Pieter Slagmolen

Nonrigid Image Registration Using Conditional Mutual Information

Maximization of mutual information (MMI) is a popular similarity measure for medical image registration. Although its accuracy and robustness has been demonstrated for rigid body image registration, extending MMI to nonrigid image registration is not trivial and an active field of research. We propose conditional mutual information (cMI) as a new similarity measure for nonrigid image registration. cMI starts from a 3-D joint histogram incorporating, besides the intensity dimensions, also a spatial dimension expressing the location of the joint intensity pair. cMI is calculated as the expected value of the cMI between the image intensities given the spatial distribution. The cMI measure was incorporated in a tensor-product B-spline nonrigid registration method, using either a Parzen window or generalized partial volume kernel for histogram construction. cMI was compared to the classical global mutual information (gMI) approach in theoretical, phantom, and clinical settings. We show that cMI significantly outperforms gMI for all applications.

Multiparametric MRI for prostate cancer localization in correlation to whole-mount histopathology

To prospectively evaluate multiparametric magnetic resonance imaging (MRI) for accurate localization of intraprostatic tumor nodules, with whole‐mount histopathology as the gold standard.

Development and external validation of a predictive model for pathological complete response of rectal cancer patients including sequential PET-CT imaging

PURPOSE To develop and validate an accurate predictive model and a nomogram for pathologic complete response (pCR) after chemoradiotherapy (CRT) for rectal cancer based on clinical and sequential PET-CT data. Accurate prediction could enable more individualised surgical approaches, including less extensive resection or even a wait-and-see policy. METHODS AND MATERIALS Population based databases from 953 patients were collected from four different institutes and divided into three groups: clinical factors (training: 677 patients, validation: 85 patients), pre-CRT PET-CT (training: 114 patients, validation: 37 patients) and post-CRT PET-CT (training: 107 patients, validation: 55 patients). A pCR was defined as ypT0N0 reported by pathology after surgery. The data were analysed using a linear multivariate classification model (support vector machine), and the models performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. RESULTS The occurrence rate of pCR in the datasets was between 15% and 31%. The model based on clinical variables (AUC(train)=0.61±0.03, AUC(validation)=0.69±0.08) resulted in the following predictors: cT- and cN-stage and tumour length. Addition of pre-CRT PET data did not result in a significantly higher performance (AUC(train)=0.68±0.08, AUC(validation)=0.68±0.10) and revealed maximal radioactive isotope uptake (SUV(max)) and tumour location as extra predictors. The best model achieved was based on the addition of post-CRT PET-data (AUC(train)=0.83±0.05, AUC(validation)=0.86±0.05) and included the following predictors: tumour length, post-CRT SUV(max) and relative change of SUV(max). This model performed significantly better than the clinical model (p(train)<0.001, p(validation)=0.056). CONCLUSIONS The model and the nomogram developed based on clinical and sequential PET-CT data can accurately predict pCR, and can be used as a decision support tool for surgery after prospective validation.

Biological image-guided radiotherapy in rectal cancer: Is there a role for FMISO or FLT, next to FDG?

Purpose. The purpose of this study is to investigate the use of PET/CT with fluorodeoxyglucose (FDG), fluorothymidine (FLT) and fluoromisonidazole (FMISO) for radiotherapy (RT) target definition and evolution in rectal cancer. Materials and methods. PET/CT was performed before and during preoperative chemoradiotherapy (CRT) in 15 patients with resectable rectal cancer. PET signals were delineated and CT images on the different time points were non-rigidly registered. Mismatch analyses were carried out to quantify the overlap between FDG and FLT or FMISO tumour volumes (TV) and between PET TVs over time. Results. Ninety sequential PET/CT images were analyzed. The mean FDG, FLT and FMISO-PET TVs showed a tendency to shrink during preoperative CRT. On each time point, the mean FDG-PET TV was significantly larger than the FMISO-PET TV but not significantly larger than the mean FLT-PET TV. There was a mean 65% mismatch between the FMISO and FDG TVs obtained before and during CRT. FLT TVs corresponded better with the FDG TVs (25% mismatch before and 56% during CRT). During CRT, on average 61% of the mean FDG TV (7 cc) overlapped with the baseline mean TV (15.5 cc) (n=15). For FLT, the TV overlap was 49% (n=5) and for FMISO only 20% of the TV during CRT remained inside the contour at baseline (n=10). Conclusion. FDG, FLT and FMISO-PET reflect different functional characteristics that change during CRT in rectal cancer. FLT and FDG show good spatial correspondence, while FMISO seems less reliable due to the non-specific FMISO uptake in normoxic tissue and tracer diffusion through the bowel wall. FDG and FLT-PET/CT imaging seem most appropriate to integrate in preoperative RT for rectal cancer.

Subclinical cardiotoxicity detected by strain rate imaging up to 14 months after breast radiation therapy.

