bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐D‐207A‐02: Possible Characterization of the Brain Tumor Vascular Environment by a Novel Strategy of Quantitative Analysis in Dynamic Contrast Enhanced MR Imaging: A Combination of Both Patlak and Logan Analyses
Authors: Yee S , Chinnaiyan P , Wloch J , Pirkola M , Yan D
Published: July 2016

Purpose:

The majority of quantitative analyses involving dynamic contrast enhanced (DCE) MRI have been performed to obtain kinetic parameters such as Ktrans and ve. Such analyses are generally performed assuming a “reversible” tissue compartment, where the tracer is assumed to be rapidly equilibrated between the plasma and tissue compartments. However, some tumor vascular environments may be more suited for a “non‐reversible” tissue compartment, where, as with FDG PET imaging, the tracer is continuously deposited into the tissue compartment (or the return back to the plasma compartment is very slow in the imaging time scale). Therefore, Patlak and Logan analyses, which represent tools for the “non‐reversible” and “reversible” modeling, respectively, were performed to better characterize the brain tumor vascular environment.

Methods:

A voxel‐by‐voxel analysis was performed to generate both Patlak and Logan plots in two brain tumor patients, one with grade III astrocytoma and the other with grade IV astrocytoma or glioblastoma. The slopes of plots and the r‐square were then obtained by linear fitting and compared for each voxel.

Results:

The 2‐dimensional scatter plots of Logan (Y‐axis) vs. Patlak slopes (X‐axis) clearly showed increased Logan slopes for glioblastoma (Figure 3A). The scatter plots of goodness‐of‐fit (Figure 3B) also suggested glioblastoma, relative to grade III astrocytoma, might consist of more voxels that are kinetically Logan‐like (i.e. rapidly equilibrated extravascular space and active vascular environment). Therefore, the enhanced Logan‐like behavior (and the Logan slope) in glioblastoma may imply an increased fraction of active vascular environment, while the enhanced Patlak‐like behavior implies the vascular environment permitting a relatively slower washout of the tracer.

Conclusion:

Although further verification is required, the combination of Patlak and Logan analyses in DCE MRI may be useful in characterizing the tumor vascular environment, and thus, may have implications in tumor grading and monitoring response to anti‐vascular therapy.
SU‐D‐207A‐04: Use of Gradient Echo Plural Contrast Imaging (GEPCI) in MR‐Guided Radiation Therapy: A Feasibility Study Targeting Brain Treatment
Authors: Cai B , Wen J , Rao Y , Tsien C , Huang J , Green O , Mutic S , Yablonskiy D , Gach H
Published: July 2016

Purpose:

To implement the Gradient Echo Plural Contrast Imaging(GEPCI) technique in MRI‐simulation for radiation therapy and assess the feasibility of using GEPCI images with advanced inhomogeneity correction in MRI‐guided radiotherapy for brain treatment.

Methods:

An optimized multigradient‐echo GRE sequence (TR=50ms;TE1=4ms;delta_TE=4ms;flip angle=300,11 Echoes) was developed to generate both structural (T1w and T2*w) and functional MRIs (field and susceptibility maps) from a single acquisition. One healthy subject (Subject1) and one post‐surgical brain cancer patient (Subject2) were scanned on a Philips Ingenia 1.5T MRI used for radiation therapy simulation. Another healthy subject (Subject3) was scanned on a 0.35T MRI‐guided radiotherapy (MR‐IGRT) system (ViewRay). A voxel spread function (VSF) was used to correct the B0 inhomogeneities caused by surgical cavities and edema for Subject2. GEPCI images and standard radiotherapy planning MRIs for this patient were compared focusing the delineation of radiotherapy target region.

Results:

GEPCI brain images were successfully derived from all three subjects with scan times of <7 minutes. The images derived for Subjects1&2 demonstrated that GEPCI can be applied and combined into radiotherapy MRI simulation. Despite low field, T1‐weighted and R2* images were successfully reconstructed for Subject3 and were satisfactory for contour and target delineation. The R2* distribution of grey matter (center=12,FWHM=4.5) and white matter (center=14.6, FWHM=2) demonstrated the feasibility for tissue segmentation and quantification. The voxel spread function(VSF) corrected surgical site related inhomogeneities for Subject2. R2* and quantitative susceptibility map(QSM) images for Subject2 can be used to quantitatively assess the brain structure response to radiation over the treatment course.

Conclusion:

We implemented the GEPCI technique in MRI‐simulation and in MR‐IGRT system for radiation therapy. The images demonstrated that it is feasible to adopt this technique in radiotherapy for structural delineation. The preliminary data also enable the opportunity for quantitative assessment of radiation response of the target region and normal tissue.
SU‐D‐207A‐07: The Effects of Inter‐Cycle Respiratory Motion Variation On Dose Accumulation in Single Fraction MR‐Guided SBRT Treatment of Renal Cell Carcinoma
Authors: Stemkens B , Glitzner M , Kontaxis C , Denis de Senneville B , Prins F , Crijns SPM , Kerkmeijer L , Lagendijk J , van den Berg CAT , Tijssen RHN
Published: July 2016

Purpose:

To assess the dose deposition in simulated single‐fraction MR‐Linac treatments of renal cell carcinoma, when inter‐cycle respiratory motion variation is taken into account using online MRI.

