Hypothesis Suboptimal cochlear implant (CI) electrode array placement may reduce presentation of coded information to the central nervous system and consequently limit speech recognition. Background Generally, mean speech reception scores for CI recipients are similar across different CI systems, yet large outcome variation is observed among recipients implanted with the same device. These observations suggest significant recipient-dependent factors influence speech reception performance. This study examines electrode array insertion depth and scalar placement as recipient-dependent factors affecting outcome. Methods Scalar location and depth of insertion of intracochlear electrodes were measured in 14 patients implanted with Advanced Bionics electrode arrays and whose word recognition scores varied broadly. Electrode position was measured using computed tomographic images of the cochlea and correlated with stable monosyllabic word recognition scores. Results Electrode placement, primarily in terms of depth of insertion and scala tympani vs. scala vestibuli location, varies widely across subjects. Lower outcome scores are associated with greater insertion depth and greater number of contacts being located in scala vestibuli. Three patterns of scalar placement are observed suggesting variability in insertion dynamics arising from surgical technique. Conclusion A significant portion of variability in word recognition scores across a broad range of performance levels of CI subjects is explained by variability in scalar location and insertion depth of the electrode array. We suggest that this variability in electrode placement can be reduced and average speech reception improved by better selection of cochleostomy sites, revised insertion approaches, and control of insertion depth during surgical placement of the array.

Breathing motion is a significant source of error in radiotherapy treatment planning for the thorax and upper abdomen. Accounting for breathing motion has a profound effect on the size of conformal radiation portals employed in these sites. Breathing motion also causes artifacts and distortions in treatment planning computed tomography (CT) scans acquired during free breathing and also causes a breakdown of the assumption of the superposition of radiation portals in intensity-modulated radiation therapy, possibly leading to significant dose delivery errors. Proposed voluntary and involuntary breath-hold techniques have the potential for reducing or eliminating the effects of breathing motion, however, they are limited in practice, by the fact that many lung cancer patients cannot tolerate holding their breath. We present an alternative solution to accounting for breathing motion in radiotherapy treatment planning, where multislice CT scans are collected simultaneously with digital spirometry over many free breathing cycles to create a four-dimensional (4-D) image set, where tidal lung volume is the additional dimension. An analysis of this 4-D data leads to methods for digital-spirometry, based elimination or accounting of breathing motion artifacts in radiotherapy treatment planning for free breathing patients. The 4-D image set is generated by sorting free-breathing multislice CT scans according to user-defined tidal-volume bins. A multislice CT scanner is operated in the ciné mode, acquiring 15 scans per couch position, while the patient undergoes simultaneous digital-spirometry measurements. The spirometry is used to retrospectively sort the CT scans by their correlated tidal lung volume within the patient's normal breathing cycle. This method has been prototyped using data from three lung cancer patients. The actual tidal lung volumes agreed with the specified bin volumes within standard deviations ranging between 22 and 33 cm3. An analysis of sagittal and coronal images demonstrated relatively small (<1 cm) motion artifacts along the diaphragm, even for tidal volumes where the rate of breathing motion is greatest. While still under development, this technology has the potential for revolutionizing the radiotherapy treatment planning for the thorax and upper abdomen.

The accurate determination of x-ray signal properties is important to several computed tomography (CT) research and development areas, notably for statistical reconstruction algorithms and dose-reduction simulation. The most commonly used model of CT signal formation, assuming monoenergetic x-ray sources with quantum counting detectors obeying simple Poisson statistics, does not reflect the actual physics of CT acquisition. This paper describes a more accurate model, taking into account the energy-integrating detection process, nonuniform flux profiles, and data-conditioning processes. Methods are developed to experimentally measure and theoretically calculate statistical distributions, as well as techniques to analyze CT signal properties. Results indicate the limitations of current models and suggest improvements for the description of CT signal properties.

Objectives: A new technique for determining the position of each electrode in the cochlea is described and applied to spiral computed tomography data from 15 patients implanted with Advanced Bionics HiFocus I, lj, or Helix arrays. Methods: ANALYZE imaging software was used to register 3-dimensional image volumes from patients' preoperative and postoperative scans and from a single body donor whose unimplanted ears were scanned clinically, with micro computed tomography and with orthogonal-plane fluorescence optical sectioning (OPFOS) microscopy. By use of this registration, we compared the atlas of OPFOS images of soft tissue within the body donor's cochlea with the bone and fluid/ tissue boundary available in patient scan data to choose the midmodiolar axis position and judge the electrode position in the scala tympani or scala vestibuli, including the distance to the medial and lateral scalar walls. The angular rotation 0 0 start point is a line joining the midmodiolar axis and the middle of the cochlear canal entry from the vestibule. Results: The group mean array insertion depth was 477 0 (range, 286 0 to 655 0). The word scores were negatively correlated (r =-0.59; P = .028) with the number of electrodes in the scala vestibuli. Conclusions: Although the individual variability in all measures was large, repeated patterns of suboptimal electrode placement were observed across subjects, underscoring the applicability of this technique.

