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Lennert S Ploeger

Publications and source records attributed to Lennert S Ploeger.

11 recordsLinked to original sources
PubMed2007

Discrimination between benign and malignant prostate tissue using chromatin texture analysis in 3-D by confocal laser scanning microscopy.

BACKGROUND: Analysis of chromatin texture may improve both the diagnosis and the assessment of the prognosis of prostate cancer. Confocal laser scanning microscopy (CLSM) allows performing measurements in nuclei reconstructed in 3-D. The aim of this study was to evaluate the clinical usefulness of 3-D texture analysis of prostate tissue. METHODS: Image stacks of eight prostate cancer sections were obtained by CLSM of both benign and malignant areas. Texture feature values were computed for individual nuclei. The discriminative power of the texture features was established by receiver operating characteristic (ROC) analysis and linear discriminant analysis (LDA). RESULTS: Texture features were identified that could discriminate between benign and malignant nuclei. LDA correctly classified 89% of the nuclei of the pooled set of benign and malignant nuclei. CONCLUSIONS: 3-D nuclear texture features allow discrimination of most benign and malignant prostate nuclei. We estimate that the classification rates can be increased by improving the image quality.

Adenocarcinoma↗
PubMed2005

Implementation of accurate and fast DNA cytometry by confocal microscopy in 3D.

BACKGROUND: DNA cytometry is a powerful method for measuring genomic instability. Standard approaches that measure DNA content of isolated cells may induce selection bias and do not allow interpretation of genomic instability in the context of the tissue. Confocal Laser Scanning Microscopy (CLSM) provides the opportunity to perform 3D DNA content measurements on intact cells in thick histological sections. Because the technique is technically challenging and time consuming, only a small number of usually manually selected nuclei were analyzed in different studies, not allowing wide clinical evaluation. The aim of this study was to describe the conditions for accurate and fast 3D CLSM cytometry with a minimum of user interaction to arrive at sufficient throughput for pilot clinical applications. METHODS: Nuclear DNA was stained in 14 microm thick tissue sections of normal liver and adrenal stained with either YOYO-1 iodide or TO-PRO-3 iodide. Different pre-treatment strategies were evaluated: boiling in citrate buffer (pH 6.0) followed by RNase application for 1 or 18 hours, or hydrolysis. The image stacks obtained with CLSM at microscope magnifications of x40 or x100 were analyzed off-line using in-house developed software for semi-automated 3D fluorescence quantitation. To avoid sectioned nuclei, the top and bottom of the stacks were identified from ZX and YZ projections. As a measure of histogram quality, the coefficient of variation (CV) of the diploid peak was assessed. RESULTS: The lowest CV (10.3%) was achieved with a protocol without boiling, with 1 hour RNase treatment and TO-PRO-3 iodide staining, and a final image recording at x60 or x100 magnifications. A sample size of 300 nuclei was generally achievable. By filtering the set of automatically segmented nuclei based on volume, size and shape, followed by interactive removal of the few remaining faulty objects, a single measurement was completely analyzed in approximately 3 hours. CONCLUSIONS: The described methodology allows to obtain a largely unbiased sample of nuclei in thick tissue sections using 3D DNA cytometry by confocal laser scanning microscopy within an acceptable time frame for pilot clinical applications, and with a CV small enough to resolve smaller near diploid stemlines. This provides a suitable method for 3D DNA ploidy assessment of selected rare cells based on morphologic characteristics and of clinical samples that are too small to prepare adequate cell suspensions.

Adrenal Glands↗
PubMed2005

Development of 3D chromatin texture analysis using confocal laser scanning microscopy.

