Prostate cancer is the most common cancer among males in the Western world (1). However, in magnetic resonance imaging (MRI), prostate cancer detection can be hampered by postbiopsy hemorrhage and/or calcifications (2); in particular, the detection of intraprostatic calcifications is difficult because of variations in signal intensity and the small size of the lesions (3). In addition, the treatment outcome may be influenced by the presence of calcifications (4, 5).
After quantitative susceptibility mapping (QSM) (6–8) had been successfully applied in several clinical studies of the brain (9–13), there have been in vivo applications of QSM in the liver (14, 15). Moreover, it has recently been shown that QSM can be a valuable tool to detect intra- and periprostatic calcifications (16), but in cases of intestinal movement or air in the rectum, severe artifacts can occur when inverting unreliable phase information because of nonlocality of the inversion kernel (17–21) for QSM and can render the detection of calcifications difficult. Because streaking artifacts in susceptibility maps not only corrupt image quality and hamper detection of lesions (calcifications or hemorrhage), but also bias the accurate quantification of susceptibility values, the reduction or elimination of artifacts is crucial.
The purpose of this study is to propose a method to reduce or eliminate artifacts and enable better visibility of calcifications and other lesions, for example, hemorrhage, in the prostate.
The study was conducted in accordance with the Declaration of Helsinki. Institutional review board approval was obtained, and all subjects provided written informed consent. Patient data were collected over the period of 1.3 years. In this study, 26 patients (age range: 55 to 80 years; mean age: 67.9 ± 6.8 years; mean body mass index: 26.2 ± 3.5 kg/m2; range: 20.5 to 34.8 kg/m2) who had previously received planning computed tomography (CT) were included.
Magnitude and phase data used for QSM were acquired using a fully flow-compensated 3D gradient-echo (GRE) sequence that was part of a clinical protocol on two 3 T magnetic resonance (MR) scanners (Biograph mMR and MAGNETOM Prisma, Siemens Healthcare, Erlangen, Germany). The sequence was applied with the water excitation option switched on to suppress fat signals in 15 patients and was run without fat suppression in 12 patients. One patient was measured once with and once without fat suppression. Measurements on the Biograph mMR scanner were performed with an 8-channel surface coil; the acquisition parameters were as follows: flip angle = 15°, repetition time/echo time = 24/15 milliseconds, voxel size = 1.0 × 1.0 × 1.7 mm3, acquisition matrix = 320 × 240 × 30–40, readout bandwidth = 822 Hz/pixel, and acquisition time = 5.55 minutes. Measurements on the MAGNETOM Prisma scanner were performed using an 18-channel surface coil with the following acquisition parameters: flip angle = 15°, repetition time/echo time = 24/20 milliseconds, voxel size = 0.83 × 0.83 × 1.6 mm3, acquisition matrix = 384 × 288 × 36, readout bandwidth = 765 Hz/pixel, phase and section partial Fourier = 7/8, and acquisition time = 4.52 minutes.
CT (Siemens and Philips scanners, Philips Healthcare, Hamburg, Germany) imaging parameters ranged from 120 to 140 kV peak, with slice thickness = 2–5 mm (3 mm for 20 patients), tube current–exposure time product = 93–300 mA · s (300 mA · s in 14 patients), and pitch factor = 0.6 to 1.5. A previous study has used the same data (16).
MR Data Processing
Phase images from different coils were combined on the scanner using the adaptive combine method (22). Phase images were unwrapped in Matlab (Matlab R2014b, The MathWorks, Inc., Natick, Massachusetts) using a Laplacian-based phase unwrapping algorithm (18, 23, 24). The background field was removed with sophisticated harmonic artifact reduction for phase data (V-SHARP) with varying spherical kernel sizes (up to 25 mm) (23, 24). First, masks encompassing the entire abdomen were used (“Method 1”). Second, masks encompassing the entire abdomen excluding bone and the rectum (if signal voids were present in the rectum) were used (“Method 2”). The masks were manually created using the Medical Imaging Interaction Toolkit (25, 26). Using the processed phase maps and the GRE magnitude data, susceptibility maps were calculated using the iLSQR method (18, 27). Susceptibility values were referenced (28) to the iliopsoas muscle (indicated in the first column in Figure 1 by “R”) as suggested by Straub et al. (16).
Calcifications, both intraprostatic and phleboliths, were identified using CT data, and the volumes of interest (VOIs) encompassing them were drawn using the Medical Imaging Interaction Toolkit. In addition, VOIs for hemorrhages and a noncalcified control region in the prostate were drawn on GRE magnitude images/susceptibility maps. All mean susceptibility values and standard deviations were calculated with Matlab as mean values over the specified VOIs after referencing the susceptibility values to the reference tissue.