Methods:

Three motion characterization methods, with increasing complexity, were compared to evaluate the effect of inter‐cycle motion variation and drifts on the accumulated dose for an SBRT kidney MR‐Linac treatment: 1) STATIC, in which static anatomy was assumed, 2) AVG‐RESP, in which 4D‐MRI phase‐volumes were time‐weighted, based on the respiratory phase and 3) PCA, in which 3D volumes were generated using a PCA‐model, enabling the detection of inter‐cycle variations and drifts. An experimental ITV‐based kidney treatment was simulated in a 1.5T magnetic field on three volunteer datasets. For each volunteer a retrospectively sorted 4D‐MRI (ten respiratory phases) and fast 2D cine‐MR images (temporal resolution = 476ms) were acquired to simulate MR‐imaging during radiation. For each method, the high spatio‐temporal resolution 3D volumes were non‐rigidly registered to obtain deformation vector fields (DVFs). Using the DVFs, pseudo‐CTs (generated from the 4D‐MRI) were deformed and the dose was accumulated for the entire treatment. The accuracies of all methods were independently determined using an additional, orthogonal 2D‐MRI slice.

Results:

Motion was most accurately estimated using the PCA method, which correctly estimated drifts and inter‐cycle variations (RMSE=3.2, 2.2, 1.1mm on average for STATIC, AVG‐RESP and PCA, compared to the 2DMRI slice). Dose‐volume parameters on the ITV showed moderate changes (D99=35.2, 32.5, 33.8Gy for STATIC, AVG‐RESP and PCA). AVG‐RESP showed distinct hot/cold spots outside the ITV margin, which were more distributed for the PCA scenario, since inter‐cycle variations were not modeled by the AVG‐RESP method.

Conclusion:

Dose differences were observed when inter‐cycle variations were taken into account. The increased inter‐cycle randomness in motion as captured by the PCA model mitigates the local (erroneous) hotspots estimated by the AVG‐RESP method.
SU‐D‐209‐04: Raise Your Table: An Effective Way to Reduce Radiation Dose for Fluoroscopy
Authors: Huo D , Hoerner M , Toskich B , Rill L
Published: July 2016

Purpose:

Patient table height plays an important role in estimating patient skin dose for interventional radiology (IR) procedures, because the patient's skin location is dependent on the height of table. Variation in table height can lead to as much as 150% difference in skin dose for patient exams with similar air kerma meter readings. In our facility, IR procedural workflow was recently changed to require the IR physicians to confirm the patient table height before the procedure. The patient table height data was collected before and after this workflow change to validate the implementation of this practice.

Methods:

Table height information was analyzed for all procedures performed in three IR rooms, which were impacted by the workflow change, covering three months before and after the change (Aug 2015 to Jan 2016). In total, 442, 425, and 390 procedures were performed in these three rooms over this time period. There were no personnel or procedure assignment changes during the six‐month period of time. Statistical analysis was performed for the average table height changes before and after the workflow change.

Results:

For the three IR rooms investigated, after the workflow change, the average table heights were increased by 1.43 cm (p=0.004084), 0.66 cm (p=0.187089), and 1.59 cm (p=0.002193), providing a corresponding estimated skin dose savings of 6.76%, 2.94% and 7.62%, respectively. After the workflow change, the average table height was increased by 0.95 cm, 0.63 cm, 0.55 cm, 1.07 cm, 1.12 cm, and 3.36 cm for the six physicians who routinely work in these three rooms.

Conclusion:

Consistent improvement in table height settings has been observed for all IR rooms and all physicians following a simple workflow change. This change has led to significant patient dose savings by making physicians aware of the pre‐procedure table position.
SU‐D‐209‐05: Sensitivity of the Diagnostic Radiological Index of Protection (DRIP) to Procedural Factors in Fluoroscopy
Authors: Jones A , Pasciak A , Wagner L
Published: July 2016

Purpose:

To evaluate the sensitivity of the Diagnostic Radiological Index of Protection (DRIP) to procedural factors in fluoroscopy in an effort to determine an appropriate set of scatter‐mimicking primary beams (SMPB) to be used in measuring the DRIP.

Methods:

A series of clinical and factorial Monte Carlo simulations were conducted to determine the shape of the scattered X‐ray spectra incident on the operator in different clinical fluoroscopy scenarios. Two clinical evaluations studied the sensitivity of the scattered spectrum to gantry angle and patient size while technical factors were varied according to measured automatic dose rate control (ADRC) data. Factorial evaluations studied the sensitivity of the scattered spectrum to gantry angle, field of view, patient size and beam quality for constant technical factors. Average energy was the figure of merit used to condense fluence in each energy bin to a single numerical index.

Results:

Beam quality had the strongest influence on the scattered spectrum in fluoroscopy. Many procedural factors affected the scattered spectrum indirectly through their effects on primary beam quality through ADRC, e.g., gantry angle and patient size. Lateral C‐arm rotation, common in interventional cardiology, increased the energy of the scattered spectrum, regardless of the direction of rotation. The effect of patient size on scattered radiation depended on ADRC characteristics, patient size, and procedure type.