PURPOSE Strain rate imaging (SRI) is a new echocardiographic modality that enables accurate measurement of regional myocardial function. We investigated the role of SRI and troponin I (TnI) in the detection of subclinical radiation therapy (RT)-induced cardiotoxicity in breast cancer patients. METHODS AND MATERIALS This study prospectively included 75 women (51 left-sided and 24 right-sided) receiving adjuvant RT to the breast/chest wall and regional lymph nodes. Sequential echocardiographs with SRI were obtained before RT, immediately after RT, and 8 and 14 months after RT. TnI levels were measured on the first and last day of RT. RESULTS Mean heart and left ventricle (LV) doses were both 9 ± 4 Gy for the left-sided patients and 4 ± 4 Gy and 1 ± 0.4 Gy, respectively, for the right-sided patients. A decrease in strain was observed at all post-RT time points for left-sided patients (-17.5% ± 1.9% immediately after RT, -16.6% ± 1.4% at 8 months, and -17.7% ± 1.9% at 14 months vs -19.4% ± 2.4% before RT, P<.01) but not for right-sided patients. When we considered left-sided patients only, the highest mean dose was given to the anterior left ventricular (LV) wall (25 ± 14 Gy) and the lowest to the inferior LV wall (3 ± 3 Gy). Strain of the anterior wall was reduced after RT (-16.6% ± 2.3% immediately after RT, -16% ± 2.6% at 8 months, and -16.8% ± 3% at 14 months vs -19% ± 3.5% before RT, P<.05), whereas strain of the inferior wall showed no significant change. No changes were observed with conventional echocardiography. Furthermore, mean TnI levels for the left-sided patients were significantly elevated after RT compared with before RT, whereas TnI levels of the right-sided patients remained unaffected. CONCLUSIONS In contrast to conventional echocardiography, SRI detected a regional, subclinical decline in cardiac function up to 14 months after breast RT. It remains to be determined whether these changes are related to clinical outcome. In the meantime, we encourage the use of radiation techniques that minimize the exposure of the anterior LV wall in left-sided patients.

Biological image-guided radiotherapy in rectal cancer: challenges and pitfalls.

PURPOSE To investigate the feasibility of integrating multiple imaging modalities for image-guided radiotherapy in rectal cancer. PATIENTS AND METHODS Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) were performed before, during, and after preoperative chemoradiotherapy (CRT) in patients with resectable rectal cancer. The FDG-PET signals were segmented with an adaptive threshold-based and a gradient-based method. Magnetic resonance tumor volumes (TVs) were manually delineated. A nonrigid registration algorithm was applied to register the images, and mismatch analyses were carried out between MR and FDG-PET TVs and between TVs over time. Tumor volumes delineated on the images after CRT were compared with the pathologic TV. RESULTS Forty-five FDG-PET/CT and 45 MR images were analyzed from 15 patients. The mean MRI and FDG-PET TVs showed a tendency to shrink during and after CRT. In general, MRI showed larger TVs than FDG-PET. There was an approximately 50% mismatch between the FDG-PET TV and the MRI TV at baseline and during CRT. Sixty-one percent of the FDG-PET TV and 76% of the MRI TV obtained after 10 fractions of CRT remained inside the corresponding baseline TV. On MRI, residual tumor was still suspected in all 6 patients with a pathologic complete response, whereas FDG-PET showed a metabolic complete response in 3 of them. The FDG-PET TVs delineated with the gradient-based method matched closest with pathologic findings. CONCLUSIONS Integration of MRI and FDG-PET into radiotherapy seems feasible. Gradient-based segmentation is recommended for FDG-PET. Spatial variance between MRI and FDG-PET TVs should be taken into account for target definition.

Intrafractional prostate motion during online image guided intensity-modulated radiotherapy for prostate cancer

INTRODUCTION Intrafractional motion consists of two components: (1) the movement between the on-line repositioning procedure and the treatment start and (2) the movement during the treatment delivery. The goal of this study is to estimate this intrafractional movement of the prostate during prostate cancer radiotherapy. MATERIAL AND METHODS Twenty-seven patients with prostate cancer and implanted fiducials underwent a marker match procedure before a five-field IMRT treatment. For all fields, in-treatment images were obtained and then processed to enable automatic marker detection. Combining the subsequent projection images, five positions of each marker were determined using the shortest path approach. The residual set-up error (RSE) after kV-MV based prostate localization, the prostate position as a function of time during a radiotherapy session and the required margins to account for intrafractional motion were determined. RESULTS The mean RSE and standard deviation in the antero-posterior, cranio-caudal and left-right direction were 2.3±1.5 mm, 0.2±1.1 mm and -0.1±1.1 mm, respectively. Almost all motions occurred in the posterior direction before the first treatment beam as the percentage of excursions>5 mm was reduced significantly when the RSE was not accounted for. The required margins for intrafractional motion increased with prolongation of the treatment. Application of a repositioning protocol after every beam could decrease the 1cm margin from CTV to PTV by 2 mm. CONCLUSIONS The RSE is the main contributor to intrafractional motion. This RSE after on-line prostate localization and patient repositioning in the posterior direction emphasizes the need to speed up the marker match procedure. Also, a prostate IMRT treatment should be administered as fast as possible, to ensure that the pre-treatment repositioning efforts are not erased by intrafractional prostate motion. This warrants an optimized workflow with the use of faster treatment techniques.

