Thermometry mapping during CT-guided thermal ablations: proof of feasibility and internal validation using spectral CT.

OBJECTIVE: Conventional CT imaging does not provide quantitative information on local thermal changes during percutaneous ablative therapy of cancerous and benign tumors, aside from few qualitative, visual cues. In this study, we have investigated changes in CT signal across a wide range of temperatures and two physical phases for two different tissue mimicking materials, each. Approach: A series of experiments were conducted using an anthropomorphic phantom filled with water-based gel and olive oil, respectively. Multiple, clinically used ablation devices were applied to locally cool or heat the phantom material and were arranged in a configuration that produced thermal changes in regions with inconsequential amounts of metal artifact. Eight fiber optic thermal sensors were positioned in the region absent of metal artifact and were used to record local temperatures throughout the experiments. A spectral CT scanner was used to periodically acquire and generate Electron Density weighted images. Average electron density weighted values in 1 mm3 volumes of interest near the temperature sensors were computed and these data were then used to calculate thermal volumetric expansion coefficients for each material and phase. Main Results: The experimentally determined expansion coefficients well-matched existing published values and variations with temperature -maximally differing by 5% of the known value. As a proof of concept, a CT-generated temperature map was produced during a heating time point of the water-based gel phantom, demonstrating the capability to map changes in electron density weighted signal to temperature. SIGNIFICANCE: This study has demonstrated that spectral CT can be used to estimate local temperature changes for different materials and phases across temperature ranges produced by thermal ablations.

Deep convolutional-neural-network-based metal artifact reduction for CT-guided interventional oncology procedures (MARIO).

BACKGROUND: Computed tomography (CT) is routinely used to guide cryoablation procedures. Notably, CT-guidance provides 3D localization of cryoprobes and can be used to delineate frozen tissue during ablation. However, metal-induced artifacts from ablation probes can make accurate probe placement challenging and degrade the ice ball conspicuity, which in combination could lead to undertreatment of potentially curable lesions. PURPOSE: In this work, we propose an image-based neural network (CNN) model for metal artifact reduction for CT-guided interventional procedures. METHODS: An image domain metal artifact simulation framework was developed and validated for deep-learning-based metal artifact reduction for interventional oncology (MARIO). CT scans were acquired for 19 different cryoablation probe configurations. The probe configurations varied in the number of probes and the relative orientations. A combination of intensity thresholding and masking based on maximum intensity projections (MIPs) was used to segment both the probes only and probes + artifact in each phantom image. Each of the probe and probe + artifact images were then inserted into 19 unique patient exams, in the image domain, to simulate metal artifact appearance for CT-guided interventional oncology procedures. The resulting 361 pairs of simulated image volumes were partitioned into disjoint training and test datasets of 304 and 57 volumes, respectively. From the training partition, 116 600 image patches with a shape of 128 × 128 × 5 pixels were randomly extracted to be used for training data. The input images consisted of a superposition of the patient and probe + artifact images. The target images consisted of a superposition of the patient and probe only images. This dataset was used to optimize a U-Net type model. The trained model was then applied to 50 independent, previously unseen CT images obtained during renal cryoablations. Three board-certified radiologists with experience in CT-guided ablations performed a blinded review of the MARIO images. A total of 100 images (50 original, 50 MARIO processed) were assessed across different aspects of image quality on a 4-point likert-type item. Statistical analyses were performed using Wilcoxon signed-rank test for paired samples. RESULTS: Reader scores were significantly higher for MARIO processed images compared to the original images across all metrics (all p < 0.001). The average scores of the overall image quality, iceball conspicuity, overall metal artifact, needle tip visualization, target region confidence, and worst metal artifact, needle tip visualization, iceball conspicuity, and target region confidence improved by 34.91%, 36.29%, 39.94%, 34.17%, 35.13%, and 45.70%, respectively. CONCLUSIONS: The proposed method of image-based metal artifact simulation can be used to train a MARIO algorithm to effectively reduce probe-related metal artifacts in CT-guided cryoablation procedures.

Adaptation of a channelized Hotelling observer model to accommodate anthropomorphic backgrounds and moving test objects in X-ray angiography.