Conclusion:

The scattered spectrum striking the operator in fluoroscopy, and therefore the DRIP, is most strongly influenced by primary beam quality, particularly kV. Use cases for protective garments should be classified by typical procedural primary beam qualities, which are governed by the ADRC according to the impacts of patient size, anatomical location, and gantry angle. These results will help determine an appropriate set of SMPB to be used for measuring the DRIP.
SU‐D‐209‐06: Study On the Dose Conversion Coefficients in Pediatric Radiography with the Development of Children Voxel Phantoms
Authors: Liu Q , Zhuo W , Liu H , Liu Y , Chen T
Published: July 2016

Purpose:

Conversion coefficients of organ dose normalized to entrance skin dose (ESD) are widely used to evaluate the organ doses directly using ESD without time‐consuming dose measurement, this work aims to investigate the dose conversion coefficients in pediatric chest and abdomen radiography with the development of 5 years and 10 years old children voxel phantoms.

Methods:

After segmentation of organs and tissues from CT slice images of ATOM tissue‐equivalent phantoms, a 5‐year‐old and a 10‐year‐old children computational voxel phantoms were developed for Monte Carlo simulation. The organ doses and the entrance skin dose for pediatric chest postero‐anterior projection and abdominal antero‐posterior projection were simulated at the same time, and then the organ dose conversion coefficients were calculated.To verify the simulated results, dose measurement was carried out with ATOM tissue‐equivalent phantoms for 5 year chest radiography.

Results:

Simulated results and experimental results matched very well with each other, the result differences of all the organs covered in radiation field were below 16% for 5‐year‐old child in chest projection. I showed that the conversion coefficients of organs covered in the radiation field were much larger than organs out of the field for all the study cases, for example, the conversion coefficients of stomach, liver intestines, and pancreas are larger for abdomen radiography while conversion coefficients of lungs are larger for chest radiography.

Conclusion:

The voxel children phantoms were helpful to evaluate the radiation doses more accurately and efficiently. Radiation field was the essential factor that affects the organ dose, use reasonably small field should be encouraged for radiation protection.

This work was supported by the National Natural Science Foundation of China(11475047)
SU‐D‐209‐07: Measure the Average Glandular Dose of a 2D+3D Breast Imaging Protocol Using GE SenoClaire Breast Tomosynthesis System
Authors: Liang Y , Dutta A
Published: July 2016

Purpose:

To measure the average glandular dose (AGD) of a 2D+3D breast imaging protocol using GE SenoClaire breast tomosynthesis system.

Methods:

This study used a GE SenoClaire breast tomosynthesis unit, a Gammex ACR mammography accreditation phantom, 5 cm thick PMMA phantom, an Unfors RaySafe X2 mammography detector. The breast imaging protocol includes a regular 2D CC view and a 3D MLO view at 45 degree, using AUTO mode. Both ACR phantom and PMMA phantom were scanned under AUTO mode with 10 daN compression to obtain the techniques of 2D CC view, 3D MLO view, and 3D CC view. The techniques of ACR phantom were used for the following manual scan with only RaySafe X2 detector being positioned under the same compression paddle at the same height as the ACR phantom. The detector is at 3 cm from the chest wall edge and laterally centered in the X‐ray field. Measurements were repeated with detector at 6 cm and 9 cm from the chest wall edge. The above procedure were repeated using the manual techniques of PMMA phantom. The measured entrance skin air Kerma was then converted to the AGD using two

Methods:

one was listed in GE QC manual; the other was based on AAPM Report 223.

Results:

The AGD from 2D+3D imaging for both breasts using AUTO mode is approximately 4.25 mGy for ACR phantom and approximately 6 mGy for 5 cm thick PMMA phantom. The difference between 3D MLO view and 3D CC view is less than 2%. The difference between two methods is also less than 3%.

Conclusion:

The AGD of a 2D +3D breast imaging using GE SenoClaire is comparable to two regular 2D images if both are scanned using AUTO mode.
SU‐D‐207B‐01: Radiomics Feature Reproducibility From Repeat CT Scans of Patients with Rectal Cancer
Authors: Hu P , Wang J , Zhong H , Zhou Z , Shen L , Hu W , Zhang Z
Published: July 2016

Purpose:

To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer.

Methods:

40 rectal cancer patients were enrolled in this study, each of whom underwent two CT scans within average 8.7 days (5 days to 17 days), before any treatment was delivered. The rectal gross tumor volume (GTV) was distinguished and segmented by an experienced oncologist in both CTs. Totally, more than 2000 radiomics features were defined in this study, which were divided into four groups (I: GLCM, II: GLRLM III: Wavelet GLCM and IV: Wavelet GLRLM). For each group, five types of features were extracted (Max slice: features from the largest slice of target images, Max value: features from all slices of target images and choose the maximum value, Min value: minimum value of features for all slices, Average value: average value of features for all slices, Matrix sum: all slices of target images translate into GLCM and GLRLM matrices and superpose all matrices, then extract features from the superposed matrix). Meanwhile a LOG (Laplace of Gauss) filter with different parameters was applied to these images. Concordance correlation coefficients (CCC) and inter‐class correlation coefficients (ICC) were calculated to assess the reproducibility.

Results:

403 radiomics features were extracted from each type of patients’ medical images. Features of average type are the most reproducible. Different filters have little effect for radiomics features. For the average type features, 253 out of 403 features (62.8%) showed high reproducibility (ICC≥0.8), 133 out of 403 features (33.0%) showed medium reproducibility (0.8≥ICC≥0.5) and 17 out of 403 features (4.2%) showed low reproducibility (ICC≥0.5).

