through the credentialing process and achieving quality improvement.

Conclusion:

Sooner or later the clinical medical physicists will likely be involved in the process of PPE. It is challenging but also an opportunity for the medical physicists to become members of medical staffs of their institutions. AAPM as a group should start preparing for and/or implementing PPE in their clinical practices for achieving quality improvement.
SU‐F‐R‐44: Modeling Lung SBRT Tumor Response Using Bayesian Network Averaging
Authors: Diamant A , El Naqa I , Ybarra N , Seuntjens J
Published: July 2016

Purpose:

The prediction of tumor control after a patient receives lung SBRT (stereotactic body radiation therapy) has proven to be challenging, due to the complex interactions between an individual's biology and dose‐volume metrics. Many of these variables have predictive power when combined, a feature that we exploit using a graph modeling approach based on Bayesian networks. This provides a probabilistic framework that allows for accurate and visually intuitive predictive modeling. The aim of this study is to uncover possible interactions between an individual patient's characteristics and generate a robust model capable of predicting said patient's treatment outcome.

Methods:

We investigated a cohort of 32 prospective patients from multiple institutions whom had received curative SBRT to the lung. The number of patients exhibiting tumor failure was observed to be 7 (event rate of 22%). The serum concentration of 5 biomarkers previously associated with NSCLC (non‐small cell lung cancer) was measured pre‐treatment. A total of 21 variables were analyzed including: dose‐volume metrics with BED (biologically effective dose) correction and clinical variables. A Markov Chain Monte Carlo technique estimated the posterior probability distribution of the potential graphical structures. The probability of tumor failure was then estimated by averaging the top 100 graphs and applying Baye's rule.

Results:

The optimal Bayesian model generated throughout this study incorporated the PTV volume, the serum concentration of the biomarker EGFR (epidermal growth factor receptor) and prescription BED. This predictive model recorded an area under the receiver operating characteristic curve of 0.94(1), providing better performance compared to competing methods in other literature.

Conclusion:

The use of biomarkers in conjunction with dose‐volume metrics allows for the generation of a robust predictive model. The preliminary results of this report demonstrate that it is possible to accurately model the prognosis of an individual lung SBRT patient's treatment.
SU‐F‐R‐47: Quantitative Shape Relationship Analysis of PTV Modification for Critical Anatomy Sparing and Its Impact On Pathologic Response for Neoadjuvant Stereotactic Radiotherapy for Pancreatic Cancer
Authors: Cheng Z , Rosati L , Chen L , Robertson S , Moore J , Peng L , Mian O , Narang A , Hacker‐Prietz A , Herman J , McNutt T
Published: July 2016

Purpose:

Stereotactic body radiation therapy (SBRT) may be used to increase surgery candidacy in borderline resectable (BRPC) and locally advanced (LAPC) pancreatic cancer. However, the planning target volume (PTV) may need to be limited to avoid toxicity when the gross tumor volume (GTV) is anatomically involved with surrounding critical structures. Our study aims to characterize the coverage of GTV and investigate the association between modified PTV and pathologic (pCR) or near pathologic (npCR) complete response rates determined from the surgical specimen.

Methods:

Patients treated with neoadjuvant pancreas SBRT followed by surgery from 2010–2015 were selected from Oncospace. Overlap volume histogram (OVH) analysis was performed to determine the extent of compromise of the PTV from both the GTV and a standard target (GTV+3mm). Subsequently, normalized overlap volume (%) was calculated for: (1) GTV‐PTV, and (2) GTV+3mm expansion‐PTV. A logistic regression model was used to identify the association between the overlap ratios and ≥ npCR(pCR/npCR) stratified by active breathing control (ABC) versus free‐breathing status.

Results:

Eighty‐one (BRPC: n=42, LAPC: n=39) patients were available for analysis. Nearly 40% (31/81) had ≥npCR and 75% (61/81) were able to complete ABC. Mean coverage of the GTV‐PTV was 92.6% (range, 59.9%–100%, SD = 8.68) and coverage of the GTV+3mm expansion‐PTV was 85. 2% (range, 59.9% −100.0%, SD= 8.67). Among the patients with ABC, every 10% increase in GTV coverage doubled the odds to have ≥npCR (OR = 1.82, p=0.06). Coverage of GTV+3mm expansion was not associated with ≥npCR regardless of ABC status.