INTRODUCTION: Analysis of nuclear texture features as a measure of nuclear chromatin changes has been proven to be useful when measured on thin (5-6 microm) tissue sections using conventional 2D bright field microscopy. The drawback of this approach is that most nuclei are not intact because of those thin sections. Confocal laser scanning microscopy (CLSM) allows measurements of texture in 3D reconstructed nuclei. The aim of this study was to develop 3D texture features that quantitatively describe changes in chromatin architecture associated with malignancy using CLSM images. METHODS: Thirty-five features thoughtfully chosen from 4 categories of 3D texture features (discrete texture features, Markovian features, fractal features, grey value distribution features) were selected and tested for invariance properties (rotation and scaling) using artificial images with a known grey value distribution. The discriminative power of the 3D texture features was tested on artificially constructed benign and malignant 3D nuclei with increasing nucleolar size and advancing chromatin margination towards the periphery of the nucleus. As a clinical proof of principle, the discriminative power of the texture features was assessed on 10 benign and 10 malignant human prostate nuclei, evaluating also whether there was more texture information in 3D whole nuclei compared to a single 2D plane from the middle of the nucleus. RESULTS: All texture features showed the expected invariance properties. Almost all features were sensitive to variations in the nucleolar size and to the degree of margination of chromatin. Fourteen texture features from different categories had high discriminative power for separating the benign and malignant nuclei. The discrete texture features performed less than expected. There was more information on nuclear texture in 3D than in 2D. CONCLUSION: A set of 35 3D nuclear texture features was used successfully to assess nuclear chromatin patterns in 3D images obtained by confocal laser scanning microscopy, and as a proof of principle we showed that these features may be clinically useful for analysis of prostate neoplasia.

Cell Nucleus↗
PubMed2004

Leaf trajectory verification during dynamic intensity modulated radiotherapy using an amorphous silicon flat panel imager.

An independent verification of the leaf trajectories during each treatment fraction improves the safety of IMRT delivery. In order to verify dynamic IMRT with an electronic portal imaging device (EPID), the EPID response should be accurate and fast such that the effect of motion blurring on the detected moving field edge position is limited. In the past, it was shown that the errors in the detected position of a moving field edge determined by a scanning liquid-filled ionization chamber (SLIC) EPID are negligible in clinical practice. Furthermore, a method for leaf trajectory verification during dynamic IMRT was successfully applied using such an EPID. EPIDs based on amorphous silicon (a-Si) arrays are now widely available. Such a-Si flat panel imagers (FPIs) produce portal images with superior image quality compared to other portal imaging systems, but they have not yet been used for leaf trajectory verification during dynamic IMRT. The aim of this study is to quantify the effect of motion distortion and motion blurring on the detection accuracy of a moving field edge for an Elekta iViewGT a-Si FPI and to investigate its applicability for the leaf trajectory verification during dynamic IMRT. We found that the detection error for a moving field edge to be smaller than 0.025 cm at a speed of 0.8 cm/s. Hence, the effect of motion blurring on the detection accuracy of a moving field edge is negligible in clinical practice. Furthermore, the a-Si FPI was successfully applied for the verification of dynamic IMRT. The verification method revealed a delay in the control system of the experimental DMLC that was also found using a SLIC EPID, resulting in leaf positional errors of 0.7 cm at a leaf speed of 0.8 cm/s.

Algorithms↗
PubMed2004

Confocal 3D DNA cytometry: assessment of required coefficient of variation by computer simulation.

BACKGROUND: Confocal Laser Scanning Microscopy (CLSM) provides the opportunity to perform 3D DNA content measurements on intact cells in thick histological sections. So far, sample size has been limited by the time consuming nature of the technology. Since the power of DNA histograms to resolve different stemlines depends on both the sample size and the coefficient of variation (CV) of histogram peaks, interpretation of 3D CLSM DNA histograms might be hampered by both a small sample size and a large CV. The aim of this study was to analyze the required CV for 3D CLSM DNA histograms given a realistic sample size. METHODS: By computer simulation, virtual histograms were composed for sample sizes of 20000, 10000, 5000, 1000, and 273 cells and CVs of 30, 25, 20, 15, 10 and 5%. By visual inspection, the histogram quality with respect to resolution of G0/1 and G2/M peaks of a diploid stemline was assessed. RESULTS: As expected, the interpretability of DNA histograms deteriorated with decreasing sample sizes and higher CVs. For CVs of 15% and lower, a clearly bimodal peak pattern with well distinguishable G0/1 and G2/M peaks were still seen at a sample size of 273 cells, which is our current average sample size with 3D CLSM DNA cytometry. CONCLUSIONS: For unambiguous interpretation of DNA histograms obtained using 3D CLSM, a CV of at most 15% is tolerable at currently achievable sample sizes. To resolve smaller near diploid stemlines, a CV of 10% or better should be aimed at. With currently available 3D imaging technology, this CV is achievable.

Computer Simulation↗
PubMed2003

Feasibility of geometrical verification of patient set-up using body contours and computed tomography data.