Conclusion:

The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and prognosis prediction.
SU‐D‐207B‐04: Morphological Features of MRI as a Correlate of Capsular Contracture in Breast Cancer Patients with Implant‐Based Reconstructions
Authors: Tyagi N , Sutton E , Hunt M , Apte A , Zhang J , Oh J , Mechalakos J , Mehrara B , Matros E , Ho A
Published: July 2016

Purpose:

Capsular contracture (CC) is a serious complication in patients receiving implant‐based reconstruction for breast cancer. The goal of this study was to identify image‐based correlates of CC using MRI imaging in breast cancer patients who received both MRI and clinical evaluation following reconstructive surgery.

Methods:

We analyzed a retrospective dataset of 50 patients who had both a diagnostic MR and a plastic surgeon's evaluations of CC score (Baker's score) within a six month period following mastectomy and reconstructive surgery. T2w sagittal MRIs (TR/TE = 3500/102 ms, slice thickness = 4 mm) were used for morphological shape features (roundness, eccentricity, solidity, extent and ratio‐length) and histogram features (median, skewness and kurtosis) of the implant and the pectoralis muscle overlying the implant. Implant and pectoralis muscles were segmented in 3D using Computation Environment for Radiological Research (CERR) and shape and histogram features were calculated as a function of Baker's score.

Results:

Shape features such as roundness and eccentricity were statistically significant in differentiating grade 1 and grade 2 (p = 0.009; p = 0.06) as well as grade 1 and grade 3 CC (p = 0.001; p = 0.006). Solidity and extent were statistically significant in differentiating grade 1 and grade 3 CC (p = 0.04; p = 0.04). Ratio‐length was statistically significant in differentiating all grades of CC except grade 2 and grade 3 that showed borderline significance (p = 0.06). The muscle thickness, median intensity and kurtosis were significant in differentiating between grade 1 and grade 3 (p = 0.02), grade 1 and grade 2 (p = 0.03) and grade 1 and grade 3 (p = 0.01) respectively.

Conclusion:

Morphological shape features described on MR images were associated with the severity of CC. MRI may be important in objectively evaluating outcomes in breast cancer patients who undergo implant reconstruction.
SU‐D‐207B‐06: Predicting Breast Cancer Malignancy On DCE‐MRI Data Using Pre‐Trained Convolutional Neural Networks
Authors: Antropova N , Huynh B , Giger M
Published: July 2016

Purpose:

We investigate deep learning in the task of distinguishing between malignant and benign breast lesions on dynamic contrast‐enhanced MR images (DCE‐MRIs), eliminating the need for lesion segmentation and extraction of tumor features. We evaluate convolutional neural network (CNN) after transfer learning with ImageNet, a database of thousands of non‐medical images.

Methods:

Under a HIPAA‐compliant IRB protocol, a database of 551 (357 malignant and 194 benign) breast MRI cases was collected. ROIs around each lesion were extracted from the DCE‐MRI slices at the second post‐contrast time point. Depending on the size of the tumor, the dimensions of ROIs varied between 1 and 1.5 times the maximum diameter of the lesion, which were further upsampled or downsampled to yield 256×256‐pixel ROIs. Next, these ROIs were directly input to the convolutional neural network ConvNet, which had been pre‐trained by AlexNet on the ImageNet database. The internal layer of ConvNet output 4,096 features, which were subsequently used as the input to a support vector machine (SVM) to classify the lesions as malignant or benign. Area under the receiver operating characteristic curve (AUC) was used as a figure of merit for the classification task. We performed 10‐fold cross‐validation with training and testing sets consisting of 90% and 10% of the database, respectively.

Results:

The CNN with transfer learning and subsequent SVM yielded an an AUC value of 0.85, demonstrating the predictive value of the CNN. In future work, we will compare the results obtained with ConvNet with the results obtained using conventional tumor radiomics features. Our approach returns the prediction within minutes, due to incorporation of transfer learning.

Conclusion:

A CNN pre‐trained on non‐medical images can be used to extract image characteristics from breast DCE‐MR images relevant to diagnostic decision‐making. Our work shows that transfer learning can aid in prediction of breast cancer malignancy.

M. Giger is a stockholder in R2/Hologic, co‐founder and equity holder in Quantitative Insights, and receives royalties from Hologic, GE Medical Systems, MEDIAN Technologies, Riverain Medical, Mitsubishi, and Toshiba
SU‐D‐207B‐07: Development of a CT‐Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer
Authors: Klawikowski S , Christian J , Schott D , Zhang M , Li X
Published: July 2016

Purpose:

Pilot study developing a CT‐texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer.

Methods:

Daily CT data acquired for 24 pancreatic head cancer patients using CT‐on‐rails, during the routine CT‐guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co‐occurrence, run‐length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each daily CT. Metric‐trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best‐fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend‐response metrics.

Results:

We found four specific trend‐metrics (Gray Level Coocurence Matrix311‐1InverseDiffMomentNorm, Gray Level Coocurence Matrix311‐1InverseDiffNorm, Gray Level Coocurence Matrix311‐1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend‐metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p=0.9741), and kernel (p=0.8586).

