Ralf Tetzlaff

In vivo accuracy assessment of a needle-based navigation system for CT-guided radiofrequency ablation of the liver.

Computed tomography (CT)-guided percutaneous radiofrequency ablation (RFA) has become a commonly used procedure in the treatment of liver tumors. One of the main challenges related to the method is the exact placement of the instrument within the lesion. To address this issue, a system was developed for computer-assisted needle placement which uses a set of fiducial needles to compensate for organ motion in real time. The purpose of this study was to assess the accuracy of the system in vivo. Two medical experts with experience in CT-guided interventions and two nonexperts used the navigation system to perform 32 needle insertions into contrasted agar nodules injected into the livers of two ventilated swine. Skin-to-target path planning and real-time needle guidance were based on preinterventional 1 mm CT data slices. The lesions were hit in 97% of all trials with a mean user error of 2.4 +/- 2.1 mm, a mean target registration error (TRE) of 2.1 +/- 1.1 mm, and a mean overall targeting error of 3.7 +/- 2.3 mm. The nonexperts achieved significantly better results than the experts with an overall error of 2.8 +/- 1.4 mm (n=16) compared to 4.5 +/- 2.7 mm (n=16). The mean time for performing four needle insertions based on one preinterventional planning CT was 57 +/- 19 min with a mean setup time of 27 min, which includes the steps fiducial insertion (24 +/- 15 min), planning CT acquisition (1 +/- 0 min), and registration (2 +/- 1 min). The mean time for path planning and targeting was 5 +/- 4 and 2 +/- 1 min, respectively. Apart from the fiducial insertion step, experts and nonexperts performed comparably fast. It is concluded that the system allows for accurate needle placement into hepatic tumors based on one planning CT and could thus enable considerable improvement to the clinical treatment standard for RFA procedures and other CT-guided interventions in the liver. To support clinical application of the method, optimization of individual system modules to reduce intervention time is proposed.

Three-dimensional visualisation improves understanding of surgical liver anatomy

Medical Education 2010: 44: 936–940

Lymph node segmentation on CT images by a shape model guided deformable surface method

With many tumor entities, quantitative assessment of lymph node growth over time is important to make therapy choices or to evaluate new therapies. The clinical standard is to document diameters on transversal slices, which is not the best measure for a volume. We present a new algorithm to segment (metastatic) lymph nodes and evaluate the algorithm with 29 lymph nodes in clinical CT images. The algorithm is based on a deformable surface search, which uses statistical shape models to restrict free deformation. To model lymph nodes, we construct an ellipsoid shape model, which strives for a surface with strong gradients and user-defined gray values. The algorithm is integrated into an application, which also allows interactive correction of the segmentation results. The evaluation shows that the algorithm gives good results in the majority of cases and is comparable to time-consuming manual segmentation. The median volume error was 10.1% of the reference volume before and 6.1% after manual correction. Integrated into an application, it is possible to perform lymph node volumetry for a whole patient within the 10 to 15 minutes time limit imposed by clinical routine.

teaching with cognition: Three‐dimensional visualisation improves understanding of surgical liver anatomy

Medical Education 2010: 44: 936–940

Particle filtering for respiratory motion compensation during navigated bronchoscopy

Although the field of a navigated bronchoscopy gains increasing attention in the literature, robust guidance in the presence of respiratory motion and electromagnetic noise remains challenging. The robustness of a previously introduced motion compensation approach was increased by taking into account the already traveled trajectory of the instrument within the lung. To evaluate the performance of the method a virtual environment, which accounts for respiratory motion and electromagnetic noise was used. The simulation is based on a deformation field computed from human computed tomography data. According to the results, the proposed method outperforms the original method and is suitable for lung motion compensation during electromagnetically guided interventions.

Magnetic resonance-compatible-spirometry: principle, technical evaluation and application

The aim of this study was to assess the feasibility and accuracy of a novel magnetic resonance-compatible (MRc)-spirometer. The influence of body posture, magnetic resonance (MR)-setting and image acquisition on lung function was evaluated. Dynamic MR imaging (dMRI) was compared with simultaneously measured lung function. The development of the MRc-spirometer was based on a commercial spirometer and evaluated by flow-generator measurements and forced expiratory manoeuvres in 34 healthy nonsmokers (17 females and 17 males, mean age 32.9 yrs). Mean differences between forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were calculated and a sample paired t-test and Bland–Altman plots were generated. A total of 11 subjects underwent different subsequent MRc-spirometric measurements to assess the influence of the components of the MR system on lung function. The mean (95% confidence interval) difference of FEV1 and FVC between the two systems was 0.004 (-0.04–0.04) L and 0.018 (-0.05–0.09) L, respectively. In the subgroup analysis, an influence of the MR-system on FEV1 was found. FEV1 correlated well with the dMRI measurement of the apico-diaphragmatic distance-change after the first second of forced expiration (r = 0.72). In conclusion, magnetic resonance-compatible-spirometry is feasible, reliable and safe. The magnetic resonance-setting only has a small influence on simultaneously measured forced expiratory volume in one second. Dynamic magnetic resonance imaging measurements correlate well with simultaneously acquired lung function parameters.