BACKGROUND: Prior implementations of the channelized Hotelling observer (CHO) model have succeeded in assessing the performance of X-ray angiography systems under a variety of imaging conditions. However, often times these conditions do not resemble those present in routine clinical imaging scenarios, such as having complex anthropomorphic backgrounds in conjunction with moving test objects. PURPOSE: This work builds up on prior established CHO methods and introduces a new approach to switch from the already established "multiple-sample" CHO implementation to a "single-sample" technique. The proposed implementation enables the inclusion of moving test objects upon nonuniform backgrounds by allowing only a single sample to represent the test object present condition that is to be used within the statistical test to estimate the detectability index. METHODS: To assess the proposed method, two image data sets were acquired with a clinical X-ray angiography system. The first set consisted of a uniform background in combination with static test objects while the second consisted of an anthropomorphic chest phantom in conjunction with moving test objects. The first set was used to validate the proposed approach against the multiple-sample method while the second was used to assess the feasibility of the proposed method under a variety of imaging conditions, including seven object sizes and seven detector target dose (DTD) levels. RESULTS: For the uniform background data set, considering all detectability indices greater or equal than 1, the ratio between the detectability indices of the proposed single-sample approach versus the multiple-sample method was 0.997 ± 0.056 (range 0.884-1.159). The average single-direction width of the 95% confidence intervals (CIs) of the detectability index estimates for the multiple-sample method was 0.38 ± 0.43 (range 0.03-2.20). For the single-sample approach, the average width was 2.52 ± 0.63 (range 1.11-5.44). For the anthropomorphic background image set, the results were consistent with classical quantum-limited signal-to-noise ratio (SNR) theory. The magnitude of the detectability indices varied predictably with changes in both object size and DTD, with the highest value associated with the highest dose and the largest object size. Additionally, the proposed method was able to capture differences in the imaging performance for a given test object across the field of view, which was associated with the attenuation levels provided by different features of the anthropomorphic background. CONCLUSIONS: A new single-sample variant of the CHO model to assess the performance of X-ray angiography imaging systems is proposed. The new approach is consistent with quantum-limited image quality theory and with a standard implementation of the CHO model. The proposed method enables the assessment of moving test objects in combination with complex, nonuniform image backgrounds, thereby opening the possibility to assess imaging conditions which more closely resemble those used in clinical care.

Establishing a quality assurance program for photon counting detector (PCD) CT: Tips and caveats.

PURPOSE: To determine the suitability of a quality assurance (QA) program based on the American College of Radiology's (ACR) CT quality control (QC) manual to fully evaluate the unique capabilities of a clinical photon-counting-detector (PCD) CT system. METHODS: A daily QA program was established to evaluate CT number accuracy and artifacts for both standard and ultra-high-resolution (UHR) scan modes. A complete system performance evaluation was conducted in accordance with the ACR CT QC manual by scanning the CT Accreditation Phantom with routine clinical protocols and reconstructing low-energy-threshold (T3D) and virtual monoenergetic images (VMIs) between 40 and 120 keV. Spatial resolution was evaluated by computing the modulation transfer function (MTF) for the UHR mode, and multi-energy performance was evaluated by scanning a body phantom containing four iodine inserts with concentrations between 2 and 15 mg I/cc. RESULTS: The daily QA program identified instances when the detector needed recalibration or replacement. CT number accuracy was impacted by image type: CT numbers at 70 keV VMI were within the acceptable range (defined for 120 kV). Other keV VMIs and the T3D reconstruction had at least one insert with CT number outside the acceptable range. The limiting resolution was nearly 40 lp/cm based on MTF measurements, which far exceeds the 12 lp/cm maximum capability of the ACR phantom. The CT numbers in the iodine inserts were accurate on all VMIs (3.8% average percentage error), while the iodine concentrations had an average root mean squared error of 0.3 mg I/cc. CONCLUSION: Protocols and parameters must be properly selected on PCD-CT to meet current accreditation requirements with the ACR CT phantom. Use of the 70 keV VMI allowed passing all tests prescribed in the ACR CT manual. Additional evaluations such an MTF measurement and multi-energy phantom scans are also recommended to comprehensively evaluate PCD-CT scanner performance.