Conclusion:

Preferential sparing of critical anatomy over GTV‐PTV coverage with ABC management suggests worse ≥npCR rates for neoadjuvant SBRT in BRPC and LAPC. Limiting the GTV and GTV+3mm expansion in free‐breathing patients was not associated with pathologic response perhaps due to larger GTV definitions as a result of motion artifacts in free‐breathing CT scans.

Collaboration with Toshiba, Elekta, and Phillips
SU‐F‐R‐50: Radiation‐Induced Changes in CT Number Histogram During Chemoradiation Therapy for Pancreatic Cancer
Authors: Chen X , Schott D , Song Y , Li D , Hall W , Erickson B , Li X
Published: July 2016

Purpose:

In an effort of early assessment of treatment response, we investigate radiation induced changes in CT number histogram of GTV during the delivery of chemoradiation therapy (CRT) for pancreatic cancer.

Methods:

Diagnostic‐quality CT data acquired daily during routine CT‐guided CRT using a CT‐on‐rails for 20 pancreatic head cancer patients were analyzed. All patients were treated with a radiation dose of 50.4 in 28 fractions. On each daily CT set, the contours of the pancreatic head and the spinal cord were delineated. The Hounsfiled Units (HU) histogram in these contourswere extracted and processed using MATLAB. Eight parameters of the histogram including the mean HU over all the voxels, peak position, volume, standard deviation (SD), skewness, kurtosis, energy, and entropy were calculated for each fraction. The significances were inspected using paired two‐tailed t‐test and the correlations were analyzed using Spearman rank correlation tests.

Results:

In general, HU histogram in pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the first to the last fraction in mean HU in pancreatic head ranged from −13.4 to 3.7 HU with an average of −4.4 HU, which was significant (P<0.001). Among other quantities, the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less sharp) during the CRT delivery. The changes of mean HU, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response status is associated with the changes of SD (ΔSD), i.e., ΔSD= 1.85 (average of 7 patients) for good reponse, −0.08 (average of 6 patients) for moderate and poor response.

Conclusion:

Significant changes in HU histogram and the histogram‐based metrics (e.g., meam HU, skewness, and kurtosis) in tumor were observed during the course of chemoradiation therapy for pancreas cancer. These changes may be potentially used for early assessment of treatment response.
SU‐F‐R‐55: Early Detection of Treatment Induced Bone Marrow Injury During Chemoradiation Therapy Using Quantitative CT
Authors: Chen X , Song Y , Erickson B , Li X
Published: July 2016

Purpose:

Acute hematologic toxicity associated with bone marrow injury is a common complication of chemoradiation therapy (CRT) for pelvic malignancies. In this work, we investigate the feasibility of using quantitative CT to detect bone marrow injury during CRT.

Methods:

Daily CTs were acquired during routine CT‐guided radiation therapy using a CT‐on‐rails for 15 cervical cancer patients. All patients treated with a radiation dose of 45.0 to 50.4 Gy in 1.8 Gy/fraction along with chemotherapy. For each patient, the contours of bone marrow were generated in L4, L5 and sacrum on the first daily CT and then populated to other daily CTs by rigid registration using MIM (MIM Software Inc., Cleveland, OH) with manual editing if possible. A series of CT texture parameters, including Hunsfield Unit (HU) histogram, mean HU, entropy, energy, in bone marrow contours were calculated using MATLAB on each daily CT and were correlated with the completed blood counts (CBC) collected weekly for each patient. The correlations were analyzed with Pearson correlation tests.

Results:

For all patient data analyzed, mean HU in bone marrow decreased during CRT delivery. From the first to the last fraction the average mean HU reduction is 58.1 ± 13.6 HU (P<0.01). This decrease can be observed as early as after first 5 fractions and is strongly associated with the changes of most CBC quantities, such as the reductions of white and blood cell counts (r=0.97, P=0.001). The reduction of HU is spatially varied.

