Faculty Bibliography

Purpose: There is limited data regarding how many cycles of chemotherapy are optimal prior to debulking surgery in metastatic ovarian cancer. Furthermore, early identification of non-responders would prompt discontinuation of chemotherapy and earlier surgical management. The purpose of our study was to investigate the performance of FDG PET, dynamic contrast-enhanced (DCE) and intra-voxel incoherent motion (IVIM) MR as early predictors of treatment response in ovarian cancer. Parametric images of molecular diffusion restriction (D), tissue perfusion (D[asterisk]), vascular volume fraction (F), blood->interstitium constant of transfer (Ktrans), interstitum->plasma constant of transfer (Kep), extravascular/extracellular volume % (Ve) and plasma volume % (Ve) were investigated along with routine measures of SUV and ADC. Materials & Methods: Five subjects with a new diagnosis of epithelial ovarian cancer enrolled in the study. All subjects underwent 3 cycles of standardized chemotherapy followed by cytoreduction (debulking surgery). FDG PET/MR including DCE and IVIM was performed at baseline (T1), after cycle 1 (T2) and after cycle 3 (T3) of chemotherapy. Final responses were categorized at T3 by RECIST 1.1. Olea 3.0 software was used to generate parametric images from the multi-B-value DWI and DCE-MR datasets at all three timepoints. Parametric DICOM images were then coregistered to anatomical datasets using MIMvista and fusion was manually adjusted to optimize co-registration of tumor lesions across the multiple datasets. VOIs were manually drawn on clearly visible solid tumor deposits on PET, DCE-MR and DWI MR images. The parametric images derived from IVIM and DCE-MR at T2 were analyzed as early predictors of final response. Results: Five subjects completed FDG PET and IVIM-MR, three of which underwent DCE-MR. All subjects were partial responders by RECIST at T3. SUV values were only available for 4/5 patients due to technical difficulties and DCE-MR was only available for 3/5. All 5 subjects had good IVIM data. At T2, the SUVmax decreased on average by -39% across all subjects (p<0.001) and the SUVmean decreased on average by -43% across all subjects (p<0.001). At T2, the ADCmean increased on average by +25% across all subjects (p<0.05). At T2, the molecular diffusion restriction (D) increased on average by +43% across all subjects, approaching statistical significance (p=0.058). Furthermore, D[asterisk], F, Kep, Ktrans, and Vp increased in some subjects and decreased in others, without any recognizable pattern. Ve decreased in 3/3 patients, however, not reaching statistical significance. Conclusions: In this current FDG PET/MR study of ovarian cancer, SUVmax and ADCmean values obtained after one cycle of chemotherapy were consistently associated with partial anatomical treatment responses at end of therapy. These findings are in agreement with pre-existing literature studying the value of SUV and ADC in early treatment response assessment. Only one of seven advanced perfusion/diffusion metrics (D; molecular diffusion restriction) was reliably associated with treatment response. This finding that D is associated with treatment response is not surprising given that it is based on ADC without the contribution of intravascular diffusion. Our current small dataset does not yet demonstrate the value of the remaining analyzed advanced DCE-MR and DWI parameters. Further study is required to determine the utility of DCE- and IVIM-derived parameters in early response assessment. Voxelwise correlative studies and other advanced data processing methods are underway to determine if these advanced quantitative parameters may provide further information in the early assessment of chemotherapy treatment response. (Table Presented)

PURPOSE: To develop and test a deep learning approach named Convolutional Neural Network (CNN) for automated screening of T2 -weighted (T2 WI) liver acquisitions for nondiagnostic images, and compare this automated approach to evaluation by two radiologists. MATERIALS AND METHODS: We evaluated 522 liver magnetic resonance imaging (MRI) exams performed at 1.5T and 3T at our institution between November 2014 and May 2016 for CNN training and validation. The CNN consisted of an input layer, convolutional layer, fully connected layer, and output layer. 351 T2 WI were anonymized for training. Each case was annotated with a label of being diagnostic or nondiagnostic for detecting lesions and assessing liver morphology. Another independently collected 171 cases were sequestered for a blind test. These 171 T2 WI were assessed independently by two radiologists and annotated as being diagnostic or nondiagnostic. These 171 T2 WI were presented to the CNN algorithm and image quality (IQ) output of the algorithm was compared to that of two radiologists. RESULTS: There was concordance in IQ label between Reader 1 and CNN in 79% of cases and between Reader 2 and CNN in 73%. The sensitivity and the specificity of the CNN algorithm in identifying nondiagnostic IQ was 67% and 81% with respect to Reader 1 and 47% and 80% with respect to Reader 2. The negative predictive value of the algorithm for identifying nondiagnostic IQ was 94% and 86% (relative to Readers 1 and 2). CONCLUSION: We demonstrate a CNN algorithm that yields a high negative predictive value when screening for nondiagnostic T2 WI of the liver. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017.

