Maaike R. Moman

Validation of functional imaging with pathology for tumor delineation in the prostate

INTRODUCTION A study was performed to validate magnetic resonance (MR) based prostate tumor delineations with pathology. MATERIAL AND METHODS Five patients with biopsy proven prostate cancer underwent a T2 weighted (T2w), diffusion weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) scan before prostatectomy. Suspicious regions were delineated based on all available MR information. After prostatectomy whole-mount hematoxylin-eosin stained (H&E) sections were made. Tumor tissue was delineated on the H&E stained sections and compared with the MR based delineations. The registration accuracy between the MR images and H&E stained sections was estimated. RESULTS A tumor coverage of 44-89% was reached by the MR based tumor delineations. The application of a margin of approximately 5mm to the MR based tumor delineations yielded a tumor coverage of 85-100% in all patients. Errors created during the registration procedure were 2-3mm, which cannot completely explain the limited tumor coverage. CONCLUSIONS An accurate tissue processing and registration method was presented (registration error 2-3mm), which enables the validation of MR based tumor delineations with pathology. Reasonable tumor coverage of about 85% and larger was found when applying a margin of approximately 5 mm to the MR based tumor delineations.

MRI-guided robotic system for transperineal prostate interventions: proof of principle

In this study, we demonstrate the proof of principle of the University Medical Center Utrecht (UMCU) robot dedicated to magnetic resonance imaging (MRI)-guided interventions in patients. The UMCU robot consists of polymers and non-ferromagnetic materials. For transperineal prostate interventions, it can be placed between the patients legs inside a closed bore 1.5T MR scanner. The robot can manually be translated and rotated resulting in five degrees of freedom. It contains a pneumatically driven tapping device to automatically insert a needle stepwise into the prostate using a controller unit outside the scanning room. To define the target positions and to verify the needle insertion point and the needle trajectory, a high-resolution 3D balanced steady state free precession (bSSFP) scan that provides a T2/T1-weighted contrast is acquired. During the needle insertion fast 2D bSSFP images are generated to track the needle on-line. When the target position is reached, the radiation oncologist manually places a fiducial gold marker (small seed) at this location. In total two needle trajectories are used to place all markers. Afterwards, a high-resolution 3D bSSFP scan is acquired to visualize the fiducial gold markers. Four fiducial gold markers were placed transperineally into the prostate of a patient with a clinical stage T3 prostate cancer. In the generated scans, it was possible to discriminate the patients anatomy, the needle and the markers. All markers were delivered inside the prostate. The procedure time was 1.5 h. This study proves that MRI-guided needle placement and seed delivery in the prostate with the UMCU robot are feasible.

Pathologic Validation of a Model Based on Diffusion-Weighted Imaging and Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Tumor Delineation in the Prostate Peripheral Zone

PURPOSE For focal boost strategies in the prostate, the robustness of magnetic resonance imaging-based tumor delineations needs to be improved. To this end we developed a statistical model that predicts tumor presence on a voxel level (2.5×2.5×2.5 mm3) inside the peripheral zone. Furthermore, we show how this model can be used to derive a valuable input for radiotherapy treatment planning. METHODS AND MATERIALS The model was created on 87 radiotherapy patients. For the validation of the voxelwise performance of the model, an independent group of 12 prostatectomy patients was used. After model validation, the model was stratified to create three different risk levels for tumor presence: gross tumor volume (GTV), high-risk clinical target volume (CTV), and low-risk CTV. RESULTS The model gave an area under the receiver operating characteristic curve of 0.70 for the prediction of tumor presence in the prostatectomy group. When the registration error between magnetic resonance images and pathologic delineation was taken into account, the area under the curve further improved to 0.89. We propose that model outcome values with a high positive predictive value can be used to define the GTV. Model outcome values with a high negative predictive value can be used to define low-risk CTV regions. The intermediate outcome values can be used to define a high-risk CTV. CONCLUSIONS We developed a logistic regression with a high diagnostic performance for voxelwise prediction of tumor presence. The model output can be used to define different risk levels for tumor presence, which in turn could serve as an input for dose planning. In this way the robustness of tumor delineations for focal boost therapy can be greatly improved.

Focal Salvage Guided by T2-Weighted and Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Prostate Cancer Recurrences

PURPOSE Salvage treatment of the entire prostate for local recurrent cancer after primary radiotherapy is associated with high toxicity rates. Our goal was to show that, using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the visualization of a recurrence, focal salvage treatment can be performed, with, potentially, a reduction in toxicity. METHODS AND MATERIALS We performed MRI, including a DCE sequence, in 7 patients with biopsy-proven locally recurrent prostate cancer. The specific regions of interest suspect for containing tumor were delineated using DCE and T(2)-weighted MRI scans. Subsequently, focal salvage high-dose-rate brachytherapy plans were created to illustrate the principle of focal salvage. Total salvage treatment plans were also created for comparison. RESULTS The transfer constant (K(trans)) values from the DCE were 0.33-0.67 min(-1) for areas suspect for tumor and 0.07-0.25 min(-1) for normal tissue. In 4 cases, a focal salvage plan could be generated; 93-100% of the gross tumor volume was covered with the prescribed dose, with relative sparing of the bladder, rectum, and urethra. In the total salvage plans, 24-53% of the gross tumor volume was covered, and the organs at risk received high doses. In 3 cases, a focal salvage plan could not be created because of multifocal tumor, seminal vesicle extension, or capsular extension. CONCLUSION Focal salvage treatment plans can be created in patients with local recurrent prostate cancer after radiotherapy. DCE-MRI supports the localization of the target area. This could lead to less toxicity in patients with local recurrent prostate cancer.