Conclusion:

Chemoradiation induced bone marrow injury can be detected during the delivery of CRT using quantitative CT. Chemoradiation results in reductions in mean HU, which are strongly associated with the change in the pretrial blood cell counts. Early detection of bone marrow injury with commonly available CT opens a door to improve bone marrow sparing, reducing risk of hematologic toxicity.
SU‐F‐I‐01: Normalized Mean Glandular Dose Values for Dedicated Breast CT Using Realistic Breast‐Shaped Phantoms
Authors: Hernandez A , Boone J
Published: July 2016

Purpose:

To estimate normalized mean glandular dose values for dedicated breast CT (DgN‐CT) using breast CT‐derived phantoms and compare to estimations using cylindrical phantoms.

Methods:

Segmented breast CT (bCT) volume data sets (N=219) were used to measure effective diameter profiles and were grouped into quintiles by volume. The profiles were averaged within each quintile to represent the range of breast sizes found clinically. These profiles were then used to generate five voxelized computational phantoms (V1, V2, V3, V4, V5 for the small to large phantom sizes, respectively), and loaded into the MCNP6 lattice geometry to simulate normalized mean glandular dose coefficients (DgN‐CT) using the system specifications of the Doheny‐prototype bCT scanner in our laboratory. The DgN‐CT coefficients derived from the bCT‐derived breast‐shaped phantoms were compared to those generated using a simpler cylindrical phantom using a constant volume, and the following constraints: (1) Length=1.5*radius; (2) radius determined at chest wall (Rcw), and (3) radius determined at the phantom center‐of‐mass (Rcm).

Results:

The change in Dg‐NCT coefficients averaged across all phantom sizes, was ‐ 0.5%, 19.8%, and 1.3%, for constraints 1–3, respectively. This suggests that the cylindrical assumption is a good approximation if the radius is taken at the breast center‐of‐mass, but using the radius at the chest wall results in an underestimation of the glandular dose.

Conclusion:

The DgN‐CT coefficients for bCT‐derived phantoms were compared against the assumption of a cylindrical phantom and proved to be essentially equivalent when the cylinder radius was set to r=1.5/L or Rcm. While this suggests that for dosimetry applications a patient's breast can be approximated as a cylinder (if the correct radius is applied), this assumes a homogenous composition of breast tissue and the results may be different if the realistic heterogeneous distribution of glandular tissue is considered.

Research reported in this paper was supported in part by the National Cancer Institute of the National Institutes of Health under award R01CA181081. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institue of Health.
SU‐F‐I‐08: CT Image Ring Artifact Reduction Based On Prior Image
Authors: Yuan C , Qi H , Chen Z , Wu S , Xu Y , Zhou L
Published: July 2016

Purpose:

In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don't work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images.

Methods:

The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre‐set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact‐free CT images.

Results:

We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp‐Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact‐free images when the dead bins rating is under 30%. The dead‐bin‐induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case.

Conclusion:

A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact‐free CT images feasibly and effectively.
SU‐F‐I‐09: Improvement of Image Registration Using Total‐Variation Based Noise Reduction Algorithms for Low‐Dose CBCT
Authors: Mukherjee S , Farr J , Merchant T , Yao W
Published: July 2016

Purpose:

To study the effect of total‐variation based noise reduction algorithms to improve the image registration of low‐dose CBCT for patient positioning in radiation therapy.

Methods:

In low‐dose CBCT, the reconstructed image is degraded by excessive quantum noise. In this study, we developed a total‐variation based noise reduction algorithm and studied the effect of the algorithm on noise reduction and image registration accuracy. To study the effect of noise reduction, we have calculated the peak signal‐to‐noise ratio (PSNR). To study the improvement of image registration, we performed image registration between volumetric CT and MV‐ CBCT images of different head‐and‐neck patients and calculated the mutual information (MI) and Pearson correlation coefficient (PCC) as a similarity metric. The PSNR, MI and PCC were calculated for both the noisy and noise‐reduced CBCT images.

Results:

The algorithms were shown to be effective in reducing the noise level and improving the MI and PCC for the low‐dose CBCT images tested. For the different head‐and‐neck patients, a maximum improvement of PSNR of 10 dB with respect to the noisy image was calculated. The improvement of MI and PCC was 9% and 2% respectively.