Conclusion:

We have successfully created a CT‐texture based early treatment response prediction model using the CTs acquired during the delivery of chemoradiation therapy for pancreatic cancer. Future testing is required to validate the model with more patient data.
SU‐F‐SPS‐03: Direct Measurement of Organ Doses Resulting From Head and Cervical Spine Trauma CT Protocols
Authors: Carranza C , Lipnharski I , Quails N , Correa N , Rill L , Arreola M
Published: July 2016

Purpose:

This retrospective study analyzes the exposure history of emergency department (ED) patients undergoing head and cervical spine trauma computed tomography (CT) studies. This study investigated dose levels received by trauma patients and addressed any potential concerns regarding radiation dose issues.

Methods:

Under proper IRB approval, a cohort of 300 trauma cases of head and cervical spine trauma CT scans received in the ED was studied. The radiological image viewing software of the hospital was used to view patient images and image data. The following parameters were extracted: the imaging history of patients, the reported dose metrics from the scanner including the volumetric CT Dose Index (CTDIvol) and Dose Length Product (DLP). A postmortem subject was scanned using the same scan techniques utilized in a standard clinical head and cervical spine trauma CT protocol with 120 kVp and 280 mAs. The CTDIvol was recorded for the subject and the organ doses were measured using optically stimulated luminescent (OSL) dosimeters. Typical organ doses to the brain, thyroid, lens, salivary glands, and skin, based on the cadaver studies, were then calculated and reported for the cohort.

Results:

The CTDIvol reported by the CT scanner was 25.5 mGy for the postmortem subject. The average CTDIvol from the patient cohort was 34.1 mGy. From these metrics, typical average organ doses in mGy were found to be: Brain (44.57), Thyroid (33.40), Lens (82.45), Salivary Glands (61.29), Skin (47.50). The imaging history of the cohort showed that on average trauma patients received 26.1 scans over a lifetime.

Conclusion:

The average number of scans received on average by trauma ED patients shows that radiation doses in trauma patients may be a concern. Available dose tracking software would be helpful to track doses in trauma ED patients, highlighting the importance of minimizing unnecessary scans and keeping doses ALARA.
SU‐F‐E‐02: A Feasibility Study for Application of Metal Artifact Reduction Techniques in MR‐Guided Brachytherapy Gynecological Cancer with Titanium Applicators
Authors: Kadbi M
Published: July 2016

Purpose:

Utilization of Titanium Tandem and Ring (T&R) applicators in MR‐guided brachytherapy has become widespread for gynecological cancer treatment. However, Titanium causes magnetic field disturbance and susceptibility artifact, which complicate image interpretation. In this study, metal artifact reduction techniques were employed to improve the image quality and reduce the metal related artifacts.

Methods:

Several techniques were employed to reduce the metal artifact caused by titanium T&R applicator. These techniques include Metal Artifact Reduction Sequence (MARS), View Angle Tilting (VAT) to correct in‐plane distortion, and Slice Encoding for Metal Artifact Correction (SEMAC) for through‐plane artifact correction. Moreover, MARS can be combined with VAT to further reduce the in‐plane artifact by reapplying the selection gradients during the readout (MARS+VAT). SEMAC uses a slice selective excitation but acquires additional z‐encodings in order to resolve off‐resonant signal and to reduce through‐plane distortions.

Results:

Comparison between the clinical sequences revealed that increasing the bandwidth reduces the error in measured diameter of T&R. However, the error is larger than 4mm for the best case with highest bandwidth and spatial resolution. MARS+VAT with isotropic resolution of 1mm reduced the error to 1.9mm which is the least among the examined 2D sequences. The measured diameter of tandem from SEMAC+VAT has the closest value to the actual diameter of tandem (3.2mm) and the error was reduced to less than 1mm. In addition, SEMAC+VAT significantly reduces the blooming artifact in the ring compared to clinical sequences.

Conclusion:

A higher bandwidth and spatial resolution sequence reduces the artifact and diameter of applicator with a slight compromise in SNR. Metal artifact reduction sequences decrease the distortion associated with titanium applicator. SEMAC+VAT sequence in combination with VAT revealed promising results for titanium imaging and can be utilized for MR‐guided brachytherapy in gynecological cancer.

The author is employee with Philips Healthcare
SU‐F‐E‐09: Respiratory Signal Prediction Based On Multi‐Layer Perceptron Neural Network Using Adjustable Training Samples
Authors: Sun W , Jiang M , Yin F
Published: July 2016

Purpose:

Dynamic tracking of moving organs, such as lung and liver tumors, under radiation therapy requires prediction of organ motions prior to delivery. The shift of moving organ may change a lot due to huge transform of respiration at different periods. This study aims to reduce the influence of that changes using adjustable training signals and multi‐layer perceptron neural network (ASMLP).

Methods:

Respiratory signals obtained using a Real‐time Position Management(RPM) device were used for this study. The ASMLP uses two multi‐layer perceptron neural networks(MLPs) to infer respiration position alternately and the training sample will be updated with time. Firstly, a Savitzky‐Golay finite impulse response smoothing filter was established to smooth the respiratory signal. Secondly, two same MLPs were developed to estimate respiratory position from its previous positions separately. Weights and thresholds were updated to minimize network errors according to Leverberg‐Marquart optimization algorithm through backward propagation method. Finally, MLP 1 was used to predict 120∼150s respiration position using 0∼120s training signals. At the same time, MLP 2 was trained using 30∼150s training signals. Then MLP is used to predict 150∼180s training signals according to 30∼150s training signals. The respiration position is predicted as this way until it was finished.

