Bi-plane correlation imaging for improved detection of lung nodules

Samei, Ehsan; Catarious, David M.; Baydush, Alan H.; Floyd, Carey E.; Vargas-Voracek, Rene

doi:10.1117/12.480478

Cited by 12 publications

(27 citation statements)

References 28 publications

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“…7,8 This technique uses the unreconstructed angular projections acquired using an approach similar to tomosynthesis. The projection images are similar to standard mammograms, except that each image is acquired with a lower dose level than that in standard full field digital mammography.…”

Section: Introductionmentioning

confidence: 99%

A mathematical model platform for optimizing a multiprojection breast imaging system

et al. 2008

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Multiprojection imaging is a technique in which a plurality of digital radiographic images of the same patient are acquired within a short interval of time from slightly different angles. Information from each image is combined to determine the final diagnosis. Projection data are either reconstructed into slices as in the case of tomosynthesis or analyzed directly as in the case of multiprojection correlation imaging technique, thereby avoiding reconstruction artifacts. In this study, the authors investigated the optimum geometry of acquisitions of a multiprojection breast correlation imaging system in terms of the number of projections and their total angular span that yield maximum performance in a task that models clinical decision. Twenty-five angular projections of each breast from 82 human subjects in our breast tomosynthesis database were each supplemented with a simulated 3 mm mass. An approach based on Laguerre-Gauss channelized Hotelling observer was developed to assess the detectability of the mass in terms of receiver operating characteristic ͑ROC͒ curves. Two methodologies were developed to integrate results from individual projections into one combined ROC curve as the overall figure of merit. To optimize the acquisition geometry, different components of acquisitions were changed to investigate which one of the many possible configurations maximized the area under the combined ROC curve. Optimization was investigated under two acquisition dose conditions corresponding to a fixed total dose delivered to the patient and a variable dose condition, based on the number of projections used. In either case, the detectability was dependent on the number of projections used, the total angular span of those projections, and the acquisition dose level. In the first case, the detectability approximately followed a bell curve as a function of the number of projections with the maximum between 8 and 16 projections spanning angular arcs of about 23°−45°, respectively. In the second case, the detectability increased with the number of projections approaching an asymptote at 11-17 projections for an angular span of about 45°. These results indicate the inherent information content of the multiprojection image data reflecting the relative role of quantum and anatomical noise in multiprojection breast imaging. The optimization scheme presented here may be applied to any multiprojection imaging modalities and may be extended by including reconstruction in the case of digital breast tomosynthesis and breast computed tomography.

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Section: Introductionmentioning

confidence: 99%

A mathematical model platform for optimizing a multiprojection breast imaging system

et al. 2008

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“…Preliminary studies have been performed with phantom and human subject data to assess how correlating suspect lesions from multiple views of a standard CAD algorithm may eliminate false positives [14,[20][21][22]. One of those studies of BCI for lung nodule detection demonstrated a FPs false positives sensitivity of 62.5 %, 1.5 false positives per image, and a 0.885 PPV index [14].…”

Section: Discussionmentioning

confidence: 99%

“…One of those studies of BCI for lung nodule detection demonstrated a FPs false positives sensitivity of 62.5 %, 1.5 false positives per image, and a 0.885 PPV index [14]. The BCI reduced sensitivity by 20 % compared to single-view CAD but also reduced false positives by 94 % yielding a 140 % improvement in the PPV [14]. A multiprojection CAD scheme for the chest was used in a study of phantom and human subject data [22].…”

Section: Discussionmentioning

confidence: 99%

“…2). The system geometry used was studied in previous works which determined the optimal operating angles for acquisition [13,14]. The X-ray tube moves along the horizontal axis to acquire the three images.…”

Section: Methodsmentioning

confidence: 99%

“…The ROC analysis considered the left and right lung as separate entities. Evaluation of the stereoscopic view compared to the PA view was based on three figures of merit which were sensitivity, positive predictive value (PPV) index, and false positives per subject [14].…”

Section: Methodsmentioning

confidence: 99%

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Preliminary Evaluation of Biplane Correlation (BCI) Stereographic Imaging for Lung Nodule Detection

et al. 2012

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A biplane correlation (BCI) imaging system obtains images that can be viewed in stereo, thereby minimizing overlapping structures. This study investigated whether using stereoscopic visualization provides superior lung nodule detection compared to standard postero-anterior (PA) image display. Images were acquired at two oblique views of ±3°as well as at a standard PA position from 60 patients. Images were processed using optimal parameters and displayed on a stereoscopic display. The PA image was viewed in the standard format, while the oblique views were paired to provide a stereoscopic view of the subject. A preliminary observer study was performed with four radiologists who viewed and scored the PA image then viewed and scored the BCI stereoscopic image. The BCI stereoscopic viewing of lung nodules resulted in 71 % sensitivity and 0.31 positive predictive value (PPV) index compared to PA results of 86 % sensitivity and 0.26 PPV index. The sensitivity for lung nodule detection with the BCI stereoscopic system was reduced by 15 %; however, the total number of false positives reported was reduced by 35 % resulting in an improved PPV index of 20 %. The preliminary results indicate observer dependency in terms of relative advantage of either system in the detection of lung nodules, but overall equivalency of the two methods with promising potential for BCI as an adjunct diagnostic technique.

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Biplane Correlation Imaging: A Feasibility Study Based on Phantom and Human Data

et al. 2011

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The objective of this study was to implement and evaluate the performance of a biplane correlation imaging (BCI) technique aimed to reduce the effect of anatomic noise and improve the detection of lung nodules in chest radiographs. Seventy-one low-dose posterior-anterior images were acquired from an anthropomorphic chest phantom with 0.28°a ngular separations over a range of ±10°along the vertical axis within an 11 s interval. Similar data were acquired from 19 human subjects with institutional review board approval and informed consent. The data were incorporated into a computer-aided detection (CAD) algorithm in which suspect lesions were identified by examining the geometrical correlation of the detected signals that remained relatively constant against variable anatomic backgrounds. The data were analyzed to determine the effect of angular separation, and the overall sensitivity and false-positives for lung nodule detection. The best performance was achieved for angular separations of the projection pairs greater than 5°. Within that range, the technique provided an order of magnitude decrease in the number of false-positive reports when compared with CAD analysis of single-view images. Overall, the technique yielded~1.1 false-positive per patient with an average sensitivity of 75%. The results indicated that the incorporation of angular information can offer a reduction in the number of false-positives without a notable reduction in sensitivity. The findings suggest that the BCI technique has the potential for clinical implementation as a cost-effective technique to improve the detection of subtle lung nodules with lowered rate of false-positives.

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Bi-plane correlation imaging for improved detection of lung nodules

Cited by 12 publications

References 28 publications

A mathematical model platform for optimizing a multiprojection breast imaging system

A mathematical model platform for optimizing a multiprojection breast imaging system

Preliminary Evaluation of Biplane Correlation (BCI) Stereographic Imaging for Lung Nodule Detection

Biplane Correlation Imaging: A Feasibility Study Based on Phantom and Human Data

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