BACKGROUND AND PURPOSE: Body contours can potentially be used for patient set-up verification in external-beam radiotherapy and might enable more accurate set-up of patients prior to irradiation. The aim of this study is to test the feasibility of patient set-up verification using a body contour scanner. MATERIAL AND METHODS: Body contour scans of 33 lung cancer and 21 head-and-neck cancer patients were acquired on a simulator. We assume that this dataset is representative for the patient set-up on an accelerator. Shortly before acquisition of the body contour scan, a pair of orthogonal simulator images was taken as a reference. Both the body contour scan and the simulator images were matched in 3D to the planning computed tomography scan. Movement of skin with respect to bone was quantified based on an analysis of variance method. RESULTS: Set-up errors determined with body-contours agreed reasonably well with those determined with simulator images. For the lung cancer patients, the average set-up errors (mm)+/-1 standard deviation (SD) for the left-right, cranio-caudal and anterior-posterior directions were 1.2+/-2.9, -0.8+/-5.0 and -2.3+/-3.1 using body contours, compared to -0.8+/-3.2, -1.0+/-4.1 and -1.2+/-2.4 using simulator images. For the head-and-neck cancer patients, the set-up errors were 0.5+/-1.8, 0.5+/-2.7 and -2.2+/-1.8 using body contours compared to -0.4+/-1.2, 0.1+/-2.1, -0.1+/-1.8 using simulator images. The SD of the set-up errors obtained from analysis of the body contours were not significantly different from those obtained from analysis of the simulator images. Movement of the skin with respect to bone (1 SD) was estimated at 2.3 mm for lung cancer patients and 1.7 mm for head-and-neck cancer patients. CONCLUSION: Measurement of patient set-up using a body-contouring device is possible. The accuracy, however, is limited by the movement of the skin with respect to the bone. In situations where the error in the patient set-up is relatively large, it is possible to reduce these errors using a computer-aided set-up technique based on contour information.

Computer Simulation↗
PubMed2003

Application of video imaging for improvement of patient set-up.

BACKGROUND AND PURPOSE: For radiotherapy of prostate cancer, the patient is usually positioned in the left-right (LR) direction by aligning a single marker on the skin with the projection of a room laser. The aim of this study is to investigate the feasibility of a room-mounted video camera in combination with previously acquired CT data to improve patient set-up along the LR axis. MATERIAL AND METHODS: The camera was mounted in the treatment room at the caudal side of the patient. For 22 patients with prostate cancer 127 video and portal images were acquired. The set-up error determined by video imaging was found by matching video images with rendered CT images using various techniques. This set-up error was retrospectively compared with the set-up error derived from portal images. It was investigated whether the number of corrections based on portal imaging would decrease if the information obtained from the video images had been used prior to irradiation. Movement of the skin with respect to bone was quantified using an analysis of variance method. RESULTS: The measurement of the set-up error was most accurate for a technique where outlines and groins on the left and right side of the patient were delineated and aligned individually to the corresponding features extracted from the rendered CT image. The standard deviations (SD) of the systematic and random components of the set-up errors derived from the portal images in the LR direction were 1.5 and 2.1 mm, respectively. When the set-up of the patients was retrospectively adjusted based on the video images, the SD of the systematic and random errors decreased to 1.1 and 1.3 mm, respectively. From retrospective analysis, a reduction of the number of set-up corrections (from nine to six corrections) is expected when the set-up would have been adjusted using the video images. The SD of the magnitude of motion of the skin of the patient with respect to the bony anatomy was estimated to be 1.1 mm. CONCLUSION: Video imaging is an accurate technique for measuring the set-up of prostate cancer patients in the LR direction. The outline of the patient is a more accurate estimate of the set-up of the bony anatomy than the marker on the patient's abdomen.

Analysis of Variance↗
PubMed2003

Evaluation of cost functions for gray value matching of two-dimensional images in radiotherapy.