Focal salvage iodine-125 brachytherapy for prostate cancer recurrences after primary radiotherapy: a retrospective study regarding toxicity, biochemical outcome and quality of life.

PURPOSE Whole-gland salvage for recurrent prostate cancer (PCa) shows high failure and toxicity rates. Early and adequate localization of recurrences enables focal salvage, thereby potentially improving functional outcomes, while maintaining cancer control. MATERIALS AND METHODS Retrospective analysis yielded 20 focal salvage I125 brachytherapy patients for locally recurrent PCa after primary radiotherapy. Tumor was defined by multiparametric MRI and correspondence with transrectal biopsies. Dose data were obtained intra-operatively. The tumor was prescribed ⩾144 Gy. Toxicity was scored by the Common Terminology Criteria for Adverse Events version 4 (CTCAE-4). Biochemical failure (BF) was defined using the Phoenix criteria (PSA-nadir + 2.0 ng/ml). Quality of life (QoL) was measured by SF-36 Health Survey and European Organization of Research and Treatment of Cancer (EORTC) C30+3 and PR25 questionnaires. RESULTS With a median follow-up of 36 months (range 10-45), six patients experienced BF, of which three had no initial response. Grade 3 genitourinary (GU) toxicity occurred in one patient (a urethral stricture). The five previously potent patients retained erectile function. QoL remained decreased with regard to urinary symptoms. CONCLUSION Focal salvage I125 brachytherapy showed one grade 3 GU toxicity in the 20 treated patients. Biochemical response and QoL were acceptable.

Accurate prostate tumour detection with multiparametric magnetic resonance imaging: dependence on histological properties.

Abstract Background. To benefit most of focal treatment of prostate tumours, detection with high precision of all tumour voxels is needed. Although diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have good diagnostic performance, perfect tumour detection is challenging. In this study, we investigated the variation in prostate tissue characteristics Gleason score (GS), cell density (CD) and microvessel density (MVD) to explain the limitations in tumour voxel detection with a MRI-based logistic regression model. Material and methods. Twelve radical prostatectomy patients underwent a pre-operative 3.0T DWI and DCE-MRI exam. The MRI scans were used to calculate voxel-wise tumour probability with a logistic regression model for the peripheral zone (PZ) of the prostate. Tumour probability maps were correlated and validated with whole-mount histology. Additionally, from the whole-mount histological sections CD, MVD and GS were retrieved for every single voxel. GS, CD and MVD of true- and false-positive voxels and of true- and false-negative voxels were compared using Mann-Whitney U-tests. Results. False-negative tumour voxels had significantly lower CD and MVD (p < 0.0001) and were similar to non-tumour PZ. True-positive detected tumour voxels had high CDs and MVDs (p < 0.0001). In addition, tumour voxels with higher GS showed a trend towards more frequent detection (p = 0.06). Tumour voxels with GS ≥ 3 + 4 showed higher CD and MVD compared to tumour voxels with GS 3 + 3 (p < 0.0001). Conclusion. Tumour voxels with low CD and MVD resemble healthy tissue and are limiting tumour voxel detection using DWI and DCE-MRI. Nevertheless, the most aggressive tumour voxels, containing high CD, MVD and GS, are more likely to be detected and can therefore be treated with high dose using focal therapy or focal boosting.

Dynamic Contrast-enhanced CT for Prostate Cancer: Relationship between Image Noise, Voxel Size, and Repeatability

