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Biomedical subjects

H J Huisman

Publications and source records attributed to H J Huisman.

9 recordsLinked to original sources
PubMed2004

Accuracy of rigid CT-FDG-PET image registration of the liver.

Diagnostic and surgical strategies could benefit from accurate localization of liver malignancies via CT-FDG-PET image registration. However, registration uncertainty occurs due to protocol differences in data-acquisition, the limited spatial resolution of positron emission tomography (PET) and the low uptake of 18F-fluorodeoxyglucose (FDG) in normal liver tissue. To assess this uncertainty, methods were presented to estimate registration precision and systematic bias. A semi-automatic, organ-focused method was investigated to minimize the uncertainty well beyond the typical uncertainty of 5-10 mm obtained by commonly available methods. By restricting registration to the liver region and by isolating the liver on computed tomography (CT) from surrounding structures using a thresholding technique, registration was achieved using the mutual information-based method as implemented in insight toolkit (ITK). CT and FDG-PET images of 10 patients with liver metastases were registered rigidly a number of times. Results of the organ-focused method were compared to results of three commonly available methods (a manual, a landmark-based and a 'standard' mutual information-based method) where no dedicated image processing was performed. The proposed method outperformed the other methods with a precision (mean+/-s.d.) of 2.5+/-1.3 mm and a bias of 1.9 mm with a 95% CI of [1.0, 2.8] mm. Unlike the commonly available methods, our approach allows for robust CT-FDG-PET registration of the liver, with an accuracy better than the spatial resolution of the PET scanner that was used.

Fluorodeoxyglucose F18↗
PubMed2001

Post-radiotherapy contrast enhancement changes in fast dynamic MRI of cervical carcinoma.

This pilot study determines fast dynamic gadolinium enhanced MRI contrast enhancement parameters (onset of enhancement and time to peak enhancement) before and after radiotherapy in 10 cervical carcinoma patients. Before radiotherapy, onset of enhancement and time to peak enhancement were early, with a median of 4.5 and 5.2 seconds, respectively. High-grade tumors showed early enhancement, compared with low-grade. After radiotherapy, contrast enhancement patterns differed. In survivors, onset of enhancement after radiotherapy was later than before radiotherapy. In non-survivors, onset of enhancement after radiotherapy was still early. The median difference in onset of enhancement before and after radiotherapy in survivors and non-survivors was an increase of 3.2 and a decrease of 1.1 seconds, respectively. Early onset of enhancement after radiotherapy was a better predictor for survival than a high-signal intensity zone on post radiotherapy unenhanced T1/T2-weighted MRI. It is concluded that enhancement parameters from fast dynamic Gd-enhanced MR images can provide additional functional information with regard to tumor vascularization, and may have prognostic significance. It complements clinical examination and unenhanced MRI in determining the effectiveness of radiotherapy treatment in cervical carcinoma. Future studies will focus on the clinical utility and improvements of the estimation of contrast-enhanced parameters with this new technique.

Contrast Media↗
PubMed2001

Accurate estimation of pharmacokinetic contrast-enhanced dynamic MRI parameters of the prostate.

Quantitative analysis of contrast-enhanced dynamic MR images has potential for diagnosing prostate cancer. Contemporary fast acquisition techniques can give sufficiently high temporal resolution to sample the fast dynamics observed in the prostate. Data reduction for parametric visualization requires automatic curve fitting to a pharmacokinetic model, which to date has been performed using least-squares error minimization methods. We observed that these methods often produce unexpectedly noisy estimates, especially for the typically fast, intermediate parameters time-to-peak and start-of-enhancement, resulting in inaccurate pharmacokinetic parameter estimates. We developed a new curve fit method that focuses on the most probable slope. A set of 10 patients annotated using histopathology was used to compare the conventional and new methods. The results show that our new method is significantly more accurate, especially in the relatively less-enhancing peripheral zone. We conclude that estimation accuracy depends on the curve fit method, which is especially important when evaluating the peripheral zone of the prostate.

Aged↗
PubMed1999

Fast dynamic gadolinium-enhanced MR imaging of urinary bladder and prostate cancer.

Among the noninvasive imaging modalities, contrast enhanced magnetic resonance (MR) imaging is the most powerful tool with which to visualize vascularity. Common pathology only shows microvessel density, whereas dynamic MR imaging is sensitive to the total endothelial surface area of perfused vessels. Therefore, dynamic MR imaging may be of additional value in tumor staging and in evaluating therapies that affect the perfused microvessel density or surface area, such as chemo-, radiation, or anti-angiogenic therapy. In urinary bladder cancer, this technique results in improved local and nodal staging, in improved separation of transurethral granulation tissue and edema from malignant tumor, and in improved evaluation of the effect of chemotherapy. In prostate cancer, dynamic MR imaging may be of help in problematic cases. This technique can assist in determining seminal vesicle infiltration, in depicting of minimal capsular penetration, and in recognizing tumors within the transitional zone. Also, based on very rapid enhancement, very poorly differentiated tumors can be recognized. Evaluation of the effects of therapy is another promising area, however a lot of research remain to be done. This article reviews some basics of fast enhancement techniques, provides practical information, and shows recent developments, in using these fast techniques for staging and grading of bladder and prostate cancer, and for evaluating the effect of therapy.