In external beam radiotherapy, portal imaging is applied for verification of the patient setup. Current automatic methods for portal image registration, which are often based on segmentation of anatomical structures, are especially successful for images of the pelvic region. For portal images of more complicated anatomical structures, e.g., lung, these techniques are less successful. It is desirable to have a method for image registration that is applicable for a wide range of treatment sites. In this study, a registration method for two-dimensional (2D) registration of portal and reference images based on intensity values was tested on portal images of various anatomical sites. Tests were performed with and without preprocessing (unsharp mask filtering followed by histogram equalization) for 96 image pairs and six cost functions. The images were obtained from treatments of the rectum, salivary gland, brain, prostate, and lung. To get insight into the behavior of the various cost functions, cost function values were computed for each portal image for 20,000 transformations of the corresponding reference image, translating the reference image in a range of +/- 1 cm and rotating +/- 10 degrees with respect to the clinical match. The automatic match was defined as the transformation associated with the global minimum (found by an exhaustive search). Without preprocessing, the registration reliability was low (less than 27%). With preprocessing, about 90% of the matches were successful, with a difference with our gold standard (manual registration) of about 1 mm and 1 degree SD. All tested cost functions performed similarly. However, the number of local minima using mutual information was larger than for the other tested cost functions. A cost function based on the mean product of the corresponding pixel values had the least number of local minima. In conclusion, gray value based registration of portal images is applicable for a wide range of treatment sites. However, pre-processing of the images is essential.

Algorithms↗
PubMed2002

Confocal DNA cytometry: a contour-based segmentation algorithm for automated three-dimensional image segmentation.

BACKGROUND: Confocal laser scanning microscopy (CLSM) presents the opportunity to perform three-dimensional (3D) DNA content measurements on intact cells in thick histological sections. So far, these measurements have been performed manually, which is quite time-consuming. METHODS: In this study, an intuitive contour-based segmentation algorithm for automatic 3D CLSM image cytometry of nuclei in thick histological sections is presented. To evaluate the segmentation algorithm, we measured the DNA content and volume of human liver and breast cancer nuclei in 3D CLSM images. RESULTS: A high percentage of nuclei could be segmented fully automatically (e.g., human liver, 92%). Comparison with (time-consuming) interactive measurements on the same CLSM images showed that the results were well correlated (liver, r = 1.00; breast, r = 0.92). CONCLUSIONS: Automatic 3D CLSM image cytometry enables measurement of volume and DNA content of large numbers of nuclei in thick histological sections within an acceptable time. This makes large-scale studies feasible, whereby the advantages of CLSM can be exploited fully. The intuitive modular segmentation algorithm presented in this study detects and separates overlapping objects, also in two-dimensional (2D) space. Therefore, this algorithm may also be suitable for other applications.

Algorithms↗
PubMed2002

A method for geometrical verification of dynamic intensity modulated radiotherapy using a scanning electronic portal imaging device.

In order to guarantee the safe delivery of dynamic intensity modulated radiotherapy (IMRT), verification of the leaf trajectories during the treatment is necessary. Our aim in this study is to develop a method for on-line verification of leaf trajectories using an electronic portal imaging device with scanning read-out, independent of the multileaf collimator. Examples of such scanning imagers are electronic portal imaging devices (EPIDs) based on liquid-filled ionization chambers and those based on amorphous silicon. Portal images were acquired continuously with a liquid-filled ionization chamber EPID during the delivery, together with the signal of treatment progress that is generated by the accelerator. For each portal image, the prescribed leaf and diaphragm positions were computed from the dynamic prescription and the progress information. Motion distortion effects of the leaves are corrected based on the treatment progress that is recorded for each image row. The aperture formed by the prescribed leaves and diaphragms is used as the reference field edge, while the actual field edge is found using a maximum-gradient edge detector. The errors in leaf and diaphragm position are found from the deviations between the reference field edge and the detected field edge. Earlier measurements of the dynamic EPID response show that the accuracy of the detected field edge is better than 1 mm. To ensure that the verification is independent of inaccuracies in the acquired progress signal, the signal was checked with diode measurements beforehand. The method was tested on three different dynamic prescriptions. Using the described method, we correctly reproduced the distorted field edges. Verifying a single portal image took 0.1 s on an 866 MHz personal computer. Two flaws in the control system of our experimental dynamic multileaf collimator were correctly revealed with our method. First, the errors in leaf position increase with leaf speed, indicating a delay of approximately 0.8 s in the control system. Second, the accuracy of the leaves and diaphragms depends on the direction of motion. In conclusion, the described verification method is suitable for detailed verification of leaf trajectories during dynamic IMRT.

Algorithms↗