PURPOSE To evaluate the relationship between image noise, voxel size, and voxel-wise repeatability of a dynamic contrast agent-enhanced (DCE) computed tomographic (CT) examination for prostate cancer. MATERIALS AND METHODS This prospective study was approved by the local research ethics committee, and all patients gave written informed consent. Twenty-nine patients (mean age, 69.1 years; range, 56-80 years) with biopsy-proved prostate cancer underwent two DCE CT examinations within 1 week prior to radiation therapy. Parameter maps of transfer constant (K(trans)), the fraction of blood plasma (v(p)), the fraction of extravascular extracellular space (v(e)), and the flux rate constant between the extravascular extracellular space and plasma (k(ep)) were calculated at 15 different image resolutions, with kernel sizes ranging from 0.002 to 2.57 cm(3). Statistical analysis to quantify the voxel-wise repeatability was performed by using a Bland-Altman analysis on all tracer kinetic model parameter maps of each patient. From this analysis, the within-voxel standard deviation (wSD) was calculated as a function of spatial resolution. RESULTS A kernel size in the range of 0.1-0.3 cm(3) yields reliable information. At 0.15 cm(3), the median wSDs of K(trans), k(ep), v(p), and v(e) are 0.047 min(-1), 0.144 min(-1), 0.011, and 0.104, respectively. With increasing kernel size, these values reach stable levels of approximately 0.02 min(-1), 0.05 min(-1), 0.005, and 0.05, respectively. CONCLUSION There is a high voxel-wise repeatability of the DCE CT imaging technique for prostate cancer for kernel sizes as small as 0.1 cm(3). With the relationship between kernel size, image noise and voxel-wise repeatability, it becomes possible to estimate for alternative DCE CT protocols (eg, those with a reduced radiation dose) at what kernel size a sufficient repeatability can be obtained.

Difficulties and potential of correlating local recurrences in prostate cancer with the delivered local dose

In the previous decades the distinction between a local relapse and distant metastases was difficult to accomplish in an early stage. As a consequence, a failure could only be coarsely related to the original radiotherapy treatment. Currently, due to better imaging and position verification techniques, the actual dose within the prostate can be estimated, taking position uncertainties into account. Furthermore, advanced functional MRI techniques, such as MR spectroscopy (MRS) and dynamic contrast-enhanced MRI (DCE-MRI), increase the chance of localizing a local recurrence within the prostate. With this information the correlation between the actual previously delivered dose and a local relapse can be established, using non-rigid registration of the planning CT and the post-recurrence MRI. The current study describes the possibilities and problems in obtaining this correlation. This serves as a framework for investigating a reliable dose effect relationship in the future.

The use of probability maps to deal with the uncertainties in prostate cancer delineation

BACKGROUND AND PURPOSE The use of dynamic contrast-enhanced (DCE) imaging for delineation of prostate tumors requires that decisions are made on a voxel wise basis about the presence of tumor. While the sensitivity and specificity of this technique is high, we propose a probabilistic approach to deal with the intrinsic imaging uncertainty. MATERIAL AND METHODS Twenty-nine patients with biopsy-proven prostate cancer underwent a DCE-CT exam prior to radiotherapy. From a logistic regression on K(trans) values from healthy and diseased appearing prostate regions we obtained a probability function for the presence of tumor. K(trans) parameter maps were converted into probability maps and a stratification was applied at the 5% and 95% probability level, to identify low-, intermediate-, and high-risk areas for the presence of tumor. RESULTS In all patients, regions with high-, intermediate-, and low-risk were identified, with median volume percentages of 7.6%, 40.0%, and 52.1%, respectively. The contiguous areas that resulted from the voxel wise stratification can be interpreted as GTV, high-risk CTV, and CTV. CONCLUSIONS K(trans) parameter maps from a DCE-CT exam can be converted into probability maps for the presence of tumor. In this way, the intrinsic uncertainty that a voxel contains tumor can be incorporated into the treatment planning process.

Why prostate tumour delineation based on apparent diffusion coefficient is challenging: An exploration of the tissue microanatomy

Abstract Background. Focal boosting of prostate tumours to improve outcome, requires accurate tumour delineation. For this, the apparent diffusion coefficient (ADC) derived from diffusion-weighted MR imaging (DWI) seems a useful tool. On voxel level, the relationship between ADC and histological presence of tumour is, however, ambiguous. Therefore, in this study the relationship between ADC and histological variables was investigated on voxel level to understand the strengths and limitations of DWI for prostate tumour delineation. Material and methods. Twelve radical prostatectomy patients underwent a pre-operative 3.0T DWI exam and the ADC was calculated. From whole-mount histological sections cell density and glandular area were retrieved for every voxel. The distribution of all variables was described for tumour, peripheral zone (PZ) and central gland (CG) on regional and voxel level. Correlations between variables and differences between regions were calculated. Results. Large heterogeneity of ADC on voxel level was observed within tumours, between tumours and between patients. This heterogeneity was reflected by the distribution of cell density and glandular area. On regional level, tumour was different from PZ having higher cell density (p = 0.007), less glandular area (p = 0.017) and lower ADCs (p = 0.017). ADC was correlated with glandular area (r = 0.402) and tumour volume (r = −0.608), but not with Gleason score. ADC tended to decrease with increasing cell density (r = −0.327, p = 0.073). On voxel level, correlations between ADC and histological variables varied among patients, for cell density ranging from r = −0.439 to r = 0.261 and for glandular area from r = 0.593 to r = 0.207. Conclusions. The variation in ADC can to a certain extent be explained by the variation in cell density and glandular area. The ADC is highly heterogeneous, which reflects the heterogeneity of malignant and benign prostate tissue. This heterogeneity might however obscure small tumours or parts of tumours. Therefore, DWI has to be used in the context of multiparametric MRI.