Model-based detection of spiculated lesions in mammograms

R. Zwiggelaar, T.C. Parr, J.E. Schumm. I.W. Hutt, S.M. Astley, C.J. Taylor and C.R.M. Boggis, 'Model-based detection of spiculated lesions in mammograms', Medical Image Analysis 3 (1), 39-62 (1999)

On Finding Sensitivity of Quantum and Classical Gates

We consider a fault model of Boolean gates, both classical and quantum, where some of the inputs may not be connected to the actual gate hardware. This model is somewhat similar to the stuck-at model which is a very popular model in testing Boolean circuits. We consider the problem of detecting such faults; the detection algorithm can query the faulty gate and its complexity is the number of such queries. This problem is related to determining the sensitivity of Boolean functions. We show how quantum parallelism can be used to detect such faults. Specifically, we show that a quantum algorithm can detect such faults more efficiently than a classical algorithm for a Parity gate and an AND gate. We give explicit constructions of quantum detector algorithms and show lower bounds for classical algorithms. We show that the model for detecting such faults is similar to algebraic decision trees and extend some known results from quantum query complexity to prove some of our results.

Application of signal detection methods to fisheries management

The abundance of many commercially important fish stocks are declining and this has led to widespread concern on the performance of traditional approach in fisheries management. Quantitative models are used for obtaining estimates of population abundance and the management advice is based on annual harvest levels (TAC), where only a certain amount of catch is allowed from specific fish stocks. However, these models are data intensive and less useful when stocks have limited historical information. This study examined whether empirical stock indicators can be used to manage fisheries. The relationship between indicators and the underlying stock abundance is not direct and hence can be affected by disturbances that may account for both transient and persistent effects. Methods from Statistical Process Control (SPC) theory such as the Cumulative Sum (CUSUM) control charts are useful in classifying these effects and hence they can be used to trigger management response only when a significant impact occurs to the stock biomass. This thesis explores how empirical indicators along with CUSUM can be used for monitoring, assessment and management of fish stocks. I begin my thesis by exploring various age based catch indicators, to identify those which are potentially useful in tracking the state of fish stocks. The sensitivity and response of these indicators towards changes in Spawning Stock Biomass (SSB) showed that indicators based on age groups that are fully selected to the fishing gear or Large Fish Indicators (LFIs) are most useful and robust across the range of scenarios considered. The Decision-Interval (DI-CUSUM) and Self-Starting (SS-CUSUM) forms are the two types of control charts used in this study. In contrast to the DI-CUSUM, the SS-CUSUM can be initiated without specifying a target reference point (‘control mean’) to detect out-of-control (significant impact) situations. The sensitivity and specificity of SS-CUSUM showed that the performances are robust when LFIs are used. Once an out-of-control situation is detected, the next step is to determine how much shift has occurred in the underlying stock biomass. If an estimate of this shift is available, they can be used to update TAC by incorporation into Harvest Control Rules (HCRs). Various methods from Engineering Process Control (EPC) theory were tested to determine which method can measure the shift size in stock biomass with the highest accuracy. Results showed that methods based on Grubb’s harmonic rule gave reliable shift size estimates. The accuracy of these estimates can be improved by monitoring a combined indicator metric of stock-recruitment and LFI because this may account for impacts independent of fishing. The procedure of integrating both SPC and EPC is known as Statistical Process Adjustment (SPA). A HCR based on SPA was designed for DI-CUSUM and the scheme was successful in bringing out-of-control fish stocks back to its in-control state. The HCR was also tested using SS-CUSUM in the context of data poor fish stocks. Results showed that the scheme will be useful for sustaining the initial in-control state of the fish stock until more observations become available for quantitative assessments.

Effective detection of celiac disease using salivary anti-transglutaminase.

Comment

Sensitivity of HER-2/neu antibodies in archival tissue samples of invasive breast carcinomas. Correlation with oncogene amplification in 160 cases.