Dual-Applicator MR Imaging-Guided Microwave Ablation with Real-Time MR Thermometry: Phantom and Porcine Tissue Model Experiments.

PURPOSE: To investigate the effect of simultaneous use of dual applicators on the image quality of real-time magnetic resonance (MR) thermometry and to characterize the dual-applicator treatment zone pattern during MR imaging-guided microwave ablation (MWA). MATERIALS AND METHODS: MWA experiments were performed on a 1.5-T MR scanner with 2 commercial microwave systems (902-928 MHz). Phantom experiments were first performed to evaluate the effect of dual-applicator MWA on the image quality of MR. Then, porcine tissue model experiments were conducted with real-time MR thermometry using either a single applicator or dual applicators inserted 2.6, 3.6, and 4.6 cm apart. Fiberoptic thermal probes were used to measure the temperature changes at the tissue surface. RESULTS: Simultaneous use of dual applicators resulted in a decrease in the relative signal-to-noise ratio (SNR) in the MR thermometry images to 55% ± 2.9% when compared with that of a single applicator (86.2% ± 2.0%). Despite the lower SNR, the temperature and ablation zone maps were of adequate quality to allow visualization of the ablation zone(s). The extents of increase in the temperature at the tissue surface using dual applicators (19.7 °C ± 2.6 °C) and a single applicator (18.2 °C ± 3.3 °C) were not significantly different (P = .40). Treatment zones were significantly larger (P < .05) in dual-applicator ablations (29.4 ± 0.4, 39.9 ± 0.6, and 42.6 ± 0.9 cm2 with 2.6-, 3.6-, and 4.6-cm spacing, respectively) at the end of the ablation procedure than in the single-applicator MWA (18.6 ± 0.9 cm2). CONCLUSIONS: MR imaging-guided dual-applicator MWA produced larger ablation zones while allowing adequate real-time MR thermometry image quality for monitoring the evolution of the treatment zone.

MRI Radiomics for Assessment of Molecular Subtype, Pathological Complete Response, and Residual Cancer Burden in Breast Cancer Patients Treated With Neoadjuvant Chemotherapy.

RATIONALE AND OBJECTIVES: There are limited data on pretreatment imaging features that can predict response to neoadjuvant chemotherapy (NAC). To extract volumetric pretreatment MRI radiomics features and assess corresponding associations with breast cancer molecular subtypes, pathological complete response (pCR), and residual cancer burden (RCB) in patients treated with NAC. MATERIALS AND METHODS: In this IRB-approved study, clinical and pretreatment MRI data from patients with biopsy-proven breast cancer who received NAC between September 2009 and July 2016 were retrospectively analyzed. Tumors were manually identified and semi-automatically segmented on first postcontrast images. Morphological and three-dimensional textural features were computed, including unfiltered and filtered image data, with spatial scaling factors (SSF) of 2, 4, and 6 mm. Wilcoxon rank-sum tests and area under the receiver operating characteristic curve were used for statistical analysis. RESULTS: Two hundred and fifty nine patients with unilateral breast cancer, including 73 (28.2%) HER2+, 112 (43.2%) luminal, and 74 (28.6%) triple negative breast cancers (TNBC), were included. There was a significant difference in the median volume (p = 0.008), median longest axial tumor diameter (p = 0.009), and median longest volumetric diameter (p = 0.01) among tumor subtypes. There was also a significant difference in minimum signal intensity and entropy among the tumor subtypes with SSF = 4 mm (p = 0.009 and p = 0.02 respectively) and SSF = 6 mm (p = 0.007 and p < 0.001 respectively). Additionally, sphericity (p = 0.04) in HER2+ tumors and entropy with SSF = 2, 4, 6 mm (p = 0.004, 0.02, 0.047 respectively) in luminal tumors were significantly associated with pCR. Multiple features demonstrated significant association (p < 0.05) with pCR in TNBC and with RCB in luminal tumors and TNBC, with standard deviation of intensity with SSF = 6 mm achieving the highest AUC (AUC = 0.734) for pCR in TNBC. CONCLUSION: MRI radiomics features are associated with different molecular subtypes of breast cancer, pCR, and RCB. These features may be noninvasive imaging biomarkers to identify cancer subtype and predict response to NAC.