Conclusion:

Total‐variation based noise reduction algorithm was studied to improve the image registration between CT and low‐dose CBCT. The algorithm had shown promising results in reducing the noise from low‐dose CBCT images and improving the similarity metric in terms of MI and PCC.
SU‐F‐I‐20: Volumetric Reduction of the Corpus Callosum in Alzheimer's Disease and Mild Cognitive Impairment
Authors: Juh R , Suh T , Han J , Kim C , Oh C
Published: July 2016

Purpose:

This study investigated correlations between regional corpus callosum (CC) atrophy and cognitive measurements in AD subjects at mild disease stages with volumetry. Our aims were to replicate ROI‐based findings of reduced volumes of the CC in mild cognitive impairment (MCI) patients relative to AD and to investigate, on a voxel‐by‐voxel basis, the presence of significant correlations between CC atrophy and cognitive test scores in AD subjects.

Methods:

We used the VBM and cross‐sectional ROI‐based volumetry approach to conduct a detailed assessment of CC volumetric reductions in a probable AD patient (n=40) in comparison to MCI (n=40) and Subjective memory impairment (SMI) (n=12) matched for age. Statistical comparisons were performed using the general linear model.

Results:

The volumetric reduction of the posterior portion of the CC body, which inter‐connects cortical regions that are also early affected in AD (mean area at mid intersection, AD=510.7mm2/MCI=515.6mm2/SMI=603/9mm2, relative %ratio: AD=0.27/MCI=0.3/SMI=0.4) such as the superior temporal lobes, is also consistent with results of previous ROI‐based morphometric MRI studies. Significant CC atrophy was detected in the anterior‐superior portion of the splenium, the isthmus, the anterior and posterior portions of the CC body. Structural abnormalities of the CC splenium may be secondary to an early primary neuronal loss in AD involving parieto‐temporal neocortical regions, which are interhemispherically connected by this callosal portion.

Conclusion:

Our results confirm of diffuse volumetric CC reductions in the AD, and warrant further evaluation of the relevance of atrophic changes in anterior CC portions to the cognitive impairments that characterize the disorder. A cluster of significant positive correlation with MMSE scores was seen on the left anterior CC body. The VBM results reported showed that in predominantly AD subjects, foci of atrophy are present in several portions of the CC, involving the anterior‐superior portion of the splenium and the isthmus.
SU‐F‐I‐27: Measurement of SAR and Temperature Elevation During MRI Scans
Authors: Seo Y
Published: July 2016

Purpose:

The poor reliability and repeatability of the manufacturer‐reported SAR values on clinical MRI systems have been acknowledged. The purpose of this study is to not only measure SAR values, but also RF‐induced temperature elevation at 1.5 and 3T MRI systems.

Methods:

SAR measurement experiment was performed at 1.5 and 3T. Three MRI RF sequences (T1w TSE, T1w inversion recovery, and T2w TSE) with imaging parameters were selected. A hydroxyl‐ethylcelluose (HEC) gelled saline phantom mimicking human body tissue was made. Human torso phantom were constructed, based on Korean adult standard anthropometric reference data (Fig.1). FDTD method was utilized to calculate the SAR distribution using Sim4Life software. Based on the results of the simulation, 4 electrical field (E‐field) sensors were located inside the phantom. 55 Fiber Bragg Grating (FBG) temperature sensors (27 sensors in upper and lower cover lids, and one sensor located in the center as a reference) were located inside the phantom to measure temperature change during MRI scan (Fig.2).

Results:

Simulation shows that SAR value is 0.4 W/kg in the periphery and 0.001 W/kg in the center (Fig.2). One 1.5T and one of two 3T MRI systems represent that the measured SAR values were lower than MRI scanner‐reported SAR values. However, the other 3T MRI scanner shows that the averaged SAR values measured by probe 2, 3, and 4 are 6.83, 7.59, and 6.01 W/kg, compared to MRI scanner‐reported whole body SAR value (<1.5 W/kg) for T2w TSE (Table 1). The temperature elevation measured by FBG sensors is 5.2°C in the lateral shoulder, 5.1°C in the underarm, 4.7°C in the anterior axilla, 4.8°C in the posterior axilla, and 4.8°C in the lateral waist for T2w TSE (Fig.3).