Overexpression and amplification of the HER-2 oncogene in patients with breast cancer has correlated with early onset of metastasis, resistance to hormonal therapy and some forms of chemotherapy, and shortened survival. Therefore, evaluation of this putative prognostic or predictive factor seems critical. Because different antibodies are used for the detection of the 185-kd HER-2 oncoprotein, we studied the sensitivity of 3 frequently used antibodies. Immunohistochemistry results were correlated with gene amplification level as assessed by fluorescence in situ hybridization. Protein overexpression was found in 17.2% and 12.5% of cases using antibodies against the external (TAB250) and internal (CB11) domains of the protein, respectively, and in 38.0% of cases using a rabbit polyclonal antibody. Fluorescence in situ hybridization was successful in all 160 tumors, and amplification was found in 37 tumors (23.1%). The monoclonal antibody TAB250 had the lowest misclassification rate, 9.6% (sensitivity, 67%; specificity, 97.5%).

Sensitive detection of H2S using gold nanoparticle decorated single-walled carbon nanotubes.

Herein, we demonstrate that highly sensitive conductometric gas nanosensors for H(2)S can be synthesized by electrodepositing gold nanoparticles on single-walled carbon nanotube (SWNT) networks. Adjusting the electrodeposition conditions allowed for tuning of the size and number of gold nanoparticles deposited. The best H(2)S sensing performance was obtained with discrete gold nanodeposits rather than continuous nanowires. The gas nanosensors could sense H(2)S in air at room temperature with a 3 ppb limit of detection. The sensors were reversible, and increasing the bias voltage reduced the sensor recovery time, probably by local Joule heating. The sensing mechanism is believed to be based on the modulation of the conduction path across the nanotubes emanating from the modulation of electron exchange between the gold and carbon nanotube defect sites when exposed to H(2)S.

Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma.

Intraoperative assessment of surgical margins is critical to ensuring residual tumor does not remain in a patient. Previously, we developed a fluorescence structured illumination microscope (SIM) system with a single-shot field of view (FOV) of 2.1 × 1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The goal of this study was to test the utility of this technology for the detection of residual disease in a genetically engineered mouse model of sarcoma. Primary soft tissue sarcomas were generated in the hindlimb and after the tumor was surgically removed, the relevant margin was stained with acridine orange (AO), a vital stain that brightly stains cell nuclei and fibrous tissues. The tissues were imaged with the SIM system with the primary goal of visualizing fluorescent features from tumor nuclei. Given the heterogeneity of the background tissue (presence of adipose tissue and muscle), an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images to specifically segment nuclear features. A logistic regression model was used to classify a tissue site as positive or negative by calculating area fraction and shape of the segmented features that were present and the resulting receiver operator curve (ROC) was generated by varying the probability threshold. Based on the ROC curves, the model was able to classify tumor and normal tissue with 77% sensitivity and 81% specificity (Youden's index). For an unbiased measure of the model performance, it was applied to a separate validation dataset that resulted in 73% sensitivity and 80% specificity. When this approach was applied to representative whole margins, for a tumor probability threshold of 50%, only 1.2% of all regions from the negative margin exceeded this threshold, while over 14.8% of all regions from the positive margin exceeded this threshold.

Finite element modelling of crack detection tests

Four non-destructive tests for determining the length of fatigue cracks within the solder joints of a 2512 surface mount resistor are investigated. The sensitivity of the tests is obtained using finite element analysis with some experimental validation. Three of the tests are mechanically based and one is thermally based. The mechanical tests all operate by applying different loads to the PCB and monitoring the strain response at the top of the resistor. The thermal test operates by applying a heat source underneath the PCB, and monitoring the temperature response at the top of the resistor. From the modelling work done, two of these tests have shown to be sensitive to cracks. Some experimental results are presented but further work is required to fully validate the simulation results.