Magnetic resonance (MR)/PET scanners provide an imaging platform that enables simultaneous acquisition of MR and PET data in perfect spatial and temporal registration. This feature allows improving image quality for the MR and PET images obtained during the course of an examination. In this work the authors demonstrate the use of prospective MR-based motion tracking information for removing motion blur in MR/PET images of small pulmonary nodules. The theoretical basis for the algorithms is presented alongside clinical examples of its use.

OBJECTIVES: The aims of this study were to observe the pattern of transient motion after gadoxetic acid administration including incidence, onset, and duration, and to evaluate the clinical feasibility of free-breathing gadoxetic acid-enhanced liver magnetic resonance imaging using golden-angle radial sparse parallel (GRASP) imaging with respiratory gating. MATERIALS AND METHODS: In this institutional review board-approved prospective study, 59 patients who provided informed consents were analyzed. Free-breathing dynamic T1-weighted images (T1WIs) were obtained using GRASP at 3 T after a standard dose of gadoxetic acid (0.025 mmol/kg) administration at a rate of 1 mL/s, and development of transient motion was monitored, which is defined as a distinctive respiratory frequency alteration of the self-gating MR signals. Early arterial, late arterial, and portal venous phases retrospectively reconstructed with and without respiratory gating and with different temporal resolutions (nongated 13.3-second, gated 13.3-second, gated 6-second T1WI) were evaluated for image quality and motion artifacts. Diagnostic performance in detecting focal liver lesions was compared among the 3 data sets. RESULTS: Transient motion (mean duration, 21.5 +/- 13.0 seconds) was observed in 40.0% (23/59) of patients, 73.9% (17/23) of which developed within 15 seconds after gadoxetic acid administration. On late arterial phase, motion artifacts were significantly reduced on gated 13.3-second and 6-second T1WI (3.64 +/- 0.34, 3.61 +/- 0.36, respectively), compared with nongated 13.3-second T1WI (3.12 +/- 0.51, P < 0.0001). Overall, image quality was the highest on gated 13.3-second T1WI (3.76 +/- 0.39) followed by gated 6-second and nongated 13.3-second T1WI (3.39 +/- 0.55, 2.57 +/- 0.57, P < 0.0001). Only gated 6-second T1WI showed significantly higher detection performance than nongated 13.3-second T1WI (figure of merit, 0.69 [0.63-0.76]) vs 0.60 [0.56-0.65], P = 0.004). CONCLUSIONS: Transient motion developed in 40% (23/59) of patients shortly after gadoxetic acid administration, and gated free-breathing T1WI using GRASP was able to consistently provide acceptable arterial phase imaging in patients who exhibited transient motion.

PURPOSE/OBJECTIVE:The purpose of this study was to assess the dosimetric equivalence of magnetic resonance (MR)-generated synthetic CT (synCT) and simulation CT for treatment planning in radiotherapy of rectal cancer. METHODS:This study was conducted on eleven patients who underwent whole-body PET/MR and PET/CT examination in a prospective IRB-approved study. For each patient synCT was generated from Dixon MR using a model-based method. Standard treatment planning directives were used to create a four-field box (4F), an oblique four-field (O4F) and a volumetric modulated arc therapy (VMAT) plan on synCT for treatment of rectal cancer. The plans were recalculated on CT with the same monitor units (MUs) as that of synCT. Dose-volume metrics of planning target volume (PTV) and organs at risk (OARs) as well as gamma analysis of dose distributions were evaluated to quantify the difference between synCT and CT plans. All plans were calculated using the analytical anisotropic algorithm (AAA). The VMAT plans on synCT and CT were also calculated using the Acuros XB algorithm for comparison with the AAA calculation. RESULTS:Medians of absolute differences in PTV metrics between synCT and CT plans were 0.2%, 0.2% and 0.3% for 4F, O4F and VMAT respectively. No significant differences were observed in OAR dose metrics including bladder V40Gy, mean dose in bladder, bowel V45Gy and femoral head V30Gy in any techniques. Gamma analysis with 2%/2mm dose difference/distance to agreement criteria showed median passing rates of 99.8% (range: 98.5 to 100%), 99.9% (97.2 to 100%), and 99.9% (99.4 to 100%) for 4F, O4F and VMAT, respectively. Using Acuros XB dose calculation, 2%/2mm gamma analysis generated a passing rate of 99.2% (97.7 to 99.9%) for VMAT plans. CONCLUSION/CONCLUSIONS:SynCT enabled dose calculation equivalent to conventional CT for treatment planning of 3D conformal treatment as well as VMAT of rectal cancer. The dosimetric agreement between synCT and CT calculated doses demonstrated the potential of MR-only treatment planning for rectal cancer using MR generated synCT.