Conclusion:

It is essential to assess the safety of MRI system for patient by measuring accurate SAR deposited in the body during clinical MRI.
SU‐F‐I‐31: Reproducibility of An Automatic Exposure Control Technique in the Low‐Dose CT Scan of Cardiac PET/CT Exams
Authors: Park M , Rosica D , Agarwal V , Di Carli M , Dorbala S
Published: July 2016

Purpose:

Two separate low‐dose CT scans are usually performed for attenuation correction of rest and stress N‐13 ammonia PET/CT myocardial perfusion imaging (PET/CT). We utilize an automatic exposure control (AEC) technique to reduce CT radiation dose while maintaining perfusion image quality. Our goal is to assess the reproducibility of displayed CT dose index (CTDI) on same‐day repeat CT scans (CT1 and CT2).

Methods:

Retrospectively, we reviewed CT images of PET/CT studies performed on the same day. Low‐dose CT utilized AEC technique based on tube current modulation called Smart‐mA. The scan parameters were 64 × 0.625mm collimation, 5mm slice thickness, 0.984 pitch, 1‐sec rotation time, 120 kVp, and noise index 50 with a range of 10–200 mA. The scan length matched with PET field of view (FOV) with the heart near the middle of axial FOV. We identified the reference slice number (RS) for an anatomical landmark (carina) and used it to estimate axial shift between two CTs. For patient size, we measured an effective diameter on the reference slice. The effect of patient positioning to CTDI was evaluated using the table height. We calculated the absolute percent difference of the CTDI (%diff) for estimation of the reproducibility.

Results:

The study included 168 adults with an average body‐mass index of 31.72 ± 9.10 (kg/m2) and effective diameter was 32.72 ± 4.60 cm. The average CTDI was 1.95 ± 1.40 mGy for CT1 and 1.97 ± 1.42mGy for CT2. The mean %diff was 7.8 ± 6.8%. Linear regression analysis showed a significant correlation between the table height and %diff CTDI. (r=0.82, p<0.001)

Conclusion:

We have shown for the first time in human subjects, using two same‐day CT images, that the AEC technique in low‐dose CT is reproducible within 10% and significantly depends on the patient centering.
SU‐F‐I‐41: Calibration‐Free Material Decomposition for Dual‐Energy CT
Authors: Zhao W , Xing L , Zhang Q , Xiong G , Min J
Published: July 2016

Purpose:

To eliminate tedious phantom calibration or manually region of interest (ROI) selection as required in dual‐energy CT material decomposition, we establish a new projection‐domain material decomposition framework with incorporation of energy spectrum.

Methods:

Similar to the case of dual‐energy CT, the integral of the basis material image in our model is expressed as a linear combination of basis functions, which are the polynomials of high‐ and low‐energy raw projection data. To yield the unknown coefficients of the linear combination, the proposed algorithm minimizes the quadratic error between the high‐ and low‐energy raw projection data and the projection calculated using material images. We evaluate the algorithm with an iodine concentration numerical phantom at different dose and iodine concentration levels. The x‐ray energy spectra of the high and low energy are estimated using an indirect transmission method. The derived monochromatic images are compared with the high‐ and low‐energy CT images to demonstrate beam hardening artifacts reduction. Quantitative results were measured and compared to the true values.

Results:

The differences between the true density value used for simulation and that were obtained from the monochromatic images, are 1.8%, 1.3%, 2.3%, and 2.9% for the dose levels from standard dose to 1/8 dose, and are 0.4%, 0.7%, 1.5%, and 1.8% for the four iodine concentration levels from 6 mg/mL to 24 mg/mL. For all of the cases, beam hardening artifacts, especially streaks shown between dense inserts, are almost completely removed in the monochromatic images.

Conclusion:

The proposed algorithm provides an effective way to yield material images and artifacts‐free monochromatic images at different dose levels without the need for phantom calibration or ROI selection. Furthermore, the approach also yields accurate results when the concentration of the iodine concentrate insert is very low, suggesting the algorithm is robust with respect to the low‐contrast scenario.
SU‐F‐I‐45: An Automated Technique to Measure Image Contrast in Clinical CT Images
Authors: Sanders J , Abadi E , Meng B , Samei E
Published: July 2016

Purpose:

To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams.

Methods:

An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standard deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non‐contrast enhanced chest CT clinical datasets were examined in the validation procedure.

Results:

The algorithm successfully measured the histograms of the four organs in both contrast and non‐contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998.