Results:

In this experiment, the two methods were used to predict 2.5 minute respiratory signals. For predicting 1s ahead of response time, correlation coefficient was improved from 0.8250(MLP method) to 0.8856(ASMLP method). Besides, a 30% improvement of mean absolute error between MLP(0.1798 on average) and ASMLP(0.1267 on average) was achieved. For predicting 2s ahead of response time, correlation coefficient was improved from 0.61415 to 0.7098.Mean absolute error of MLP method(0.3111 on average) was reduced by 35% using ASMLP method(0.2020 on average).

Conclusion:

The preliminary results demonstrate that the ASMLP respiratory prediction method is more accurate than MLP method and can improve the respiration forecast accuracy.
SU‐F‐E‐10: Student‐Driven Exploration of Radiographic Material Properties, Phantom Construction, and Clinical Workflows Or: The Extraordinary Life of CANDY MAN
Authors: Mahon RN , Riblett MJ , Hugo GD
Published: July 2016

Purpose:

To develop a hands‐on learning experience that explores the radiological and structural properties of everyday items and applies this knowledge to design a simple phantom for radiotherapy exercises.

Methods:

Students were asked to compile a list of readily available materials thought to have radiation attenuation properties similar to tissues within the human torso. Participants scanned samples of suggested materials and regions of interest (ROIs) were used to characterize bulk attenuation properties. Properties of each material were assessed via comparison to a Gammex Tissue characterization phantom and used to construct a list of inexpensive near‐tissue‐equivalent materials. Critical discussions focusing on samples found to differ from student expectations were used to revise and narrow the comprehensive list. From their newly acquired knowledge, students designed and constructed a simple thoracic phantom for use in a simulated clinical workflow. Students were tasked with setting up the phantom and acquiring planning CT images for use in treatment planning and dose delivery.

Results:

Under engineer and physicist supervision, students were trained to use a CT simulator and acquired images for approximately 60 different foodstuffs, candies, and household items. Through peer discussion, students gained valuable insights and were made to review preconceptions about radiographic material properties. From a subset of imaged materials, a simple phantom was successfully designed and constructed to represent a human thorax. Students received hands‐on experience with clinical treatment workflows by learning how to perform CT simulation, create a treatment plan for an embedded tumor, align the phantom for treatment, and deliver a treatment fraction.

Conclusion:

In this activity, students demonstrated their ability to reason through the radiographic material selection process, construct a simple phantom to specifications, and exercise their knowledge of clinical workflows. Furthermore, the enjoyable and inexpensive nature of this project proved to attract participant interest and drive creative exploration.

Mahon and Riblett have nothing to disclose; Hugo has a research agreement with Phillips Medical systems, a license agreement with Varian Medical Systems, research grants from the National Institute of Health. Authors do not have any potential conflicts of interest to disclose.
SU‐F‐E‐17: A Dedicated Teaching and Research Linac as a Stepping Stone to Introduce Medical Physics to Students
Authors: Beaulieu L , Gingras L , Bergeron M , Archambault L
Published: July 2016

Purpose:

This work describes how a non‐clinical, research and teaching Linac is used as an extremely motivating and exciting way to introduce students to medical physics.

Methods:

The dedicated facility was inaugurated in 2014. The facility is composed of a fully equipped and functional state‐of‐the‐art Varian TrueBeam Linac and a complete set of physics instruments and QA phantoms for the Linac and onboard imaging. The Linac bunker and treatment console are oversized such that a class of 12–15 can comfortably fit, seated if needed for longer sessions. A 3cr undergraduate laboratory course that includes medical imaging, x‐ray source characterization (mAs, kVp, and filtering) and many others including an introductory Linac laboratory was created. The latter is composed of one general 4‐hours session and a weekly 4‐hours session for teams of two students. The general session includes a hands‐on presentation of the Linac, its environment and a formal safety and radiation protection course (with an exam).

Results:

Since the winter of 2015, senior undergraduate (total of 15) pursuing either the medical physics or the biomedical engineering tracks can register. At the Linac, the students are allowed full control of the experiments, including set‐up and irradiation. Supervisor intervention is limited to safety concerns for students or equipment. Measurements of output factors using two chambers (regular and small field) for various field sizes (1×1 to 30×30 cm2) and of detailed depth‐dose curves for 6 MV, 6 and 12 MeV beams are to be performed and discussed in a formal report.

Conclusion:

Full access to, and control of, a Linac is the high point of this course. It provides a glimpse of medical physics and generates an experimental background for those continuing to CAMPEP programs. This dedicated, non‐clinical facility further enable enhance CAMPEP graduate teaching and research activities not possible with a clinical device.
SU‐F‐E‐21: Change in Retinal Arteriole Diameter with Visual Simulation
Authors: Tellapragada N , Burns S
Published: July 2016

Purpose:

Neural activity and blood flow in the brain are tightly coupled. This coupling allows the brain to respond to periods of increased neural activity with increased blood flow. This coupling is known as neurovascular coupling. Many vascular based imaging techniques such as Functional MRI scans provide maps of signals of brain activity but they are limited by the resolution of fMRI to a few mm. The fMRI signal is indirect because the scanner is not tracking the neural activity directly but are measuring the changes in the blood oxygen levels. Since the retina and optic tract are part of the central nerves system and they can be measured optically it should be possible to make precise measurements of the retinal vasculature of the human retina and its response to changing stimulation levels.