Interactive Surface Correction for 3D Shape Based Segmentation

Statistical shape models have become a fast and robust method for segmentation of anatomical structures in medical image volumes. In clinical practice, however, pathological cases and image artifacts can lead to local deviations of the detected contour from the true object boundary. These deviations have to be corrected manually. We present an intuitively applicable solution for surface interaction based on Gaussian deformation kernels. The method is evaluated by two radiological experts on segmentations of the liver in contrast-enhanced CT images and of the left heart ventricle (LV) in MRI data. For both applications, five datasets are segmented automatically using deformable shape models, and the resulting surfaces are corrected manually. The interactive correction step improves the average surface distance against ground truth from 2.43mm to 2.17mm for the liver, and from 2.71mm to 1.34mm for the LV. We expect this method to raise the acceptance of automatic segmentation methods in clinical application.

On combining internal and external fiducials for liver motion compensation

This paper presents an in-vivo accuracy study on combining skin markers (external fiducials) and fiducial needles (internal fiducials) for motion compensation during liver interventions. We compared the target registration error (TRE) for different numbers of skin markers ns and fiducial needles nf, as well as for different transformation types, in two swine using the tip of an additional tracked needle as the target. During continuous breathing, nf had the greatest effect on the accuracy, yielding mean root mean square (RMS) errors of 4.8 ± 1.1 mm (nf = 0), 2.0 ± 0.9 mm (nf = 1) and 1.7 ± 0.8 mm (nf = 2) when averaged over multiple tool arrangements (n = 18, 36, 18) with ns = 4. These values correspond to error reductions of 11%, 64% and 70%, respectively, compared to the case when no motion compensation is performed, i.e., when the target position is assumed to be constant. At expiration, the mean RMS error ranged from 1.1 mm (nf = 0) to 0.8 mm (nf = 2), which is of the order of magnitude of the target displacement. Our study further indicates that the fiducial registration error (FRE) of a rigid transformation reflecting tissue motion generally correlates strongly with the TRE. Our findings could be used in practice to (1) decide on a suitable combination of fiducials for a given intervention, considering the trade-off between high accuracy and low invasiveness, and (2) provide an intra-interventional measure of confidence for the accuracy of the system based on the FRE.

Evaluation and extension of a navigation system for bronchoscopy inside human lungs

For exact orientation inside the tracheobronchial tree, clinicians are in urgent need of a navigation system for bronchoscopy. Such an image guided system has the ability to show the current position of a bronchoscope (instrument to inspect the inside of the lung) within the tracheobronchial tree. Thus orientation inside the complex tree structure is improved. Our approach of navigated bronchoscopy considers the problem of using a static image to navigate inside a constantly moving soft tissue. It offers a direct guidance to a preinterventionally defined target inside the bronchial tree to save intervention time spent on searching the right path and to minimize the duration of anesthesia. It is designed to adapt to the breathing cycle of the patient, so no further intervention to minimize the movement of the lung has to stress the patient. We present a newly developed navigation sensor with allows to display a virtual bronchoscopy in real time and we demonstrate an evaluation on the accuracy within a non moving ex vivo lung phantom.

An electromagnetic navigation system for transbronchial interventions with a novel approach to respiratory motion compensation

PURPOSE Bronchoscopic interventions, such as transbronchial needle aspiration (TBNA), are commonly performed procedures to diagnose and stage lung cancer. However, due to the complex structure of the lung, one of the main challenges is to find the exact position to perform a biopsy and to actually hit the biopsy target (e.g., a lesion). Today, most interventions are accompanied by fluoroscopy to verify the position of the biopsy instrument, which means additional radiation exposure for the patient and the medical staff. Furthermore, the diagnostic yield of TBNA is particularly low for peripheral lesions. METHODS To overcome these problems the authors developed an image-guided, electromagnetic navigation system for transbronchial interventions. The system provides real time positioning information for the bronchoscope and a transbronchial biopsy instrument with only one preoperatively acquired computed tomography image. A twofold respiratory motion compensation method based on a particle filtering approach allows for guidance through the entire respiratory cycle. In order to evaluate our system, 18 transbronchial interventions were performed in seven ventilated swine lungs using a thorax phantom. RESULTS All tracked bronchoscope positions were corrected to the inside of the tracheobronchial tree and 80.2% matched the correct bronchus. During regular respiratory motion, the mean overall targeting error for bronchoscope tracking and TBNA needle tracking was with compensation on 10.4 ± 1.7 and 10.8 ± 3.0 mm, compared to 14.4 ± 1.9 and 13.3 ± 2.7 mm with compensation off. The mean fiducial registration error (FRE) was 4.2 ± 1.1 mm. CONCLUSIONS The navigation system with the proposed respiratory motion compensation method allows for real time guidance during bronchoscopic interventions, and thus could increase the diagnostic yield of transbronchial biopsy.