Citations

Purpose Using common datasets, to estimate and compare the diagnostic performance of image‐based denoising techniques or iterative reconstruction algorithms for the task of detecting hepatic metastases. Methods Datasets from contrast‐enhanced CT scans of the liver were provided to participants in an NIH ‐, AAPM ‐ and Mayo Clinic‐sponsored Low Dose CT Grand Challenge. Training data included full‐dose and quarter‐dose scans of the ACR CT accreditation phantom and 10 patient examinations; both images and projections were provided in the training data. Projection data were supplied in a vendor‐neutral standardized format ( DICOM ‐ CT ‐ PD ). Twenty quarter‐dose patient datasets were provided to each participant for testing the performance of their technique. Images were provided to sites intending to perform denoising in the image domain. Fully preprocessed projection data and statistical noise maps were provided to sites intending to perform iterative reconstruction. Upon return of the denoised or iteratively reconstructed quarter‐dose images, randomized, blinded evaluation of the cases was performed using a Latin Square study design by 11 senior radiology residents or fellows, who marked the locations of identified hepatic metastases. Markings were scored against reference locations of clinically or pathologically demonstrated metastases to determine a per‐lesion normalized score and a per‐case normalized score (a faculty abdominal radiologist established the reference location using clinical and pathological information). Scores increased for correct detections; scores decreased for missed or incorrect detections. The winner for the competition was the entry that produced the highest total score (mean of the per‐lesion and per‐case normalized score). Reader confidence was used to compute a Jackknife alternative free‐response receiver operating characteristic ( JAFROC ) figure of merit, which was used for breaking ties. Results 103 participants from 90 sites and 26 countries registered to participate. Training data were shared with 77 sites that completed the data sharing agreements. Subsequently, 41 sites downloaded the 20 test cases, which included only the 25% dose data ( CTDI vol = 3.0 ± 1.8 mG y, SSDE = 3.5 ± 1.3 mG y). 22 sites submitted results for evaluation. One site provided binary images and one site provided images with severe artifacts; cases from these sites were excluded from review and the participants removed from the challenge. The mean (range) per‐lesion and per‐case normalized scores were −24.2% (−75.8%, 3%) and 47% (10%, 70%), respectively. Compared to reader results for commercially reconstructed quarter‐dose images with no noise reduction, 11 of the 20 sites showed a numeric improvement in the mean JAFROC figure of merit. Notably two sites performed comparably to the reader results for full‐dose commercial images. The study was not designed for these comparisons, so wide confidence intervals surrounded these figures of merit and the results should be used only to motivate future testing. Conclusion Infrastructure and methodology were developed to rapidly estimate observer performance for liver metastasis detection in low‐dose CT examinations of the liver after either image‐based denoising or iterative reconstruction. The results demonstrated large differences in detection and classification performance between noise reduction methods, although the majority of methods provided some improvement in performance relative to the commercial quarter‐dose images with no noise reduction applied.

Abstract Androgen receptor (AR) signaling is a key driver of prostate cancer, and androgen-deprivation therapy (ADT) is a standard treatment for patients with advanced and metastatic disease. However, patients receiving ADT eventually develop incurable castration-resistant prostate cancer (CRPC). Here, we report that the chromatin modifier LSD1, an important regulator of AR transcriptional activity, undergoes epigenetic reprogramming in CRPC. LSD1 reprogramming in this setting activated a subset of cell-cycle genes, including CENPE, a centromere binding protein and mitotic kinesin. CENPE was regulated by the co-binding of LSD1 and AR to its promoter, which was associated with loss of RB1 in CRPC. Notably, genetic deletion or pharmacological inhibition of CENPE significantly decreases tumor growth. Our findings show how LSD1-mediated epigenetic reprogramming drives CRPC, and they offer a mechanistic rationale for its therapeutic targeting in this disease. Cancer Res; 77(20); 5479–90. ©2017 AACR.

Purpose: Abnormal ocular biomechanical properties may be important for understanding the risk of glaucoma. However, there are no clinical methods for measuring standard material properties in patients. In this feasibility study we demonstrated proof-of-principle for a novel method, ultrasound surface wave elastography (USWE), to determine the in vivo Young’s modulus of elasticity of corneas in normal human eyes. Methods: In total, 20 eyes of 10 healthy subjects (mean age, 51.4±7.2; ±SD; range, 43 to 64 y) were studied. A spherical-tipped probe (3-mm diameter) was placed on closed eyelids and generated a gentle harmonic vibration at 100 Hz for 0.1 second. Wave speed propagation in the cornea was measured by USWE, and Young’s modulus was calculated from the wave speed. Associations between Young’s modulus and intraocular pressure (IOP), age, central corneal thickness, and axial length were explored by the Pearson correlation. Statistical significance was determined by using generalized estimating equation models to account for possible correlation between fellow eyes. Results: Mean IOP was 12.8±2.7 mm Hg. Mean wave speed in the cornea was 1.82±0.10 m/s. Young’s modulus of elasticity was 696±113 kPa and was correlated with IOP (r=0.57; P=0.004), but none of the other variables (P>0.1). Conclusions: USWE is a novel noninvasive technique for measuring ocular biomechanical properties. Corneal Young’s modulus in normal eyes is associated with IOP, consistent with measurements in cadaver eyes. Further work is needed to determine elasticity in other ocular tissues, particularly the sclera, and if elasticity is altered in glaucoma patients.

Abstract Photon-counting computed tomography (PCCT) uses a photon counting detector to count individual photons and allocate them to specific energy bins by comparing photon energy to preset thresholds. This enables simultaneous multi-energy CT with a single source and detector. Phantom studies were performed to assess the spectral performance of a research PCCT scanner by assessing the accuracy of derived images sets. Specifically, we assessed the accuracy of iodine quantification in iodine map images and of CT number accuracy in virtual monoenergetic images (VMI). Vials containing iodine with five known concentrations were scanned on the PCCT scanner after being placed in phantoms representing the attenuation of different size patients. For comparison, the same vials and phantoms were also scanned on 2nd and 3rd generation dual-source, dual-energy scanners. After material decomposition, iodine maps were generated, from which iodine concentration was measured for each vial and phantom size and compared with the known concentration. Additionally, VMIs were generated and CT number accuracy was compared to the reference standard, which was calculated based on known iodine concentration and attenuation coefficients at each keV obtained from the U.S. National Institute of Standards and Technology (NIST). Results showed accurate iodine quantification (root mean square error of 0.5 mgI/cc) and accurate CT number of VMIs (percentage error of 8.9%) using the PCCT scanner. The overall performance of the PCCT scanner, in terms of iodine quantification and VMI CT number accuracy, was comparable to that of EID-based dual-source, dual-energy scanners.