Diffusion-weighted imaging (DWI) is increasingly incorporated into routine body magnetic resonance imaging protocols. DWI can assist with lesion detection and even in characterization. Quantitative DWI has exhibited promise in the discrimination between benign and malignant pathology, in the evaluation of the biologic aggressiveness, and in the assessment of the response to treatment. Unfortunately, inconsistencies in DWI acquisition parameters and analysis have hampered widespread clinical utilization. Focusing primarily on liver applications, this article will review the basic principles of quantitative DWI. In addition to standard mono-exponential fitting, the authors will discuss intravoxel incoherent motion and diffusion kurtosis imaging that involve more sophisticated approaches to diffusion quantification.

Non-Cartesian magnetic resonance imaging (MRI) sequences have shown great promise for abdominal examination during free breathing, but break down in the presence of bulk patient motion (i.e. voluntary or involuntary patient movement resulting in translation, rotation or elastic deformations of the body). This work describes a data-consistency-driven image stabilization technique that detects and excludes bulk movements during data acquisition. Bulk motion is identified from changes in the signal intensity distribution across different elements of a multi-channel receive coil array. A short free induction decay signal is acquired after excitation and used as a measure to determine alterations in the load distribution. The technique has been implemented on a clinical MR scanner and evaluated in the abdomen. Six volunteers were scanned and two radiologists scored the reconstructions. To show the applicability to other body areas, additional neck and knee images were acquired. Data corrupted by bulk motion were successfully detected and excluded from image reconstruction. An overall increase in image sharpness and reduction of streaking and shine-through artifacts were seen in the volunteer study, as well as in the neck and knee scans. The proposed technique enables automatic real-time detection and exclusion of bulk motion during MR examinations without user interaction. It may help to improve the reliability of pediatric MRI examinations without the use of sedation.

PURPOSE: Conventional fat/water separation techniques require that patients hold breath during abdominal acquisitions, which often fails and limits the achievable spatial resolution and anatomic coverage. This work presents a novel approach for free-breathing volumetric fat/water separation. METHODS: Multiecho data are acquired using a motion-robust radial stack-of-stars three-dimensional GRE sequence with bipolar readout. To obtain fat/water maps, a model-based reconstruction is used that accounts for the off-resonant blurring of fat and integrates both compressed sensing and parallel imaging. The approach additionally enables generation of respiration-resolved fat/water maps by detecting motion from k-space data and reconstructing different respiration states. Furthermore, an extension is described for dynamic contrast-enhanced fat-water-separated measurements. RESULTS: Uniform and robust fat/water separation is demonstrated in several clinical applications, including free-breathing noncontrast abdominal examination of adults and a pediatric subject with both motion-averaged and motion-resolved reconstructions, as well as in a noncontrast breast exam. Furthermore, dynamic contrast-enhanced fat/water imaging with high temporal resolution is demonstrated in the abdomen and breast. CONCLUSION: The described framework provides a viable approach for motion-robust fat/water separation and promises particular value for clinical applications that are currently limited by the breath-holding capacity or cooperation of patients. Magn Reson Med, 2016. (c) 2016 International Society for Magnetic Resonance in Medicine.

BACKGROUND: Interest in MR-only treatment planning for radiation therapy is growing rapidly with the emergence of integrated MRI/linear accelerator technology. The purpose of this study was to evaluate the feasibility of using synthetic CT images generated from conventional Dixon-based MRI scans for radiation treatment planning of lung cancer. METHODS: Eleven patients who underwent whole-body PET/MR imaging following a PET/CT exam were randomly selected from an ongoing prospective IRB-approved study. Attenuation maps derived from the Dixon MR Images and atlas-based method was used to create CT data (synCT). Treatment planning for radiation treatment of lung cancer was optimized on the synCT and subsequently copied to the registered CT (planCT) for dose calculation. Planning target volumes (PTVs) with three sizes and four different locations in the lung were planned for irradiation. The dose-volume metrics comparison and 3D gamma analysis were performed to assess agreement between the synCT and CT calculated dose distributions. RESULTS: Mean differences between PTV doses on synCT and CT across all the plans were -0.1% +/- 0.4%, 0.1% +/- 0.5%, and 0.4% +/- 0.5% for D95, D98 and D100, respectively. Difference in dose between the two datasets for organs at risk (OARs) had average differences of -0.14 +/- 0.07 Gy, 0.0% +/- 0.1%, and -0.1% +/- 0.2% for maximum spinal cord, lung V20, and heart V40 respectively. In patient groups based on tumor size and location, no significant differences were observed in the PTV and OARs dose-volume metrics (p > 0.05), except for the maximum spinal-cord dose when the target volumes were located at the lung apex (p = 0.001). Gamma analysis revealed a pass rate of 99.3% +/- 1.1% for 2%/2 mm (dose difference/distance to agreement) acceptance criteria in every plan. CONCLUSIONS: The synCT generated from Dixon-based MRI allows for dose calculation of comparable accuracy to the standard CT for lung cancer treatment planning. The dosimetric agreement between synCT and CT calculated doses warrants further development of a MR-only workflow for radiotherapy of lung cancer.