Rupert Young

Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage

Abstract The aim was to undertake an initial study of the relationship between texture features in computed tomography (CT) images of non-small cell lung cancer (NSCLC) and tumour glucose metabolism and stage. This retrospective pilot study comprised 17 patients with 18 pathologically confirmed NSCLC. Non-contrast-enhanced CT images of the primary pulmonary lesions underwent texture analysis in 2 stages as follows: (a) image filtration using Laplacian of Gaussian filter to differentially highlight fine to coarse textures, followed by (b) texture quantification using mean grey intensity (MGI), entropy (E) and uniformity (U) parameters. Texture parameters were compared with tumour fluorodeoxyglucose (FDG) uptake (standardised uptake value (SUV)) and stage as determined by the clinical report of the CT and FDG-positron emission tomography imaging. Tumour SUVs ranged between 2.8 and 10.4. The number of NSCLC with tumour stages I, II, III and IV were 4, 4, 4 and 6, respectively. Coarse texture features correlated with tumour SUV (E: r = 0.51, p = 0.03; U: r = −0.52, p = 0.03), whereas fine texture features correlated with tumour stage (MGI: rs = 0.71, p = 0.001; E: rs = 0.55, p = 0.02; U: rs = −0.49, p = 0.04). Fine texture predicted tumour stage with a kappa of 0.7, demonstrating 100% sensitivity and 87.5% specificity for detecting tumours above stage II ( p = 0.0001). This study provides initial evidence for a relationship between texture features in NSCLC on non-contrast-enhanced CT and tumour metabolism and stage. Texture analysis warrants further investigation as a potential method for obtaining prognostic information for patients with NSCLC undergoing CT.

Colorectal Cancer: Texture Analysis of Portal Phase Hepatic CT Images as a Potential Marker of Survival

PURPOSE To assess the utility of texture analysis of liver computed tomographic (CT) images by determining the effect of acquisition parameters on texture and by comparing the abilities of texture analysis and hepatic perfusion CT to help predict survival for patients with colorectal cancer. MATERIALS AND METHODS The study comprised a phantom test and a clinical evaluation of 48 patients with colorectal cancer who had consented to retrospective analysis of hepatic perfusion CT data acquired during a research study approved by the institutional review board. Both components involved texture analysis to quantify the relative contribution of CT features between 2 and 12 pixels wide to overall image brightness and uniformity. The effect of acquisition factors on texture was assessed on CT images of a cylindric phantom filled with water obtained by using tube currents between 100 and 250 mAs and voltages between 80 and 140 kVp. Texture on apparently normal portal phase CT images of the liver and hepatic perfusion parameters were related to patient survival by using Kaplan-Meier survival analysis. RESULTS A texture parameter that compared the uniformity of distribution of CT image features 10 and 12 pixels wide exhibited the least variability with CT acquisition parameters (maximum coefficient of variation, 2.6%) and was the best predictor of patient survival (P < .005). There was no significant association between survival and hepatic perfusion parameters. CONCLUSION The study provides preliminary evidence that analysis of liver texture on portal phase CT images is potentially a superior predictor of survival for patients with colorectal cancer than CT perfusion imaging. SUPPLEMENTAL MATERIAL http://radiology.rsnajnls.org/cgi/content/full/2502071879/DC1.

Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver.

OBJECTIVES To determine whether texture analysis of non-contrast enhanced computed tomography (CT) images in apparently disease-free areas of the liver is altered by the presence of extra- and intra-hepatic malignancy in colorectal cancer patients. MATERIALS AND METHODS Hepatic attenuation and texture were assessed from non-contrast enhanced CT in three groups of colorectal cancer patients: (A) 15 controls with no malignancy; (B) nine patients with extra-hepatic malignancy but no liver involvement; (C) eight patients with hepatic metastases. Regions of interest were manually constructed only over apparently normal areas of liver tissue excluding major blood vessels and areas of intra-hepatic fat, which may otherwise alter CT texture irrespective of the presence of malignancy. Texture was analysed on unfiltered images and following band-pass image filtration to highlight image features at different spatial frequencies (fine: 2 pixels/1.68 mm in width, medium: 6 pixels/5.04 mm and coarse: 12 pixels/10.08 mm). The relative contributions made to the image by features at two different spatial frequencies were expressed as filter ratios (fine/medium, fine/coarse and medium/coarse). Texture was quantified as mean grey-level intensity, entropy and uniformity. RESULTS Texture was not altered on unfiltered images whereas relative texture analysis following image filtration identified differences in fine to medium texture ratios in apparently disease-free areas of the liver in patients with hepatic metastases as compared to patients with no tumour (entropy, p=0.0257) and patients with extra-hepatic disease (uniformity, p=0.0143). CONCLUSIONS Relative texture analysis of unenhanced hepatic CT can reveal changes in apparently disease-free areas of the liver that have previously required more complex perfusion measurements for detection.

Dynamic contrast-enhanced texture analysis of the liver: initial assessment in colorectal cancer.