Methods:

In this study we used an adaptive optics scanning laser ophthalmoscope (AOSLO) with multiply scattered light to measure the change in arteriolar diameter when the retina was stimulated with flickering light. We hypothesized that we could use this technique to measure both arterial dilation and time course. We used information from the reflectance of the vessel to measure total vessel diameter.

Results:

Images were acquired at approximately 30 Hz and averaged over 3.3 second periods. Retinal arteries were measured in five observers before, during, and after presentation of a large flickering stimulus. There was a 6–10% dilation of the blood vessels during the flicker. The Vascular dilation occurred within seconds of flickering onset and constricted again following the end of flicker stimulation.

Conclusion:

This work shows that with modern retinal imaging methods it is possible to make precise measures of vascular constriction and its time course in response to changing tissue demand.
SU‐F‐P‐06: Moving From Computed Radiography to Digital Radiography: A Collaborative Approach to Improve Image Quality
Authors: Sandoval D , Valenti D , Bateman T , Norris V , Mlady G , Selwyn R
Published: July 2016

Purpose:

To bring together radiologists, technologists, and physicists to utilize post‐processing techniques in digital radiography (DR) in order to optimize image acquisition and improve image quality.

Methods:

Sub‐optimal images acquired on a new General Electric (GE) DR system were flagged for follow‐up by radiologists and reviewed by technologists and medical physicists. Various exam types from adult musculoskeletal (n=35), adult chest (n=4), and pediatric (n=7) were chosen for review. 673 total images were reviewed. These images were processed using five customized algorithms provided by GE. An image score sheet was created allowing the radiologist to assign a numeric score to each of the processed images, this allowed for objective comparison to the original images. Each image was scored based on seven properties: 1) overall image look, 2) soft tissue contrast, 3) high contrast, 4) latitude, 5) tissue equalization, 6) edge enhancement, 7) visualization of structures. Additional space allowed for additional comments not captured in scoring categories. Radiologists scored the images from 1 – 10 with 1 being non‐diagnostic quality and 10 being superior diagnostic quality. Scores for each custom algorithm for each image set were summed. The algorithm with the highest score for each image set was then set as the default processing.

Results:

Images placed into the PACS “QC folder” for image processing reasons decreased. Feedback from radiologists was, overall, that image quality for these studies had improved. All default processing for these image types was changed to the new algorithm.

Conclusion:

This work is an example of the collaboration between radiologists, technologists, and physicists at the University of New Mexico to add value to the radiology department. The significant amount of work required to prepare the processing algorithms, reprocessing and scoring of the images was eagerly taken on by all team members in order to produce better quality images and improve patient care.
SU‐F‐P‐26: Study of Radiation Dose Evaluation for Organs at Risk Using MRI in Intensity Modulated Radiation Therapy for Nasopharyngeal Carcinoma
Authors: Gong G , Guo Y , Yin Y
Published: July 2016

Purpose:

To study the contour and dosimetric feature of organs at risk (OARs) applying magnetic resonance imaging (MRI) images in intensity modulated radiation therapy (IMRT) of nasopharyngeal carcinoma (NPC) compared to computed tomography (CT) images.

Methods:

35 NPC patients was selected into this trail. CT simulation with non‐contrast and contrast enhanced scan, MRI simulation with non‐contrast and contrast enhanced T1, T2 and diffusion weighted imaging were achieved sequentially. And the OARs were contoured on the CT and MRI images after rigid registration respectively. 9 beams IMRT plan with equal division angle were designed for every patients, and the prescription dose for tumor target was set as 72Gy (2.4Gy/ fration). The boundary display, volume and dose‐volume indices of each organ were compared between on MRI and CT images.

Results:

Compared to CT, MRI showed clearer boundary of brainstem, spinal cord, the deep lobe of Parotid gland and the optical nerve in canal. MRI images increase the volume of lens, optical nerve, while reducing the volume of eye slightly, and the maximum dose of lens, the mean dose of eyes and optical raised in different percentage, while there was no statistical differences were found. The left and right parotid volume on MRI increased by 7.07%, 8.13%, and the mean dose raised by 14.95% (4.01Gy), 18.76% (4.95Gy) with statistical significant difference (p<0.05). The brainstem volume reduced by 9.33% (p<0.05), and the dose of 0.1cm3 volume (D0.1cm3) reduced by mean 8.46% (4.32Gy), and D0.1cm3 of spinal cord increased by 1.5Gy on MRI.

Conclusion:

It is credible to evaluate the radiation dose of lens, eye and the spinal cord, while it should be necessary to evaluate the dose of brainstem, parotid and the optical nerve applying MRI images sometime, it will be more meaningful for these organs with high risk of radiation injury.
SU‐F‐P‐36: Automation of Linear Accelerator Star Shot Measurement with Advanced XML Scripting and Electronic Portal Imaging Device
Authors: Nguyen N , Knutson N , Schmidt M , Price M
Published: July 2016

Purpose:

To verify a method used to automatically acquire jaw, MLC, collimator and couch star shots for a Varian TrueBeam linear accelerator utilizing Developer Mode and an Electronic Portal Imaging Device (EPID).