Conclusion:

Patient‐specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non‐enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies that may not be captured in phantom data.
SU‐F‐I‐47: Optimizing Protocols for Image Quality and Dose in Abdominal CT of Large Patients
Authors: Johnson L , Yester M
Published: July 2016

Purpose:

Newer CT scanners are able to use scout views to adjust mA throughout the scan in order to achieve a given noise level. However, given constraints of radiologist preferences for kVp and rotation time, it may not be possible to achieve an acceptable noise level for large patients. A study was initiated to determine for which patients kVp and/or rotation time should be changed in order to achieve acceptable image quality.

Methods:

Patient scans were reviewed on two new Emergency Department scanners (Philips iCT) to identify patients over a large range of sizes. These iCTs were set with a limit of 500 mA to safeguard against a failure that might cause a CT scan to be (incorrectly) obtained at too‐high mA. Scout views of these scans were assessed for both AP and LAT patient width and AP and LAT standard deviation in an ROI over the liver. Effective diameter and product of the scout standard deviations over the liver were both studied as possible metrics for identifying patients who would need kVp and/or rotation time changed. The mA used for the liver in the CT was compared to these metrics for those patients whose CT scans showed acceptable image quality.

Results:

Both effective diameter and product of the scout standard deviations over the liver result in similar predictions for which patients will require the kVp and/or rotation time to be changed to achieve an optimal combination of image quality and dose.

Conclusion:

Two mechanisms for CT technologists to determine based on scout characteristics what kVp, mA limit, and rotation time to use when DoseRight with our physicians’ preferred kVp and rotation time will not yield adequate image quality are described.
SU‐F‐I‐48: Variability in CT Scanning Over‐Range Across Clinical Operation
Authors: Ria F , Wilson J M , Guntzer P , Zanca F , Samei E
Published: July 2016

Purpose:

Inconsistency in the scan range for a given protocol can be a source of variability in patient dose. The purpose of this study was to determine the variability in the over‐scan length in clinical CT operation for chest and abdominopelvic (A&P) protocols.

Methods:

A total of 51 abdomen‐pelvis and 121 chest CT exams were randomly selected from our clinical database. A commercial dose monitoring solution was used to extract and database the total exposure area and the geometrical information related to automatically‐segmented anatomical landmarks for each target region. The data were exported off‐line for the statistical analysis. The over‐scan length (delta) was calculated as the difference between the real scanned length and ideal scanning length based on the anatomical landmarks for each target region.

Results:

The mean delta for abdomen‐pelvis exams was 12 mm (median 8 mm; min −191 mm; max 158 mm; standard deviation 71 mm). The average delta values at the interfaces with the chest and lower extremity regions were 69 mm and −57 mm, respectively. For chest exams, the average delta was 91 mm (median 93 mm; min 36 mm; max 190 mm; standard deviation 29 mm), and the average delta values at interfaces with the neck and abdomen regions were 26 mm and 65 mm, respectively. The percentage delta mean related to the abdomen‐pelvis and chest lengths were 3% and 45%, respectively.

Conclusion:

Although there is greater over‐scan in the chest region, there is considerably more variability in the over‐scan area for abdomen‐pelvis exams. Estimation of the over‐scan length must be included in the effective dose estimates, which uses different coefficients for different target region (ICRP 102). Furthermore, knowledge of over‐scan lengths and variability can guide steps to improve clinical consistency and operation.
SU‐F‐I‐51: CT/MR Image Deformation: The Clinical Assessment QA in Target Delineation
Authors: Yang C , Chen Y
Published: July 2016

Purpose:

To study the deformation effects in CT/MR image registration of head and neck (HN) cancers. We present a clinical indication in guiding and simplifying registration procedures of this process while CT images possessed artifacts.

Methods:

CT/MR image fusion provides better soft tissue contrast in intracranial GTV definition with artifacts. However, whether the fusion process should include the deformation process is questionable and not recommended. We performed CT/MR image registration of a HN patient with tonsil GTV and nodes delineation on Varian Velocity™ system. Both rigid transformation and deformable registration of the same CT/MR imaging data were processed separately. Physician's selection of target delineation was implemented to identify the variations. Transformation matrix was shown with visual identification, as well as the deformation QA numbers and figures were assessed.

