Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

A Neuromonitoring Approach to Facial Nerve Preservation During Image-guided Robotic Cochlear Implantation.

HYPOTHESIS A multielectrode probe in combination with an optimized stimulation protocol could provide sufficient sensitivity and specificity to act as an effective safety mechanism for preservation of the facial nerve in case of an unsafe drill distance during image-guided cochlear implantation. BACKGROUND A minimally invasive cochlear implantation is enabled by image-guided and robotic-assisted drilling of an access tunnel to the middle ear cavity. The approach requires the drill to pass at distances below 1 mm from the facial nerve and thus safety mechanisms for protecting this critical structure are required. Neuromonitoring is currently used to determine facial nerve proximity in mastoidectomy but lacks sensitivity and specificity necessaries to effectively distinguish the close distance ranges experienced in the minimally invasive approach, possibly because of current shunting of uninsulated stimulating drilling tools in the drill tunnel and because of nonoptimized stimulation parameters. To this end, we propose an advanced neuromonitoring approach using varying levels of stimulation parameters together with an integrated bipolar and monopolar stimulating probe. MATERIALS AND METHODS An in vivo study (sheep model) was conducted in which measurements at specifically planned and navigated lateral distances from the facial nerve were performed to determine if specific sets of stimulation parameters in combination with the proposed neuromonitoring system could reliably detect an imminent collision with the facial nerve. For the accurate positioning of the neuromonitoring probe, a dedicated robotic system for image-guided cochlear implantation was used and drilling accuracy was corrected on postoperative microcomputed tomographic images. RESULTS From 29 trajectories analyzed in five different subjects, a correlation between stimulus threshold and drill-to-facial nerve distance was found in trajectories colliding with the facial nerve (distance <0.1 mm). The shortest pulse duration that provided the highest linear correlation between stimulation intensity and drill-to-facial nerve distance was 250 μs. Only at low stimulus intensity values (≤0.3 mA) and with the bipolar configurations of the probe did the neuromonitoring system enable sufficient lateral specificity (>95%) at distances to the facial nerve below 0.5 mm. However, reduction in stimulus threshold to 0.3 mA or lower resulted in a decrease of facial nerve distance detection range below 0.1 mm (>95% sensitivity). Subsequent histopathology follow-up of three representative cases where the neuromonitoring system could reliably detect a collision with the facial nerve (distance <0.1 mm) revealed either mild or inexistent damage to the nerve fascicles. CONCLUSION Our findings suggest that although no general correlation between facial nerve distance and stimulation threshold existed, possibly because of variances in patient-specific anatomy, correlations at very close distances to the facial nerve and high levels of specificity would enable a binary response warning system to be developed using the proposed probe at low stimulation currents.

A Novel Ultrasound-Based Registration for Image-Guided Laparoscopic Liver Ablation.

BACKGROUND Patient-to-image registration is a core process of image-guided surgery (IGS) systems. We present a novel registration approach for application in laparoscopic liver surgery, which reconstructs in real time an intraoperative volume of the underlying intrahepatic vessels through an ultrasound (US) sweep process. METHODS An existing IGS system for an open liver procedure was adapted, with suitable instrument tracking for laparoscopic equipment. Registration accuracy was evaluated on a realistic phantom by computing the target registration error (TRE) for 5 intrahepatic tumors. The registration work flow was evaluated by computing the time required for performing the registration. Additionally, a scheme for intraoperative accuracy assessment by visual overlay of the US image with preoperative image data was evaluated. RESULTS The proposed registration method achieved an average TRE of 7.2 mm in the left lobe and 9.7 mm in the right lobe. The average time required for performing the registration was 12 minutes. A positive correlation was found between the intraoperative accuracy assessment and the obtained TREs. CONCLUSIONS The registration accuracy of the proposed method is adequate for laparoscopic intrahepatic tumor targeting. The presented approach is feasible and fast and may, therefore, not be disruptive to the current surgical work flow.

Body image rating scales to assess obesity

Obesity prevalence in the U.S. has increased during the last three decades with major impact on public health. Screening for obesity in a population with unknown weight status can be time- and resource-consuming, but the information is valuable for prioritizing and allocating scarce resources. The challenge remains to properly assess obesity with the available methods. Body Image Rating Scales (BIRS) have initially been developed to assess body image disturbances, but also seem useful as an alternative method in assessing obesity prevalence. Several different BIRS exists. In this project I reviewed the literature that exists regarding the use of BIRS, and its advantages and limitations for the assessment of obesity status with regards to BMI. The result yielded nine publications that examined eight different scales and their correlation with BMI, ranging from r=.59 for self-reported BMI to r=.94 for measured BMI. One concern is the lack of standardization of this method to assess obesity, given the range of different scales. While many methods for obesity assessment are available, the simplicity, ease of use and cost-effectiveness of BIRS make it very appealing. BIRS remain a potentially attractive option to assess the weight status of a large population with minimal requirements in assets and time, especially in situations where measuring instruments are not available, or when height or weight could not be recalled.^

Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction

Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.

A dual resonance, image -guided, volume localization technique for magnetic resonance spectroscopy

An interleaved, dual resonance, volume localization technique for $\sp1$H/$\sp{31}$P magnetic resonance spectroscopy has been designed, implemented on a 2 T imager/spectrometer, and verified with phantom studies.^ Localization techniques, including several single voxel techniques and spectroscopic imaging, were implemented, and studies were performed to compare the efficiency of each sequence of $\sp1$H/$\sp{31}$P spectral acquisitions. The sequence chosen was a hybrid of the stimulated echo single voxel technique and the spectroscopic imaging technique.^ Water suppression during the $\sp1$H spectral acquisitions was accomplished by the use of three narrow bandwidth RF saturation pulses in combination with three spoiler gradients. The spoiler gradient amplitudes were selected on the basis of a numerical solution of the Bloch equations. A post-acquisition water suppression algorithm was used to minimize any residual water signal.^ For interleaved $\sp1$H/$\sp{31}$P acquisitions, a dual resonance RF coil was constructed and interfaced to the existing RF detection system via a custom-designed dual resonance transcoupler and switching system. Programmable attenuators were incorporated to allow for changes in receiver and transmitter attenuation "on the fly".^ To provide the rapidly switched gradient fields required for the $\sp1$H/$\sp{31}$P acquisitions, an actively screened gradient coil system was designed and implemented. With this system, gradient field rise times on the order of 100 $\mu$s were obtained. These rapid switching times were necessary for minimizing intrasequence delays and for improving localization quality and water suppression efficiency.^ The interleaved $\sp1$H/$\sp{31}$P volume localization technique was tested using a two-compartment phantom. Analysis of the data showed that the spectral contamination was less than three percent. One-to-one spatial correspondence of the $\sp1$H and $\sp{31}$P spectra was verified and allowed for direct correlation of the spectral data with a standard magnetic resonance image. ^