Purpose:To undertake an initial assessment of the potential utility of dynamic contrast-enhanced texture analysis (DCE-TA) of the liver in patients with colorectal cancer. Materials and Methods:TA comprised measurement of mean gray-level intensity, entropy, and uniformity with and without selective-scale filtration using a band-pass filter to highlight different spatial frequencies reflecting fine, medium, and coarse textures. An initial phantom study assessed the sensitivity of each texture qualifier to computed tomography (CT) acquisition parameters. Texture was analyzed in DCE-CT series from 27 colorectal cancer patients having apparently normal hepatic morphology (node-negative: n = 8, node-positive: n = 19). Averaged changes in hepatic texture induced by contrast material were assessed qualitatively and quantitatively by using kinetic modeling to calculate hepatic perfusion indices following fine, medium, and coarse image filtration. Results:All texture qualifiers were less sensitive to changes in CT acquisition parameters than measurement of CT attenuation. Temporal changes in hepatic texture were qualitatively different from changes in enhancement. Statistically significant differences between node-negative and node-positive patients were observed for at least 1 time period for measurements of hepatic enhancement and for all texture parameters. The differences were most statistically significant and occurred over the greatest number of time periods for fine texture quantified as mean gray-level intensity (5 time periods, minimum P value: 0.006) followed by fine texture quantified as entropy (4 time points, minimum P value: 0.006). There was no difference in hepatic perfusion indices for the 2 groups. Conclusions:DCE-TA is a potentially useful adjunct to DCE-CT warranting further investigation.

A framework for post-event timeline reconstruction using neural networks

Post-event timeline reconstruction plays a critical role in forensic investigation and serves as a means of identifying evidence of the digital crime. We present an artificial neural networks based approach for post-event timeline reconstruction using the file system activities. A variety of digital forensic tools have been developed during the past two decades to assist computer forensic investigators undertaking digital timeline analysis, but most of the tools cannot handle large volumes of data efficiently. This paper looks at the effectiveness of employing neural network methodology for computer forensic analysis by preparing a timeline of relevant events occurring on a computing machine by tracing the previous file system activities. Our approach consists of monitoring the file system manipulations, capturing file system snapshots at discrete intervals of time to characterise the use of different software applications, and then using this captured data to train a neural network to recognise execution patterns of the application programs. The trained version of the network may then be used to generate a post-event timeline of a seized hard disk to verify the execution of different applications at different time intervals to assist in the identification of available evidence.

Fully complex optical modulation with an analogue ferroelectric liquid crystal spatial light modulator

Full complex modulation in the Fourier plane is demonstrated using a 128 x 128 analogue ferroelectric liquid crystal spatial light modulator. The device can modulate along both the positive and negative real axes. Two pixels were used together as a macro pixel, one representing the real component and the other the imaginary component, phase shifted by pi/2 using a phase detour technique. Using this method, a fully complex Fourier spectrum was displayed on the SLM and an asymmetric reconstruction into the first diffraction order was produced. (

Microfabrication by use of a Spatial Light Modulator in the Ultraviolet: Experimental results

We report the development of a new microstereophotolithography technique for creation of three-dimensional microcomponents by use of a planar, layer-by-layer process of exposure, in which a spatial light modulator is used as a dynamic lithographic mask. The system operates in the UV to take advantage of the wide supply of commercially available photopolymers designed for conventional stereolithography. With this novel procedure it is possible to build components with feature sizes as small as a few micrometers. The experimental setup is briefly described, and the first microcomponent fabricated by this system is shown.

UV microstereolithography system that uses spatial light modulator technology

A new stereophotolithography technique utilizing a spatial light modulator (SLM) to create three-dimensional components with a planar, layer-by-layer process of exposure is described. With this procedure it is possible to build components with dimensions in the range of 50 mum-50 mm and feature sizes as small as 5 mum with a resolution of 1 mum. A polysilicon thin-film twisted nematic SVGA SLM is used as the dynamic photolithographic mask. The system consists of eight elements: a UV laser light source, an optical shutter, beam-conditioning optics, a SLM, a multielement reduction lens system, a high-resolution translation stage, a control system, and a computer-aided-design system. Each of these system components is briefly described. In addition, the optical characteristics of commercially available UV curable resins are investigated with nondegenerate four-wave mixing. Holographic gratings were written at a wavelength of 351.1 nm and read at 632.8 nm to compare the reactivity, curing speed, shrinkage, and resolution of the resins. These experiments were carried out to prove the suitability of these photopolymerization systems for microstereolithography.

Position-, rotation-, scale-, and orientation-invariant multiple object recognition from cluttered scenes

A method of detecting target objects in still images despite any kind of geometrical distortion is demonstrated. Two existing techniques are combined, each one capable of creating invariance to various types of distortion of the target object. A maximum average correlation height (MACH) filter is used to create invariance to orientation and gives good tolerance to background clutter and noise. A log r- mapping is employed to give invariance to in-plane rotation and scale by transforming rotation and scale variations of the target object into vertical and horizontal shifts. The MACH filter is trained on the log r- map of the target for a range of orientations and applied sequentially over regions of interest in the input image. Areas producing a strong correlation response can then be used to determine the position, in-plane rotation, and scale of the target objects in the scene.

Two-pixel computer-generated hologram with a zero-twist nematic liquid-crystal spatial light modulator

We present a method of producing a computer-generated hologram by use of a zero-twist linear nematic liquid-crystal spatial light modulator. A 2x1 macro pixel method is used; one pixel represents the real data, and one, the imaginary. A method is shown that produces both positive and negative analog amplitude modulation.