Results:

The deformable CT/MR images were traced with the calculated matrix, both translation and rotational parameters were summarized. In deformable quality QA, the calculated Jacobian matrix was analyzed, which the min/mean/max of 0.73/0/99/1.37, respectively. Jacobian matrix of right neck node was 0.84/1.13/1.41, which present dis‐similarity of the nodal area. If Jacobian = 1, the deformation is at the optimum situation. In this case, the deformation results have shown better target delineation for CT/MR deformation than rigid transformation. Though the root‐mean‐square vector difference is 1.48 mm, with similar rotational components, the cord and vertebrae position were aligned much better in the deformable MR images than the rigid transformation.

Conclusion:

CT/MR with/without image deformation presents similar image registration matrix; there were significant differentiate the anatomical structures in the region of interest by deformable process. Though vendor suggested only rigid transformation between CT/MR assuming the geometry remain similar, our findings indicated with patient positional variations, deformation registration is needed to generate proper GTV coverage, which will be irradiated more accurately in the following boost phase.
SU‐F‐I‐62: A Dcm4chee Log Analyzer for Monitoring DICOM Network Performance
Authors: Moriyama M , Murakami Y , Ohki M , Tokumori K , Okamoto S
Published: July 2016

Purpose:

The dcm4chee is an open source software for making a high‐performance DICOM server. The process of dcm4chee is recorded in a log as text file. It takes a lot of time to read the log file for checking DICOM server performance. Therefore, we made a log analyzer for dcm4chee, which compiles the statistics on image transfer between DICOM server and imaging devices.

Methods:

The log analysis program was written in Perl (practical extraction and report language). ChartDirector, a chart component for creating charts for web applications was also used. The log analyzer was installed in DICOM server and invoked with a common gateway interface (CGI). The dcm4chee‐2.18.1‐mysql version using MySQL database software was used in this study. The hardware of our DICOM server for educational use was an Apple Mac mini computer (2.6GHz, Intel Core i5, 8 GB RAM) and two 6TB hard disks.

Results:

Users can specify the beginning and end dates to analyze in the start page of this log analyzer. Three types of output can also be chosen, which are the number of transferred images from each imaging device to the DICOM server in sequence, the total number of transferred images from each imaging device to the server in the period, and the temporal variation in free disk space of the server. These results are shown in the tabular and graph form on a web page.

Conclusion:

The log analyzer in this study makes it easy to get information on the usage of a dcm4chee DICOM server and should be available for the management of the PACS system using dcm4chee.
SU‐F‐I‐74: Dose Evaluation Based On Monte Carlo Simulation of Three‐Dimensional Rotational Angiography During Hepatic Transarterial Chemoembolization Procedures
Authors: Hwang Y , Lui K , Lin Y , Tsai H
Published: July 2016

Purpose:

This study was aimed to investigate the dose with patient performing three‐dimensional (3D) angiography imaging during hepatic transarterial chemoembolization (TACE) procedures.

Methods:

Organ doses and effective doses calculations were retrospectively performed in 88 patients (61 males and 27 females with averaged age of 65.4±12.6 years old) referred for hepatic TACE on a digital flat‐panel angiography system (Bransist safire; Shimadzu) using software (PCXMC; Helsinki, Finland) based on Monte Carlo technique. Patient information (weight and height) and projection data were also used as parameters for dose calculations. Doses were evaluated of the 26 organs in 43 projections at 5° intervals from RAO 120° to LAO 95°. 3D rotational angiography images were acquired three times (before and after contrast, as well as after chemoembolization) using the same exposure techniques (100 kV, 360 mA and 5 ms pulse width) for each patient. Effective doses and dose conversion factors (CFs) were also calculated from the Monte Carlo data.

Results:

Upper abdominal organs, especially for the dorsal organs, showed the higher dose. Kidney received the highest dose (45.67 mGy) during the whole 3D procedure. Averaged DAP for 88 patients was 394.67±10.85 dGycm2. Averaged effective dose during the 3D procedure were 11.33 mSv. Significant inverse linear relationship was found between effective dose and patient weight (R2 =0.90). Averaged DAP‐to‐effective dose CF were 0.027 mSvdGy−1cm−2 in our study and tend to be decreased as patient weight increased (R2=0.92).

Conclusion:

Effective dose for the three acquisitions in the 3D rotational angiography of TACE is comparable to the effective dose for one series in the abdominal CT. By utilizing the conversion factors, the DAPs may be useful for estimating the effective dose during 3D abdominal angiographic imaging in the future.