Artificial Intelligence-Assisted Amphiregulin and Epiregulin IHC Predicts Panitumumab Benefit in RAS Wild-Type Metastatic Colorectal Cancer.

PURPOSE: High tumor mRNA levels of the EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are associated with anti-EGFR agent response in metastatic colorectal cancer (mCRC). However, ligand RNA assays have not been adopted into routine practice due to issues with analytic precision and practicality. We investigated whether AREG/EREG IHC could predict benefit from the anti-EGFR agent panitumumab. EXPERIMENTAL DESIGN: Artificial intelligence algorithms were developed to assess AREG/EREG IHC in 274 patients from the PICCOLO trial of irinotecan with or without panitumumab (Ir vs. IrPan) in RAS wild-type mCRC. The primary endpoint was progression-free survival (PFS). Secondary endpoints were RECIST response rate (RR) and overall survival (OS). Models were repeated adjusting separately for BRAF mutation status and primary tumor location (PTL). RESULTS: High ligand expression was associated with significant PFS benefit from IrPan compared with Ir [8.0 vs. 3.2 months; HR, 0.54; 95% confidence interval (CI), 0.37-0.79; P = 0.001]; whereas low ligand expression was not (3.4 vs. 4.4 months; HR, 1.05; 95% CI, 0.74-1.49; P = 0.78). The ligand-treatment interaction was significant (P interaction = 0.02) and remained significant after adjustment for BRAF-mutation status and PTL. Likewise, RECIST RR was significantly improved in patients with high ligand expression (IrPan vs. Ir: 48% vs. 6%; P < 0.0001) but not those with low ligand expression (25% vs. 14%; P = 0.10; P interaction = 0.01). The effect on OS was similar but not statistically significant. CONCLUSIONS: AREG/EREG IHC identified patients who benefitted from the addition of panitumumab to irinotecan chemotherapy. IHC is a practicable assay that may be of use in routine practice.

Numerical observer for atherosclerotic plaque classification in spectral computed tomography.

Spectral computed tomography (SCT) generates better image quality than conventional computed tomography (CT). It has overcome several limitations for imaging atherosclerotic plaque. However, the literature evaluating the performance of SCT based on objective image assessment is very limited for the task of discriminating plaques. We developed a numerical-observer method and used it to assess performance on discrimination vulnerable-plaque features and compared the performance among multienergy CT (MECT), dual-energy CT (DECT), and conventional CT methods. Our numerical observer was designed to incorporate all spectral information and comprised two-processing stages. First, each energy-window domain was preprocessed by a set of localized channelized Hotelling observers (CHO). In this step, the spectral image in each energy bin was decorrelated using localized prewhitening and matched filtering with a set of Laguerre-Gaussian channel functions. Second, the series of the intermediate scores computed from all the CHOs were integrated by a Hotelling observer with an additional prewhitening and matched filter. The overall signal-to-noise ratio (SNR) and the area under the receiver operating characteristic curve (AUC) were obtained, yielding an overall discrimination performance metric. The performance of our new observer was evaluated for the particular binary classification task of differentiating between alternative plaque characterizations in carotid arteries. A clinically realistic model of signal variability was also included in our simulation of the discrimination tasks. The inclusion of signal variation is a key to applying the proposed observer method to spectral CT data. Hence, the task-based approaches based on the signal-known-exactly/background-known-exactly (SKE/BKE) framework and the clinical-relevant signal-known-statistically/background-known-exactly (SKS/BKE) framework were applied for analytical computation of figures of merit (FOM). Simulated data of a carotid-atherosclerosis patient were used to validate our methods. We used an extended cardiac-torso anthropomorphic digital phantom and three simulated plaque types (i.e., calcified plaque, fatty-mixed plaque, and iodine-mixed blood). The images were reconstructed using a standard filtered backprojection (FBP) algorithm for all the acquisition methods and were applied to perform two different discrimination tasks of: (1) calcified plaque versus fatty-mixed plaque and (2) calcified plaque versus iodine-mixed blood. MECT outperformed DECT and conventional CT systems for all cases of the SKE/BKE and SKS/BKE tasks (all [Formula: see text]). On average of signal variability, MECT yielded the SNR improvements over other acquisition methods in the range of 46.8% to 65.3% (all [Formula: see text]) for FBP-Ramp images and 53.2% to 67.7% (all [Formula: see text]) for FBP-Hanning images for both identification tasks. This proposed numerical observer combined with our signal variability framework is promising for assessing material characterization obtained through the additional energy-dependent attenuation information of SCT. These methods can be further extended to other clinical tasks such as kidney or urinary stone identification applications.

Spectral CT using multiple balanced K-edge filters.