Fast, accurate, and robust automatic marker detection for motion correction based on oblique kV or MV projection image pairs

PURPOSE A robust and accurate method that allows the automatic detection of fiducial markers in MV and kV projection image pairs is proposed. The method allows to automatically correct for inter or intrafraction motion. METHODS Intratreatment MV projection images are acquired during each of five treatment beams of prostate cancer patients with four implanted fiducial markers. The projection images are first preprocessed using a series of marker enhancing filters. 2D candidate marker locations are generated for each of the filtered projection images and 3D candidate marker locations are reconstructed by pairing candidates in subsequent projection images. The correct marker positions are retrieved in 3D by the minimization of a cost function that combines 2D image intensity and 3D geometric or shape information for the entire marker configuration simultaneously. This optimization problem is solved using dynamic programming such that the globally optimal configuration for all markers is always found. Translational interfraction and intrafraction prostate motion and the required patient repositioning is assessed from the position of the centroid of the detected markers in different MV image pairs. The method was validated on a phantom using CT as ground-truth and on clinical data sets of 16 patients using manual marker annotations as ground-truth. RESULTS The entire setup was confirmed to be accurate to around 1 mm by the phantom measurements. The reproducibility of the manual marker selection was less than 3.5 pixels in the MV images. In patient images, markers were correctly identified in at least 99% of the cases for anterior projection images and 96% of the cases for oblique projection images. The average marker detection accuracy was 1.4 +/- 1.8 pixels in the projection images. The centroid of all four reconstructed marker positions in 3D was positioned within 2 mm of the ground-truth position in 99.73% of all cases. Detecting four markers in a pair of MV images takes a little less than a second where most time is spent on the image preprocessing. CONCLUSIONS The authors have developed a method to automatically detect multiple markers in a pair of projection images that is robust, accurate, and sufficiently fast for clinical use. It can be used for kV, MV, or mixed image pairs and can cope with limited motion between the projection images.

CT characteristics allow identification of patient-specific susceptibility for radiation-induced lung damage

BACKGROUND AND PURPOSE There is a huge difference in radiosensitivity of lungs between patients. The present study aims to identify and quantify patient-specific radiosensitivity based on a single pre-treatment CT scan. MATERIALS AND METHODS 130 lung cancer patients were studied: 60 stereotactic ablative radiotherapy (SABR) treatments and 70 conventional treatments (20 and 30 patients from external datasets, respectively). A 3month-follow-up scan (CT3M) was non-rigidly registered to the planning CT scan (CT0). Changes in Hounsfield Units (ΔHU=HU3M-HU0) inside lung subvolumes were analyzed per dose bin of 5Gy. ΔHU was modeled as a function of local dose using linear and sigmoidal fits. Sigmoidal fit parameters ΔHUmax (saturation level) and D50 (dose corresponding to 50% of ΔHUmax) were collected for all patients. RESULTS Sigmoidal fits outperformed linear fits in the SABR groups for the majority of patients. Sigmoidal dose-responses were also observed in both conventional groups but to a lesser extent. Distributions of D50 and ΔHUmax showed a large variation between patients in all datasets. Higher baseline lung density (p<0.001) was prognostic for higher ΔHUmax in one SABR group. No prognostic factors were found for D50. CONCLUSIONS Baseline CT characteristics are prognostic for radiation-induced lung damage susceptibility.

A semi-automated 2D/3D marker-based registration algorithm modelling prostate shrinkage during radiotherapy for prostate cancer

BACKGROUND AND PURPOSE Currently, most available patient alignment tools based on implanted markers use manual marker matching and rigid registration transformations to measure the needed translational shifts. To quantify the particular effect of prostate gland shrinkage, implanted gold markers were tracked during a course of radiotherapy including an isotropic scaling factor to model prostate shrinkage. MATERIALS AND METHODS Eight patients with prostate cancer had gold markers implanted transrectally and seven were treated with (neo) adjuvant androgen deprivation therapy. After patient alignment to skin tattoos, orthogonal electronic portal images (EPIs) were taken. A semi-automated 2D/3D marker-based registration was performed to calculate the necessary couch shifts. The registration consists of a rigid transformation combined with an isotropic scaling to model prostate shrinkage. RESULTS The inclusion of an isotropic shrinkage model in the registration algorithm cancelled the corresponding increase in registration error. The mean scaling factor was 0.89+/-0.09. For all but two patients, a decrease of the isotropic scaling factor during treatment was observed. However, there was almost no difference in the translation offset between the manual matching of the EPIs to the digitally reconstructed radiographs and the semi-automated 2D/3D registration. A decrease in the intermarker distance was found correlating with prostate shrinkage rather than with random marker migration. CONCLUSIONS Inclusion of shrinkage in the registration process reduces registration errors during a course of radiotherapy. Nevertheless, this did not lead to a clinically significant change in the proposed table translations when compared to translations obtained with manual marker matching without a scaling correction.