In addition, the data were evaluated by three readers who were blinded to the CT data. Reader 1 was a radiologist with eight years of experience in assessing prostate MRI, whereas Readers 2 and 3 were physicists. They were provided with information about sections that contained lesions and were asked to rate the data for visibility of lesions and for image quality concerning the region of the prostate and the reference region (iliopsoas muscle) from 1 (poor) to 4 (good). They were asked to perform the following two rounds of scoring:
They were given the susceptibility maps i.e. calculated using Methods 1 and 2 of the 27 measurements. They were not provided with any information about the ordering. They were asked to consecutively rate the data.
They were asked to repeat the reading. For the second reading, the readers were provided with the susceptibility maps computed with Methods 1 and 2 in pairs. They were asked to compare these two paired maps and rate each of these maps according to the same criteria as in the first reading session.
Quality Assessment by Readers
When assessing all susceptibility maps separately, Reader 1 always rated the visibility of lesions as either equal or better for Method 2. The quality of the susceptibility maps in the region of the prostate and in the reference region was rated as either equal or better for Method 2 in 24 (out of 27) cases and in 20 (out of 27) cases, respectively, by Reader 1. Reader 2 rated the visibility of lesions and the quality of susceptibility maps in the region of the prostate/reference region always as either equal or better for Method 2 than for Method 1, except for one case, in which the visibility of lesions was rated better for Method 1. Reader 3 rated the visibility of lesions for Method 2 always as either equal or better with one exception. The quality of the susceptibility maps in the region of the prostate and in the reference region was rated as either equal or better in 24 (out of 27) cases by Reader 3.
When directly comparing the susceptibility maps computed by Methods 1 and 2, the readers always rated the susceptibility maps as either equal or better for Method 2. The mean scores of the three readers are shown in Table 1.
Figure 1 shows susceptibility maps of four patients computed with a mask including the entire abdomen (Method 1) and a mask where bones and rectum were excluded (Method 2). In addition, the difference of the susceptibility maps calculated using Method 1 and Method 2 is shown as well as the unwrapped phase map. In Patients 2 and 13, strong artifacts (thick arrows) can be observed close to the rectum when using Method 1. These artifacts coincide with large field distortions seen on the phase maps. In Patients 2 and 13, these artifacts lie exactly in the region where the calcifications are located (white arrow heads). In these cases, susceptibility values differ more strongly between the two methods than for the two susceptibility maps without strong artifacts (Patients 12, 14). Using Method 1 results in more regions in which strong noise can be observed (thin arrows), which, however, does not strongly affect the visibility of the prostate itself or the reference region.
Figure 2 shows mean susceptibility values with standard deviations of all measurements for calcifications in the prostate, phleboliths, hemorrhage, a noncalcified control region in the prostate, and the reference region (iliopsoas muscle). Mean susceptibility values differ only slightly between the two methods, but standard deviations are lower for Method 2.
In particular, in cases where severe artifacts from intestinal movements or air tissue interfaces impair the quality of susceptibility maps, masking such regions and therefore treating the field distortions they cause as artificial background field may be a viable option to reliably obtain clinically useful susceptibility maps that allow good depiction and quantification of calcifications or hemorrhage.
A similar approach to increase susceptibility maps' quality by masking out problematic regions has been proposed to reduce artifacts when calculating susceptibility maps of the brain when hemorrhage is present (29): the hemorrhage is masked by thresholding, and susceptibility maps are calculated both for the mask of the whole brain and the mask excluding the hemorrhage. These two susceptibility maps are then superposed to obtain a susceptibility map where artifacts are either reduced or eliminated. In the case of the prostate, it has to be evaluated whether mask generation can be performed automatically, for example, using active appearance models, atlas registration, or level sets (30) on GRE magnitude data, as prostate MRI image segmentation has been an area of intense research because of the increased use of MRI as a modality for the clinical workup of prostate cancer. Similar approaches may be applicable to investigations of other organs in which air tissue interfaces or motion are inevitably present during imaging. In contrast, in the case of motion, triggering, or motility-reducing medication (i.e., hyoscine butylbromide) may be further options to reduce artifacts.
The assessment of prostatic calcifications with MRI techniques can be of importance in various applications, such as in radiation therapy and high intensity focused ultrasound prostatic calcifications can influence dose and therefore treatment outcome (4, 5); and calcifications can be used as a position marker in image-guided therapy (3). Moreover, knowledge about calcifications may gain importance in future applications, for example, MR-linac procedures (31).
Limitations of this study include the small number of patients and the use of different scanners with slightly different imaging parameters. Moreover, drawing masks of the abdomen in which bones and the rectum are excluded can be very time-consuming. In addition, the effect of using a multiecho acquisition and water–fat separation (32, 33) on the quality of susceptibility maps of the prostate has to be assessed in the future.
In conclusion, using adapted masks for susceptibility map calculation can efficiently eliminate severe artifacts and enable correct quantification of susceptibility in the prostate even in difficult cases of intestinal movement or air in the rectum.