Our goal is to validate a spectral computed tomography (CT) system design that uses a conventional X-ray source with multiple balanced K-edge filters. By performing a simultaneously synthetic reconstruction in multiple energy bins, we obtained a good agreement between measurements and model expectations for a reasonably complex phantom. We performed simulation and data acquisition on a phantom containing multiple rods of different materials using a NeuroLogica CT scanner. Five balanced K-edge filters including Molybdenum, Cerium, Dysprosium, Erbium, and Tungsten were used separately proximal to the X-ray tube. For each sinogram bin, measured filtered vector can be defined as a product of a transmission matrix, which is determined by the filters and is independent of the imaging object, and energy-binned intensity vector. The energy-binned sinograms were then obtained by inverting the transmission matrix followed by a multiplication of the filter measurement vector. For each energy bin defined by two consecutive K-edges, a synthesized energy-binned attenuation image was obtained using filtered back-projection reconstruction. The reconstructed attenuation coefficients for each rod obtained from the experiment was in good agreement with the corresponding simulated results. Furthermore, the reconstructed attenuation coefficients for a given energy bin, agreed with National Institute of Standards and Technology reference values when beam hardening within the energy bin is small. The proposed cost-effective system design using multiple balanced K-edge filters can be used to perform spectral CT imaging at clinically relevant flux rates using conventional detectors and integrating electronics.

4D numerical observer for lesion detection in respiratory-gated PET.

PURPOSE: Respiratory-gated positron emission tomography (PET)/computed tomography protocols reduce lesion smearing and improve lesion detection through a synchronized acquisition of emission data. However, an objective assessment of image quality of the improvement gained from respiratory-gated PET is mainly limited to a three-dimensional (3D) approach. This work proposes a 4D numerical observer that incorporates both spatial and temporal informations for detection tasks in pulmonary oncology. METHODS: The authors propose a 4D numerical observer constructed with a 3D channelized Hotelling observer for the spatial domain followed by a Hotelling observer for the temporal domain. Realistic (18)F-fluorodeoxyglucose activity distributions were simulated using a 4D extended cardiac torso anthropomorphic phantom including 12 spherical lesions at different anatomical locations (lower, upper, anterior, and posterior) within the lungs. Simulated data based on Monte Carlo simulation were obtained using geant4 application for tomographic emission (GATE). Fifty noise realizations of six respiratory-gated PET frames were simulated by GATE using a model of the Siemens Biograph mMR scanner geometry. PET sinograms of the thorax background and pulmonary lesions that were simulated separately were merged to generate different conditions of the lesions to the background (e.g., lesion contrast and motion). A conventional ordered subset expectation maximization (OSEM) reconstruction (5 iterations and 6 subsets) was used to obtain: (1) gated, (2) nongated, and (3) motion-corrected image volumes (a total of 3200 subimage volumes: 2400 gated, 400 nongated, and 400 motion-corrected). Lesion-detection signal-to-noise ratios (SNRs) were measured in different lesion-to-background contrast levels (3.5, 8.0, 9.0, and 20.0), lesion diameters (10.0, 13.0, and 16.0 mm), and respiratory motion displacements (17.6-31.3 mm). The proposed 4D numerical observer applied on multiple-gated images was compared to the conventional 3D approach applied on the nongated and motion-corrected images. RESULTS: On average, the proposed 4D numerical observer improved the detection SNR by 48.6% (p < 0.005), whereas the 3D methods on motion-corrected images improved by 31.0% (p < 0.005) as compared to the nongated method. For all different conditions of the lesions, the relative SNR measurement (Gain = SNRObserved/SNRNongated) of the 4D method was significantly higher than one from the motion-corrected 3D method by 13.8% (p < 0.02), where Gain4D was 1.49 ± 0.21 and Gain3D was 1.31 ± 0.15. For the lesion with the highest amplitude of motion, the 4D numerical observer yielded the highest observer-performance improvement (176%). For the lesion undergoing the smallest motion amplitude, the 4D method provided superior lesion detectability compared with the 3D method, which provided a detection SNR close to the nongated method. The investigation on a structure of the 4D numerical observer showed that a Laguerre-Gaussian channel matrix with a volumetric 3D function yielded higher lesion-detection performance than one with a 2D-stack-channelized function, whereas a different kind of channels that have the ability to mimic the human visual system, i.e., difference-of-Gaussian, showed similar performance in detecting uniform and spherical lesions. The investigation of the detection performance when increasing noise levels yielded decreasing detection SNR by 27.6% and 41.5% for the nongated and gated methods, respectively. The investigation of lesion contrast and diameter showed that the proposed 4D observer preserved the linearity property of an optimal-linear observer while the motion was present. Furthermore, the investigation of the iteration and subset numbers of the OSEM algorithm demonstrated that these parameters had impact on the lesion detectability and the selection of the optimal parameters could provide the maximum lesion-detection performance. The proposed 4D numerical observer outperformed the other observers for the lesion-detection task in various lesion conditions and motions. CONCLUSIONS: The 4D numerical observer shows substantial improvement in lesion detectability over the 3D observer method. The proposed 4D approach could potentially provide a more reliable objective assessment of the impact of respiratory-gated PET improvement for lesion-detection tasks. On the other hand, the 4D approach may be used as an upper bound to investigate the performance of the motion correction method. In future work, the authors will validate the proposed 4D approach on clinical data for detection tasks in pulmonary oncology.