Theoretical analysis of ocean color radiances anomalies and implications for phytoplankton groups detection in case 1 waters

Past years have seen the development of different approaches to detect phytoplankton groups from space. One of these methods, the PHYSAT one, is empirically based on reflectance anomalies. Despite observations in good agreement with in situ measurements, the underlying theoretical explanation of the method is still missing and needed by the ocean color community as it prevents improvements of the methods and characterization of uncertainties on the inversed products. In this study, radiative transfer simulations are used in addition to in situ measurements to understand the organization of the signals used in PHYSAT. Sensitivity analyses are performed to assess the impact of the variability of the following three parameters on the reflectance anomalies: specific phytoplankton absorption, colored dissolved organic matter absorption, and particles backscattering. While the later parameter explains the largest part of the anomalies variability, results show that each group is generally associated with a specific bio-optical environment which should be considered to improve methods of phytoplankton groups detection.

Detection and impacts of leakage from sub-seafloor deep geological carbon dioxide storage

Fossil fuel power generation and other industrial emissions of carbon dioxide are a threat to global climate1, yet many economies will remain reliant on these technologies for several decades2. Carbon dioxide capture and storage (CCS) in deep geological formations provides an effective option to remove these emissions from the climate system3. In many regions storage reservoirs are located offshore4, 5, over a kilometre or more below societally important shelf seas6. Therefore, concerns about the possibility of leakage7, 8 and potential environmental impacts, along with economics, have contributed to delaying development of operational CCS. Here we investigate the detectability and environmental impact of leakage from a controlled sub-seabed release of CO2. We show that the biological impact and footprint of this small leak analogue (<1 tonne CO2 d−1) is confined to a few tens of metres. Migration of CO2 through the shallow seabed is influenced by near-surface sediment structure, and by dissolution and re-precipitation of calcium carbonate naturally present in sediments. Results reported here advance the understanding of environmental sensitivity to leakage and identify appropriate monitoring strategies for full-scale carbon storage operations.

Detection and impacts of leakage from sub-seafloor deep geological carbon dioxide storage

Fossil fuel power generation and other industrial emissions of carbon dioxide are a threat to global climate1, yet many economies will remain reliant on these technologies for several decades2. Carbon dioxide capture and storage (CCS) in deep geological formations provides an effective option to remove these emissions from the climate system3. In many regions storage reservoirs are located offshore4, 5, over a kilometre or more below societally important shelf seas6. Therefore, concerns about the possibility of leakage7, 8 and potential environmental impacts, along with economics, have contributed to delaying development of operational CCS. Here we investigate the detectability and environmental impact of leakage from a controlled sub-seabed release of CO2. We show that the biological impact and footprint of this small leak analogue (<1 tonne CO2 d−1) is confined to a few tens of metres. Migration of CO2 through the shallow seabed is influenced by near-surface sediment structure, and by dissolution and re-precipitation of calcium carbonate naturally present in sediments. Results reported here advance the understanding of environmental sensitivity to leakage and identify appropriate monitoring strategies for full-scale carbon storage operations.

Global and local contributions to the optical specification of time to contact: Observer sensitivity to composite tau

First-order time remaining until a moving observer will pass an environmental element is optically specified in two different ways. The specification provided by global tau (based on the pattern of change of angular bearing) requires that the element is stationary and that the direction of motion is accurately detected, whereas the specification provided by composite tau (based on the patterns of change of optical size and optical distance) does not require either of these. We obtained converging evidence,for our hypothesis. that observers are sensitive to composite tau in four experiments involving, relative judgments of, time to, passage with forced-choice methodology. Discrimination performance was enhanced in the presence of a local expansion component, while being unaffected when the detection of the direction of heading was impaired. Observers relied on the information carried in composite tau rather than on the information carried in its constituent components. Finally, performance was similar under conditions of observer motion and conditions of object motion. Because composite tau specifies first-order time remaining for a large number of situations, the different ways in which it may be detected are discussed.

Paralytic shellfish poisoning detection by surface plasmon resonance-based biosensors in shellfish matrixes.