Contrast Media↗
PubMed1998

Quantitative ultrasonic analysis of liver metastases.

The performance of five features of ultrasonic tissue characterization (UTC) of metastases in vivo in liver was investigated. We acquired serial radiofrequency data sets of 12 patients with metastases in the liver from adenocarcinoma of the colon. Parenchyma and metastases UTC features were estimated in semiautomatically segmented regions. Over 200 metastases were measured in patients and 43 dummy metastases in healthy volunteers. Two attenuation features could be estimated in only 15% of the metastases, and these were not different from those in parenchyma. The texture features signal-to-noise ratio (SNR) could not discriminate real from dummy metastases. Average backscatter intensity, b0, is an established discriminative echographic image feature. However, the metastases that were hypoechoic relative to surrounding parenchyma appeared to be isoechoic relative to normal liver parenchyma. They were visible because of an increased b0 in the surrounding liver parenchyma. Finally, we found an increased backscatter coefficient slope vs. frequency in hypoechoic metastases that may predict a deterioration of lesion contrast at higher transducer frequencies. We conclude that the backscatter coefficient slope can improve detection of metastases, and that b0 measured relative to normal liver parenchyma should be used to correctly correlate metastasis echography with histology.

Acoustics↗
PubMed1998

Adaptive texture feature extraction with application to ultrasonic image analysis.

Computer texture analysis methods use texture features that are traditionally chosen from a large set of fixed features known in literature. These fixed features are often not specifically designed to the problem at hand, and as a result they may have low discriminative power, and/or may be correlated. Increasing the number of selected fixed features is statistically not a good solution in limited data environments such as medical imaging. For that reason, we developed an adaptive texture feature extraction method (ATFE) that extracts a small number of features that are tuned to the problem at hand. By using a feed-forward neutral network, we ensure that even nonlinear relations are captured from the data. Using extensive, repeated synthetic ultrasonic images, we compared the performance of ATFE with the optimal feature set. We show that the ATFE method is capable of robust operation on small data sets with a performance close to that of the optimal feature set. Another experiment confirms that our ATFE is capable of capturing nonlinear relations from the dataset. We conclude that our method can improve performance in practical, limited dataset situations where an optimal fixed feature set can be hard to find.

Artificial Intelligence↗
PubMed1996

Precision and accuracy of acoustospectrographic parameters.

Theoretical estimates of the standard deviation (STD) of four acoustospectrographic parameters (the intercept and slope of attenuation and backscatter coefficient) are derived. This derivation expands and corrects existing derivations, and is confirmed using simulations based on the adopted theoretical model. A robust parameter estimation method is applied to various phantom measurements, and to in vivo liver scans of healthy human subjects. The measured STD is higher than the theoretically predicted value, and we investigated four possible factors which explain this discrepancy. First, it is shown that the STD and bias after spectrogram calculation are rather insensitive to changes in windowing function, type, length and overlap. Second, we observed that a diffraction correction spectrogram calibrated on a medium different from the one being measured insufficiently corrects the depth-dependency of the parameters, which affects both precision as well as accuracy. We therefore propose a method that constructs an organ-specific diffraction correction spectrogram from the averaged spectrogram of a set of normal organs. We show that the organ-specific correction does not affect STD even in case of previously unseen acquisitions. Third, we introduce local inhomogeneity, which predicts excess STD due to local variations of the physical parameters within an organ (i.e., intrasubject), and global inhomogeneity, which predicts variations between organs (i.e., intersubject). We conclude that our method of estimating STD predicts normal, in vivo data very well, and propose that the deviation from these estimates is a potential tissue characterization parameter.

Humans↗
PubMed1994

Fast scan conversion algorithms for displaying ultrasound sector images.

Two fast algorithms for interpolation of ultrasonic sector-scans were developed. Both algorithms are based on line-drawing algorithms and are free from multiplications in the innermost loops. The algorithms were compared to the following conventional interpolators: 2-D windowed sinc, bicubic spline, 4 x 4 point bicubic spline, bilinear, and nearest neighbor. The most accurate of the two new algorithms is about eight times faster than nearest neighbor interpolation. The quantitative errors are of the same order as the errors of the nearest neighbor interpolator. The subjective image quality is between nearest neighbor and bilinear interpolation.

Algorithms↗