Impact of temporal resolution on LV myocardial regional strain assessment with real-time 3D ultrasound.

Non-invasive quantification of regional left ventricular (LV) deformation is crucial for the identification of clinical and subclinical myocardial dysfunction in various conditions. Several software tools now exist to provide regional LV strain estimation for echocardiography images. In this paper, we experimentally investigated the impact of real-time three-dimensional (RT3D) ultrasound temporal resolution on the precision of an integrated speckle-tracking framework. We compared temporal displacement and strain profiles acquired at three different frame rates on five normal volunteers. Results showed that estimated displacement fields and regional strain measurements were more homogeneous and of larger amplitude at higher frame rates.

A momentum-based constraint on optical flow tracking of the endocardial surface.

Echocardiography is the standard of care for the evaluation of cardiac function in a variety of clinical scenarios. Despite the increasing availability of RT3D imaging, its utility remains limited due to a lack of tools available to analyze 3D+t datasets. In previous work, we have proposed and validated optical flow as an effective correlation-based technique to track myocardial motion and deformation in RT3D datasets. However, OF's ability to track small regions of tissue (e.g. the endocardial surface) is diminished in less optimal acquisitions. Our goal, therefore, is to develop additional constraints on OF-estimated motion in order to increase the robustness of endocardial surface tracking. We present several modifications to OF-based tracking including motion field smoothing and momentum correction that results in improved OF tracking.

Parameterization of real-time 3D speckle tracking framework for cardiac strain assessment.

Cross-correlation based 3D speckle tracking algorithm can be used to automatically track myocardial motion on three dimensional real-time (RT3D) echocardiography. The goal of this study was to experimentally investigate the effects of different parameters associated with such algorithm to ensure accurate cardiac strain measurements. The investigation was performed on 10 chronic obstructive pulmonary disease RT3DE cardiac ultrasound images. The following two parameters were investigated: 1) the gradient threshold of the anisotropic diffusion pre-filtering and 2) the window size of the cross correlation template matching in the speckle tracking. Results suggest that the optimal gradient threshold of the anisotropic filter depends on the average gradient of the background speckle noise, and that an optimal pair of template size and search window size can be identified determines the cross-correlation level and computational cost.

In-vivo clinical validation of cardiac deformation and strain measurements from 4D ultrasound.

An important goal in clinical cardiology is the non-invasive quantification of regional cardiac deformation. While many methods have been proposed for the estimation of 3D left ventricular deformation and strains derived from 4D ultrasound, currently there is a lack of in vivo clinical validation of these algorithms on humans. In this paper, we describe the experiments used in validating cardiac deformation and strain estimates of 4D ultrasound using correlation-based optical flow tracking on two different COPD patients with normal left ventricular function. Validation of the algorithm was done by 1) validation of cardiac volume across multiple scans of the same patient and 2) validation of the repeatability of cardiac displacement and strain results from multiple scan acquisitions of the same patient. The preliminary results are encouraging with our algorithm producing consistent cardiac volume and strain results across multiple acquisitions. Furthermore, our derived 4D cardiac strains showed qualitatively correct results. We also observed particularly interesting results in the radial displacements of the posterior and lateral walls of our COPD patients.

QUANTITATIVE VALIDATION OF OPTICAL FLOW BASED MYOCARDIAL STRAIN MEASURES USING SONOMICROMETRY.

Dynamic cardiac metrics, including myocardial strains and displacements, provide a quantitative approach to evaluate cardiac function. However, in current clinical diagnosis, largely 2D strain measures are used despite the fact that cardiac motions are complex 3D volumes over time. Recent advances in 4D ultrasound enable the capability to capture such complex motion in a single image data set. In our previous work, a 4D optical flow based motion tracking algorithm was developed to extract fully 4D dynamic cardiac metrics from such 4D ultrasound data. In order to quantitatively evaluate our tracking method, in-vivo coronary artery occlusion experiments at various locations were performed on three canine hearts. Each dog was screened with 4D ultrasound and sonomicrometry data was acquired during each occlusion study. The 4D ultrasound data from these experiments was then analyzed with our tracking method and estimated principal strain measures were directly compared to those recorded by sonomicrometry, and showed strong agreement. This is the first validation study of optical flow based strain estimation for 4D ultrasound with direct comparison with sonomicrometry using in-vivo data.