The detection of paralytic shellfish poisoning (PSP) toxins in contaminated shellfish is essential for human health preservation. Ethical and technical reasons have prompted the search for new detection procedures as an alternative to the mouse bioassay. On the basis of the detection of molecular interactions by surface plasmon resonance (SPR) biosensors, an inhibition assay was developed using an anti-GTX2/3 antibody (GT13-A) and a saxitoxin-CM5 chip. This assay allowed for quantification of saxitoxin (STX), decarbamoyl saxitoxin (dcSTX), gonyautoxin 2,3 (GTX2/3), decarbamoyl gonyautoxin 2,3 (dcGTX2/3), gonyautoxin 5 (GTX5), and C 1,2 (C1/2) at concentrations from 2 to 50 ng/mL. The interference of five shellfish matrixes with the inhibition assay was analyzed. Mussels, clams, cockles, scallops, and oysters were extracted with five published methods. Ethanol extracts and acetic acid/heat extracts (AOAC Lawrence method) performed adequately in terms of surface regeneration and baseline interference, did not inhibit antibody binding to the chip surface significantly, and presented STX calibration curves similar to buffer controls in all matrixes tested. Hydrochloric acid/heat extracts (AOAC mouse bioassay method) presented surface regeneration problems, and although ethanol-acetic acid/dichloromethane extracts performed well, they were considered too laborious for routine sample testing. Overall the best results were obtained with the ethanol extraction method with calibration curves prepared in blank matrix extracts. STX recovery rate with the ethanol extraction method was 60.52 ± 3.72%, with variations among species. The performance of this biosensor assay in natural samples, compared to two AOAC methods for PSP toxin quantification (mouse bioassay and HPLC), suggests that this technology can be useful as a PSP screening assay. In summary, the GT13-A-STX chip inhibition assay is capable of PSP toxin detection in ethanol shellfish extracts, with sufficient sensitivity to quantify the toxin in the range of the European regulatory limit of 80 g/100 g of shellfish meat.

Enhanced Nanoparticle Detection with Liquid Droplet Resonators

Whispering gallery mode particle sensing experiments are commonly performed with solid resonators, whereby the sensing volume is limited to the weak evanescent tail of the mode near the resonator surface. In this work we discuss in detail the sensitivity enhancements achievable in liquid droplet resonators wherein the stronger internal fields and convenient means of particle delivery can be exploited. Asymptotic formulae are derived for the relative resonance shift, line broadening and mode splitting of TE and TM modes in liquid droplet resonators. As a corollary the relative fraction of internal and external mode energy follows, which is shown to govern achievable sensitivity enhancements of solute concentration measurements in droplet sensors. Experimental measurements of nanoparticle concentration based on whispering gallery mode resonance broadening are also presented.

Specific and sensitive detection of Nosema bombi (Microsporidia : Nosematidae) in bumble bees (Bombus spp.; Hymenoptera : Apidae) by PCR of partial rRNA gene sequences

A polymerase chain reaction (PCR) based method was developed for the specific and sensitive diagnosis of the microsporidian parasite Nosema bombi in bumble bees (Bombus spp.). Four primer pairs, amplifying ribosomal RNA (rRNA) gene fragments, were tested on N. bombi and the related microsporidia Nosema apis and Nosema ceranae, both of which infect honey bees. Only primer pair Nbombi-SSU-Jf1/Jr1 could distinguish N. bombi (323 bp amplicon) from these other bee parasites. Primer pairs Nbombi-SSU-Jf1/Jr1 and ITS-f2/r2 were then tested for their sensitivity with N. bombi spore concentrations from 107 down to 10 spores diluted in 100 mu l of either (i) water or (ii) host bumble bee homogenate to simulate natural N. bombi infection (equivalent to the DNA from 10(6) spores down to 1 spore per PCR). Though the N. bombi-specific primer pair Nbombi-SSU-Jf1/Jr1 was relatively insensitive, as few as 10 spores per extract (equivalent to 1 spore per PCR) were detectable using the N. bombi-non-specific primer pair ITS-f2/r2, which amplifies a short fragment of similar to 120 bp. Testing 99 bumble bees for N. bombi infection by light microscopy versus PCR diagnosis with the highly sensitive primer pair ITS-f2/r2 showed the latter to b more accurate. PCR diagnosis of N. bombi using a combination of two primer pairs (Nbombi-SSU-Jf1/Jr1 and ITS-f2/r2) provides increased specificity, sensitivity, and detection of all developmental stages compared with light microscopy. (c) 2005 Elsevier Inc. All rights reserved.