Traditional computed tomography (CT) reconstructions of total joint prostheses are limited by metal artifacts from corrupted projection data. Published metal artifact reduction methods are based on the assumption that severe attenuation of X-rays by prostheses renders corresponding portions of projection data unavailable, hence the "missing" data are either avoided (in iterative reconstruction) or interpolated (in filtered backprojection with data completion; typically, with filling data "gaps" via linear functions). In this paper, we propose a wavelet-based multiresolution analysis method for metal artifact reduction, in which information is extracted from corrupted projection data. The wavelet method improves image quality by a successive interpolation in the wavelet domain. Theoretical analysis and experimental results demonstrate that the metal artifacts due to both photon starving and beam hardening can be effectively suppressed using our method. As compared to the filtered backprojection after linear interpolation, the wavelet-based reconstruction is significantly more accurate for depiction of anatomical structures, especially in the immediate neighborhood of the prostheses. This superior imaging precision is highly advantageous in geometric modeling for fitting hip prostheses.

The goal of this study is to evaluate the theoretically achievable accuracy in estimating photon cross sections at low energies (20-1000 keV) from idealized dual-energy x-ray computed tomography (CT) images. Cross-section estimation from dual-energy measurements requires a model that can accurately represent photon cross sections of any biological material as a function of energy by specifying only two characteristic parameters of the underlying material, e.g., effective atomic number and density. This paper evaluates the accuracy of two commonly used two-parameter cross-section models for postprocessing idealized measurements derived from dual-energy CT images. The parametric fit model (PFM) accounts for electron-binding effects and photoelectric absorption by power functions in atomic number and energy and scattering by the Klein-Nishina cross section. The basis-vector model (BVM) assumes that attenuation coefficients of any biological substance can be approximated by a linear combination of mass attenuation coefficients of two dissimilar basis substances. Both PFM and BVM were fit to a modern cross-section library for a range of elements and mixtures representative of naturally occurring biological materials (Z = 2-20). The PFM model, in conjunction with the effective atomic number approximation, yields estimated the total linear cross-section estimates with mean absolute and maximum error ranges of 0.6%-2.2% and 1%-6%, respectively. The corresponding error ranges for BVM estimates were 0.02%-0.15% and 0.1%-0.5%. However, for photoelectric absorption frequency, the PFM absolute mean and maximum errors were 10.8%-22.4% and 29%-50%, compared with corresponding BVM errors of 0.4%-11.3% and 0.5%-17.0%, respectively. Both models were found to exhibit similar sensitivities to image-intensity measurement uncertainties. Of the two models, BVM is the most promising approach for realizing dual-energy CT cross-section measurement.

Rationale and Objectives CT section thickness and reconstruction kernel each influence CT measurements of emphysema. This study was performed to assess whether their effects are related to the magnitude of the measurement. Materials and Methods Low-radiation-dose multidetector CT was performed in 21 subjects representing a wide range of emphysema severity. Images were reconstructed using 20 different combinations of section thickness and reconstruction kernel. Emphysema index values were determined as the percentage of lung pixels having attenuation lower than multiple thresholds ranging from −960 HU to −890 HU. The index values obtained from the different thickness-kernel combinations were compared by repeated measures ANOVA and Bland-Altman plots of mean vs. difference, and correlated with quantitative histology (mean linear intercept, Lm) in a subset of resected lung specimens. Results The effects of section thickness and reconstruction kernel on the emphysema index were significant (p<0.001) and diminished as the index threshold was raised. The changes in index values due to changing the thickness-kernel combination were largest for subjects with intermediate index values (10–30%), and became progressively smaller for those with lower and higher index values. This pattern was consistent regardless of the thickness-kernel combinations compared and the HU threshold used. Correlations between the emphysema index values obtained with each thickness-kernel combination and Lm ranged from r=0.55–0.68 (p=0.007–0.03). Conclusion The effects of CT section thickness and kernel on emphysema index values varied systematically with the magnitude of the emphysema index. All reconstruction techniques provided significant correlations with quantitative histology.

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