Diffusion-weighted MRI treatment monitoring of primary hypofractionated proton and carbon ion prostate cancer irradiation using raster scan technique.

PURPOSE: To investigate parametric changes in the apparent diffusion coefficient (ADC) at multiple timepoints during and after completion of primary proton and carbon ion irradiation of prostate cancer (PCa) as compared with normal-appearing prostate parenchyma. MATERIALS AND METHODS: In all, 92 patients with histologically confirmed PCa received either proton or carbon ion hypofractionated radiotherapy (RT). All were prospectively evaluated with diffusion-weighted magnetic resonance imaging (DWI-MRI) at five timepoints: baseline, day 10 during therapy and 6 weeks, 6 months, and 18 months after treatment. Linear mixed models (LMM) were used to evaluate the effects of radiation, antihormonal therapy, time, and type of particle irradiation on manual ADC measurements. ADC differences related to prostate-specific antigen (PSA) relapse according to PSA thresholds and to Vancouver rules and Phoenix criteria were examined using LMM and unpaired Student's t-test. RESULTS: A measurable and continuous increase of tumor ADC measurements from baseline (1.194 × 10-3 mm2 /s) during (1.350 × 10-3 mm2 /s, day 10, P = 0.006) and after treatment (1.355/1.430/1.490 × 10-3 mm2 /s, week 6 / month 6 / month 18, P = 0.001/<0.001/<0.001) was found. ADC values of normal-appearing control tissue remained unchanged. Androgen deprivation (P ≥ 0.320), different PSA thresholds (P = 0.634), and PSA relapse criteria according to Vancouver rules (P ≥ 0.776) had no effect. A weak association between 18-month measurements and Phoenix criteria (P = 0.046) was found. CONCLUSION: ADC parametric changes were distinct in tumor tissue, highlighting the ability of diffusion MRI to evaluate different aspects of the microscopic pathophysiology. Although promising, their use as noninvasive imaging biomarkers requires further validation. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:850-860.

Potential of quantitative susceptibility mapping for detection of prostatic calcifications.

PURPOSE: To evaluate whether quantitative susceptibility (QSM) may be used as an alternative to computed tomography (CT) to detect calcification in prostate cancer patients. MATERIALS AND METHODS: Susceptibility map calculation was performed using 3D gradient echo magnetic resonance imaging (MRI) data from 26 patients measured at 3T who previously received a planning CT of the prostate. Phase images were unwrapped using Laplacian-based phase unwrapping, the background field was removed with the V-SHARP method, and susceptibility maps were calculated with the iLSQR method. Two blinded readers were asked to identify peri- and intraprostatic calcifications. RESULTS: Average mean and minimum susceptibility values (referenced to iliopsoas muscle) of calcifications were -0.249 ± 0.179 ppm and -0.551 ± 0.323 ppm, and average mean and maximum intensities in CT images were 319 ± 164 HU and 679 ± 392 HU. Twenty-one and 17 out of 22 prostatic calcifications were identified using susceptibility maps and magnitude images, respectively, as well as more than half of periprostatic phleboliths depicted by CT. Calcifications in the prostate and its periphery were quantitatively differentiable from noncalcified prostate tissue in CT (mean values for calcifications / for noncalcified tissue: 71 to 649 / -1 to 83 HU) and in QSM (mean values for calcifications / for noncalcified tissue: -0.641 to 0.063 / -0.046 to 0.181 ppm). Moreover, there was a significant correlation between susceptibility values and CT image intensities for calcifications (P < 0.004). CONCLUSION: Prostatic calcifications could be well identified with QSM. Susceptibility maps can be easily obtained from clinical prostate MR protocols that include a 3D gradient echo sequence, rendering it a promising technique for detection and quantification of intraprostatic calcifications. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:889-898.

Mask-Adapted Background Field Removal for Artifact Reduction in Quantitative Susceptibility Mapping of the Prostate.

We propose an alternative processing method for quantitative susceptibility mapping of the prostate that reduces artifacts and enables better visibility and quantification of calcifications and other lesions. Three-dimensional gradient-echo magnetic resonance data were obtained from 26 patients at 3 T who previously received a planning computed tomography of the prostate. Phase images were unwrapped using Laplacian-based phase unwrapping. The background field was removed with the V-SHARP method using tissue masks for the entire abdomen (Method 1) and masks that excluded bone and the rectum (Method 2). Susceptibility maps were calculated with the iLSQR method. The quality of susceptibility maps was assessed by one radiologist and two physicists who rated the data for visibility of lesions and data quality on a scale from 1 (poor) to 4 (good). The readers rated susceptibility maps computed with Method 2 to be, on average, better for visibility of lesions with a score of 2.9 ± 1.1 and image quality with a score of 2.8 ± 0.8 compared with maps computed with Method 1 (2.4 ± 1.2/2.3 ± 1.0). Regarding strong artifacts, these could be removed using adapted masks, and the susceptibility values seemed less biased by the artifacts. Thus, using an adapted mask for background field removal when calculating susceptibility maps of the prostate from phase data reduces artifacts and improves visibility of lesions.

MRI-based simulation of treatment plans for ion radiotherapy in the brain region.

PURPOSE: To test the potential of MRI-based treatment plan simulation for ion radiotherapy in the brain region. MATERIALS AND METHODS: A classification-based tissue segmentation method based on discriminant analysis was employed to derive so-called pseudo CT numbers from MR images of three patients with lesions in the head region undergoing ion radiotherapy. Treatment plans for ions, and for comparison purposes also for photons, were subsequently optimized and simulated using both MRI-based pseudo CT and a standard X-ray-based reference CT. RESULTS: Pseudo CTs revealed mean absolute errors in CT number in the range of 141-165 HU. While soft tissue was in good agreement with reference CT values, large deviations appeared at air cavities and bones as well as at interfaces of different tissue types. In simulations of ion treatment plans, pseudo CT optimizations showed small underdosages of target volumes with deviations in the PTV mean dose of 0.4-2.0% in comparison to reference CT optimizations. In contrast, the PTV mean dose in photon treatment plans differed by no more than 0.2%. CONCLUSIONS: The main challenge in deriving pseudo CT numbers from MRI was the correct assignment of air and compact bone. In this study, the impact of deviations on simulations of ion and photon treatment plans in the brain region was small, however for more complicated morphologies a further improvement of the classification method including MR imaging of compact bone is required.