Body Interventional MRI for Diagnostic and Interventional Radiologists: Current Practice and Future Prospects.

Clinical use of MRI for guidance during interventional procedures emerged shortly after the introduction of clinical diagnostic MRI in the late 1980s. However, early applications of interventional MRI (iMRI) were limited owing to the lack of dedicated iMRI magnets, pulse sequences, and equipment. During the 3 decades that followed, technologic advancements in iMRI magnets that balance bore access and field strength, combined with the development of rapid MRI pulse sequences, surface coils, and commercially available MR-conditional devices, led to the rapid expansion of clinical iMRI applications, particularly in the field of body iMRI. iMRI offers several advantages, including superior soft-tissue resolution, ease of multiplanar imaging, lack of ionizing radiation, and capability to re-image the same section. Disadvantages include longer examination times, lack of MR-conditional equipment, less operator familiarity, and increased cost. Nonetheless, MRI guidance is particularly advantageous when the disease is best visualized with MRI and/or when superior soft-tissue contrast is needed for treatment monitoring. Safety in the iMRI environment is paramount and requires close collaboration among interventional radiologists, MR physicists, and all other iMRI team members. The implementation of risk-limiting measures for personnel and equipment in MR zones III and IV is key. Various commercially available MR-conditional needles, wires, and biopsy and ablation devices are now available throughout the world, depending on the local regulatory status. As such, there has been tremendous growth in the clinical applications of body iMRI, including localization of difficult lesions, biopsy, sclerotherapy, and cryoablation and thermal ablation of malignant and nonmalignant soft-tissue neoplasms. Online supplemental material is available for this article. ©RSNA, 2021.

Experimental Investigation of Cryoneedle Heating during MR-Guided Cryoablation in Ex Vivo Tissue Samples at 1.5-Tesla.

PURPOSE: To investigate cryoneedle heating risks during magnetic resonance (MR)-guided cryoablation and potential strategies to mitigate these risks. MATERIALS AND METHODS: Ex vivo experiments were performed on a 1.5-Tesla (T) MR scanner using an MR conditional cryoablation system on porcine tissue phantoms. Cryoneedles were placed inside the tissue phantom either with or without an angiocatheter. Typical cryoneedle geometric configurations (including gas supply line) encountered in clinical procedures with low to high expected heating risks were investigated. Up to 4 fiber optic temperature sensors were attached to the cryoneedle/angiocatheter to measure the MR-induced cryoneedle heating at different locations during MR with different estimated specific absorption rates (SARs). The impact of cryoneedle heating on cryoablation treatment was studied by comparing temperature changes during 10-min freeze-thaw cycles with and without MR. RESULTS: Rapid temperature increases of >100 °C in < 2 minutes were observed during MR with a SAR of 2.1 W/kg. The temperature changes during a typical freeze-thaw cycle were also affected by cryoneedle heating when MR was used to monitor the ice-ball evolution. The observed cryoneedle heating was affected by multiple factors; including cryoneedle geometric configurations, sequence SAR, whether an angiocatheter was used, and whether the cryoneedle was connected to the rest of the cryoablation system. CONCLUSIONS: The ex vivo experiments demonstrated that MR could induce significant cryoneedle heating risks. Furthermore, MR-induced cryoneedle heating can affect temperatures in the ice-ball evolution during the freeze-thaw cycle. Several practical strategies to reduce the cryoneedle heating have been proposed.

Task-specific efficient channel selection and bias management for Gabor function channelized Hotelling observer model for the assessment of x-ray angiography system performance.