Methods:

An XML script was written to automate motion of the jaws, MLC, collimator and couch in TrueBeam Developer Mode (TBDM) to acquire star shot measurements. The XML script also dictates MV imaging parameters to facilitate automatic acquisition and recording of integrated EPID images. Since couch star shot measurements cannot be acquired using a combination of EPID and jaw/MLC collimation alone due to a fixed imager geometry, a method utilizing a 5mm wide steel ruler placed on the table and centered within a 15×15cm2 open field to produce a surrogate of the narrow field aperture was investigated. Four individual star shot measurements (X jaw, Y jaw, MLC and couch) were obtained using our proposed as well as traditional film‐based method. Integrated EPID images and scanned measurement films were analyzed and compared.

Results:

Star shot (X jaw, Y jaw, MLC and couch) measurements were obtained in a single 5 minute delivery using the TBDM XML script method compared to 60 minutes for equivalent traditional film measurements. Analysis of the images and films demonstrated comparable isocentricity results, agreeing within 0.3mm of each other.

Conclusion:

The presented automatic approach of acquiring star shot measurements using TBDM and EPID has proven to be more efficient than the traditional film approach with equivalent results.
SU‐F‐R‐51: Radiomics in CT Perfusion Maps of Head and Neck Cancer
Authors: Nesteruk M , Riesterer O , Bundschuh R , Veit‐Haibach P , Huellner M , Studer G , Stieb S , Glatz S , Pruschy M , Guckenberger M , Tanadini‐Lang S
Published: July 2016

Purpose:

The aim of this study was to test the predictive value of radiomics features of CT perfusion (CTP) for tumor control, based on a preselection of radiomics features in a robustness study.

Methods:

11 patients with head and neck cancer (HNC) and 11 patients with lung cancer were included in the robustness study to preselect stable radiomics parameters. Data from 36 HNC patients treated with definitive radiochemotherapy (median follow‐up 30 months) was used to build a predictive model based on these parameters. All patients underwent pre‐treatment CTP. 315 texture parameters were computed for three perfusion maps: blood volume, blood flow and mean transit time. The variability of texture parameters was tested with respect to non‐standardizable perfusion computation factors (noise level and artery contouring) using intraclass correlation coefficients (ICC). The parameter with the highest ICC in the correlated group of parameters (inter‐parameter Spearman correlations) was tested for its predictive value. The final model to predict tumor control was built using multivariate Cox regression analysis with backward selection of the variables. For comparison, a predictive model based on tumor volume was created.

Results:

Ten parameters were found to be stable in both HNC and lung cancer regarding potentially non‐standardizable factors after the correction for inter‐parameter correlations. In the multivariate backward selection of the variables, blood flow entropy showed a highly significant impact on tumor control (p=0.03) with concordance index (CI) of 0.76. Blood flow entropy was significantly lower in the patient group with controlled tumors at 18 months (p<0.1). The new model showed a higher concordance index compared to the tumor volume model (CI=0.68).

Conclusion:

The preselection of variables in the robustness study allowed building a predictive radiomics‐based model of tumor control in HNC despite a small patient cohort. This model was found to be superior to the volume‐based model.

The project was supported by the KFSP Tumor Oxygenation of the University of Zurich, by a grant of the Center for Clinical Research, University and University Hospital Zurich and by a research grant from Merck (Schweiz) AG.
SU‐F‐R‐56: Early Assessment of Treatment Response During Radiation Therapy Delivery for Esophageal Cancer Using Quantitative CT
Authors: Li D , Chen X , Wu H , Wang J , Li X
Published: July 2016

Purpose:

To investigate the feasibility of assessing treatment response using CTs during delivery of radiation therapy (RT) for esophageal cancer.

Methods:

Daily CTs acquired using a CT‐on‐Rails during the routine CT‐guided RT for 20 patients with stage II to IV esophageal cancers were analyzed. All patients were treated with combined chemotherapy and IMRT of 45–50 Gy in 25 fractions, and were followed up for two years. Contours of GTV, spinal cord, and non‐specified tissue (NST) irradiated with low dose were generated on each daily CT. A series of CT‐texture metrics including Hounsfield Unit (HU) histogram, mean HU, standard derivation (STD), entropy, and energy were obtained in these contours on each daily CT. The changes of these metrics and GTV volume during RT delivery were calculated and correlated with treatment outcome.

Results:

Changes in CT texture (e.g., HU histogram) in GTV and spinal cord (but not in NST) were observed during RT delivery and were consistently increased with radiation dose. For the 20 cases studied, the mean HU in GTV was reduced on average by 4.0HU from the first to the last fractions, while 8 patients (responders) had larger reductions in GTV mean HU (average 7.8 HU) with an average GTV reduction of 51% and had increased consistently in GTV STD and entropy with radiation dose. The rest of 12 patients (non‐responders) had lower reductions in GTV mean HU (average 1.5HU) and almost no change in STD and entropy. For the 8 responders, 2 experienced complete response, 7 (88%) survived and 1 died. In contrast, for the 12 non‐responders, 4 (33%) survived and 8 died.

Conclusion:

Radiation can induce changes in CT texture in tumor (e.g., mean HU) during the delivery of RT for esophageal cancer. If validated with more data, such changes may be used for early prediction of RT response for esophageal cancer.