PURPOSE: Channelized Hotelling observer (CHO) models have been implemented to assess imaging performance in x-ray angiography systems. While current methods are appropriate for assessing unprocessed images of moving test objects upon uniform-exposure backgrounds, they are inadequate for assessing conditions which more appropriately mimic clinical imaging conditions including the combination of moving test objects, complex anthropomorphic backgrounds, and image processing. In support of this broad goal, the purpose of this work was to develop theory and methods to automatically select a subset of task-specific efficient Gabor channels from a task-generic Gabor channel base set. Also, previously described theory and methods to manage detectability index (d') bias due to nonrandom temporal variations in image electronic noise will be revisited herein. METHODS: Starting with a base set of 96 Gabor channels, backward elimination of channels was used to automatically identify an "efficient" channel subset which reduced the number of channels retained in the subset while maintaining the magnitude of the d' estimate. The concept of a pixelwise Hotelling observer (PHO) model was introduced and similarly implemented to assess the performance of the efficient-channel CHO model. Bias in d' estimates arising from temporally variable nonstationary noise was modeled as a bivariate probability density function for normal distributions, where one variable corresponds to the signal from the test object and the other variable corresponds to the signal from temporally variable nonstationary noise. Theory and methods were tested on uniform-exposure unprocessed angiography images with detector target dose (DTD) of 6, 18, and 120 nGy containing static disk-shaped test objects with diameter in the range of 0.5 to 4 mm. RESULTS: Considering all DTD levels and test object sizes, the proposed method reduced the number of Gabor channels in the final subset by 63-82% compared to the original 96 Gabor channel base set, while maintaining a mean relative performance ( ( d CHO ' / d PHO ' ) × 100 % ) of 95%  ±  4% with respect to the reference PHO model. Experimental results demonstrated that the bivariate approach to account for bias due to temporally variable nonstationary noise resulted in improved correlation between the CHO and PHO models as compared to a previously proposed univariate approach. CONCLUSIONS: Computationally efficient backward elimination can be used to select an efficient subset of Gabor channels from an initial channel base set without substantially compromising the magnitude of the d' estimate. Bias due to temporally variable nonstationary noise can be modeled through a bivariate approach leading to an improved unbiased estimate of d'.

Improved MR-thermometry during hepatic microwave ablation by correcting for intermittent electromagnetic interference artifacts.

MRI-guided microwave ablation (MWA) is a minimally invasive treatment for localized cancer. MR thermometry has been shown to be able to provide vital information for monitoring the procedure in real-time. However, MRI during active MWA can suffer from image quality degradation due to intermittent electromagnetic interference (EMI). A novel approach to correct for EMI-contaminated images is presented here to improve MR thermometry during clinical hepatic MWA. The method was applied to MR-thermometry images acquired during four MR-guided hepatic MWA treatments using a commercially available MRI-configured microwave generator system. During the treatments MR thermometry data acquisition was synchronized to respiratory cycle to minimize the impact of motion. EMI was detected and corrected using uncontaminated k-space data from nearby frames in k-space. Substantially improved temperature and thermal damage maps have been obtained and the treatment zone can be better visualized. Our ex vivo tissue sample study shows the correction introduced minimal errors to the temperature maps and thermal damage maps.

Evaluation of Shimming Techniques on MRI Breast Image Quality at 1.5T.

OBJECTIVE: The quality of all clinical MRI is dependent on B0 homogeneity, which is optimized during the shimming part of a prescan or preparatory phase before image acquisition. The purpose of this study was to assess shimming techniques clinically employed for breast MRI across our practice, and to determine factors that correlate with higher image quality for contrast-enhanced breast MRI at 1.5T. METHODS: One hundred consecutive female patients were retrospectively collected with Institutional Review Board approval. Shimming-related parameters, including shim-box placement and shimming gradient offsets were extracted from prior contrast-enhanced 3D fat-suppressed T1-weighted gradient echo image acquisitions. Three breast radiologists evaluated these images for fat saturation, breast density, overall image quality, and artifacts. Technologist experience was also evaluated for variability of shimming. Generalized linear mixed models were used to compare acquisition parameters between fat saturation. P < 0.05 was considered as statistical significance. RESULTS: The percentage of soft tissue inside the field of view (FOV) (ie, Tissue/FOV) in the good fat-saturation group (0.37 ± 0.06) was significantly lower (P < 0.01) than that in the poor fat-saturation group (0.39 ± 0.06). Other shimming-related parameters were found not significantly affecting the fat-saturation outcomes. Technologists with more experience tended to have less variable shimming performance than junior technologists did. CONCLUSIONS: The quality of clinical MRI and especially breast MRI is highly dependent on shimming. Decreasing Tissue/FOV was associated with good image quality (good fat saturation). Optimization of shimming may require manual shimming or higher-order field-correction strategies.

Development of a robust MRI fiducial system for automated fusion of MR-US abdominal images.

We present the development of a two-component magnetic resonance (MR) fiducial system, that is, a fiducial marker device combined with an auto-segmentation algorithm, designed to be paired with existing ultrasound probe tracking and image fusion technology to automatically fuse MR and ultrasound (US) images. The fiducial device consisted of four ~6.4 mL cylindrical wells filled with 1 g/L copper sulfate solution. The algorithm was designed to automatically segment the device in clinical abdominal MR images. The algorithm's detection rate and repeatability were investigated through a phantom study and in human volunteers. The detection rate was 100% in all phantom and human images. The center-of-mass of the fiducial device was robustly identified with maximum variations of 2.9 mm in position and 0.9° in angular orientation. In volunteer images, average differences between algorithm-measured inter-marker spacings and actual separation distances were 0.53 ± 0.36 mm. "Proof-of-concept" automatic MR-US fusions were conducted with sets of images from both a phantom and volunteer using a commercial prototype system, which was built based on the above findings. Image fusion accuracy was measured to be within 5 mm for breath-hold scanning. These results demonstrate the capability of this approach to automatically fuse US and MR images acquired across a wide range of clinical abdominal pulse sequences.

Safety of Laser Interstitial Thermal Therapy in Patients With Pacemakers.

BACKGROUND AND IMPORTANCE: Laser interstitial thermal therapy (LiTT) has increasingly been used as a treatment option for medically refractory epilepsy, tumors, and radiation necrosis. The use of LiTT requires intraoperative magnetic resonance (MR) thermography. This can become an issue in patients with other implanted therapeutic devices such as pacemakers and vagal nerve stimulators due to concerns regarding increases in the specific absorption rate (SAR). This is a technical case report demonstrating a successfully and safely performed LiTT in a 1.5-T magnetic resonance imaging (MRI) in a patient with a pacemaker for mesial temporal sclerosis. CLINICAL PRESENTATION: An 83-yr-old gentleman who had an implanted cardiac pacemaker presented with medically intractable epilepsy and was confirmed to have mesial temporal sclerosis on imaging. Video electroencephalography demonstrated concordant ipsilateral seizures and semiology. He underwent LiTT for ablation of the mesial temporal lobe. This was performed with the below described protocol with a cardiology nurse monitoring the patient's cardiac condition and a physicist monitoring SAR, and MR imaging quality without any adverse events. CONCLUSION: This study reports on a protocol of cardiac and MR SAR to safely perform MR-guided LiTT in the setting of traditional pacemakers in patients who are not pacemaker dependent.

Use of a channelized Hotelling observer to assess CT image quality and optimize dose reduction for iteratively reconstructed images.

The use of iterative reconstruction (IR) algorithms in CT generally decreases image noise and enables dose reduction. However, the amount of dose reduction possible using IR without sacrificing diagnostic performance is difficult to assess with conventional image quality metrics. Through this investigation, achievable dose reduction using a commercially available IR algorithm without loss of low contrast spatial resolution was determined with a channelized Hotelling observer (CHO) model and used to optimize a clinical abdomen/pelvis exam protocol. A phantom containing 21 low contrast disks-three different contrast levels and seven different diameters-was imaged at different dose levels. Images were created with filtered backprojection (FBP) and IR. The CHO was tasked with detecting the low contrast disks. CHO performance indicated dose could be reduced by 22% to 25% without compromising low contrast detectability (as compared to full-dose FBP images) whereas 50% or more dose reduction significantly reduced detection performance. Importantly, default settings for the scanner and protocol investigated reduced dose by upward of 75%. Subsequently, CHO-based protocol changes to the default protocol yielded images of higher quality and doses more consistent with values from a larger, dose-optimized scanner fleet. CHO assessment provided objective data to successfully optimize a clinical CT acquisition protocol.

Evaluation of feasibility of 1.5 Tesla prostate MRI using body coil RF transmit in a patient with an implanted vagus nerve stimulator.

PURPOSE: To assess risks of RF-heating of a vagus nerve stimulator (VNS) during 1.5 T prostate MRI using body coil transmit and to compare these risks with those associated with MRI head exams using a transmit/receive head coil. METHODS: Spatial distributions of radio-frequency (RF) B1 fields generated by transmit/receive (T/R) body and head coils were empirically assessed along the long axis of a 1.5 T MRI scanner bore. Measurements were obtained along the center axis of the scanner and laterally offset by 15 cm (body coil) and 7 cm (head coil). RF-field measurements were supplemented with direct measurements of RF-heating of 15 cm long copper wires affixed to and submerged in the "neck" region of the gelled saline-filled (sodium chloride and polyacrylic acid) "head-and-torso" phantom. Temperature elevations at the lead tips were measured using fiber-optic thermometers with the phantom positioned at systematically increased distances from the scanner isocenter. RESULTS: B1 field measurements demonstrated greater than 10 dB reduction in RF power at distances beyond 28 cm and 24 cm from isocenter for body and head coil, respectively. Moreover, RF power from body coil transmit at distances greater than 32 cm from isocenter was found to be lower than from the RF power from head coil transmit measured at locations adjacent to the coil array at its opening. Correspondingly, maximum temperature elevations at the tips of the copper wires decreased with increasing distance from isocenter - from 7.4°C at 0 cm to no appreciable heating at locations beyond 40 cm. CONCLUSIONS: For the particular scanner model evaluated in this study, positioning an implanted VNS farther than 32 cm from isocenter (configuration achievable for prostate exams) can reduce risks of RF-heating resulting from the body coil transmit to those associated with using a T/R head coil.

Practical implementation of Channelized Hotelling Observers: Effect of ROI size.

Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO's performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO's performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies.

Correlation between a 2D channelized Hotelling observer and human observers in a low-contrast detection task with multislice reading in CT.

PURPOSE: Model observers have been successfully developed and used to assess the quality of static 2D CT images. However, radiologists typically read images by paging through multiple 2D slices (i.e., multislice reading). The purpose of this study was to correlate human and model observer performance in a low-contrast detection task performed using both 2D and multislice reading, and to determine if the 2D model observer still correlate well with human observer performance in multislice reading. METHODS: A phantom containing 18 low-contrast spheres (6 sizes × 3 contrast levels) was scanned on a 192-slice CT scanner at five dose levels (CTDIvol = 27, 13.5, 6.8, 3.4, and 1.7 mGy), each repeated 100 times. Images were reconstructed using both filtered-backprojection (FBP) and an iterative reconstruction (IR) method (ADMIRE, Siemens). A 3D volume of interest (VOI) around each sphere was extracted and placed side-by-side with a signal-absent VOI to create a 2-alternative forced choice (2AFC) trial. Sixteen 2AFC studies were generated, each with 100 trials, to evaluate the impact of radiation dose, lesion size and contrast, and reconstruction methods on object detection. In total, 1600 trials were presented to both model and human observers. Three medical physicists acted as human observers and were allowed to page through the 3D volumes to make a decision for each 2AFC trial. The human observer performance was compared with the performance of a multislice channelized Hotelling observer (CHO_MS), which integrates multislice image data, and with the performance of previously validated CHO, which operates on static 2D images (CHO_2D). For comparison, the same 16 2AFC studies were also performed in a 2D viewing mode by the human observers and compared with the multislice viewing performance and the two CHO models. RESULTS: Human observer performance was well correlated with the CHO_2D performance in the 2D viewing mode [Pearson product-moment correlation coefficient R = 0.972, 95% confidence interval (CI): 0.919 to 0.990] and with the CHO_MS performance in the multislice viewing mode (R = 0.952, 95% CI: 0.865 to 0.984). The CHO_2D performance, calculated from the 2D viewing mode, also had a strong correlation with human observer performance in the multislice viewing mode (R = 0.957, 95% CI: 879 to 0.985). Human observer performance varied between the multislice and 2D modes. One reader performed better in the multislice mode (P = 0.013); whereas the other two readers showed no significant difference between the two viewing modes (P = 0.057 and P = 0.38). CONCLUSIONS: A 2D CHO model is highly correlated with human observer performance in detecting spherical low contrast objects in multislice viewing of CT images. This finding provides some evidence for the use of a simpler, 2D CHO to assess image quality in clinically relevant CT tasks where multislice viewing is used.

Technical Note: Display window setting: An important factor for detecting subtle but clinically relevant artifacts in daily CT quality control.

PURPOSE: This study aimed to investigate the influence of display window setting on technologist performance detecting subtle but clinically relevant artifacts in daily computed tomography (CT) quality control (dQC) images. METHODS: Fifty three sets of dQC images were retrospectively selected, including 30 sets without artifacts, and 23 with subtle but clinically relevant artifacts. They were randomized and shown to six CT technologists (two new and four experienced). Each technologist reviewed all images in each of two sessions, one with a display window width (WW) of 100 HU, which is currently recommended by the American College of Radiology, and the other with a narrow WW of 40 HU, both at a window level of 0 HU. For each case, technologists rated the presence of image artifacts based on a five point scale. The area under the receiver operating characteristic curve (AUC) was used to evaluate the artifact detection performance. RESULTS: At a WW of 100 HU, the AUC (95% confidence interval) was 0.658 (0.576, 0.740), 0.532 (0.429, 0.635), and 0.616 (0.543, 0.619) for the experienced, new, and all technologists, respectively. At a WW of 40 HU, the AUC was 0.768 (0.687, 0.850), 0.546 (0.433, 0.658), and 0.694 (0.619, 0.769), respectively. The performance significantly improved at WW of 40 HU for experienced technologists (p = 0.009) and for all technologists (p = 0.040). CONCLUSIONS: Use of a narrow display WW significantly improved technologists' performance in dQC for detecting subtle but clinically relevant artifacts as compared to that using a 100 HU display WW.

Direct estimation and correction of bias from temporally variable non-stationary noise in a channelized Hotelling model observer.

Channelized Hotelling model observer (CHO) methods were developed to assess performance of an x-ray angiography system. The analytical methods included correction for known bias error due to finite sampling. Detectability indices ([Formula: see text]) corresponding to disk-shaped objects with diameters in the range 0.5-4 mm were calculated. Application of the CHO for variable detector target dose (DTD) in the range 6-240 nGy frame(-1) resulted in [Formula: see text] estimates which were as much as 2.9× greater than expected of a quantum limited system. Over-estimation of [Formula: see text] was presumed to be a result of bias error due to temporally variable non-stationary noise. Statistical theory which allows for independent contributions of 'signal' from a test object (o) and temporally variable non-stationary noise (ns) was developed. The theory demonstrates that the biased [Formula: see text] is the sum of the detectability indices associated with the test object [Formula: see text] and non-stationary noise ([Formula: see text]). Given the nature of the imaging system and the experimental methods, [Formula: see text] cannot be directly determined independent of [Formula: see text]. However, methods to estimate [Formula: see text] independent of [Formula: see text] were developed. In accordance with the theory, [Formula: see text] was subtracted from experimental estimates of [Formula: see text], providing an unbiased estimate of [Formula: see text]. Estimates of [Formula: see text] exhibited trends consistent with expectations of an angiography system that is quantum limited for high DTD and compromised by detector electronic readout noise for low DTD conditions. Results suggest that these methods provide [Formula: see text] estimates which are accurate and precise for [Formula: see text]. Further, results demonstrated that the source of bias was detector electronic readout noise. In summary, this work presents theory and methods to test for the presence of bias in Hotelling model observers due to temporally variable non-stationary noise and correct this bias when the temporally variable non-stationary noise is independent and additive with respect to the test object signal.