Digital tomosynthesis of the chest for lung nodule detection: Interim sensitivity results from an ongoing NIH‐sponsored trial

Dobbins, James T.; McAdams, H. Page; Song, Jaewoo; Li, Christina M.; Godfrey, D; DeLong, David M.; Paik, Sanghyun; Martínez-Jiménez, Santiago

doi:10.1118/1.2937277

Cited by 103 publications

(90 citation statements)

References 8 publications

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“…[8][9][10] Therefore, DTS has been recommended by several authors as an alternative to both chest radiography and CT, and the greater diagnostic performance of DTS for detecting pulmonary nodules has been reported. 9,[11][12][13] However, differences in the diagnostic performance for detection of pulmonary nodules between chest radiography and DTS have not been clearly delineated. Thus, the purpose of this meta-analysis was to compare the diagnostic accuracy of DTS with that of chest radiography for the detection of pulmonary nodules.…”

Section: Introductionmentioning

confidence: 99%

Comparison of digital tomosynthesis and chest radiography for the detection of pulmonary nodules: systematic review and meta-analysis

Kim¹,

Lee²,

Kim³

et al. 2016

The British Journal of Radiology

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Objective: To compare the diagnostic accuracy of digital tomosynthesis (DTS) with that of chest radiography for the detection of pulmonary nodules by meta-analysis. Methods: A systematic literature search was performed to identify relevant original studies from 1 January 1 1976 to 31 August 31 2016. The quality of included studies was assessed by quality assessment of diagnostic accuracy studies-2. Per-patient data were used to calculate the sensitivity and specificity and per-lesion data were used to calculate the detection rate. Summary receiveroperating characteristic curves were drawn for pulmonary nodule detection. Results: 16 studies met the inclusion criteria. 1017 patients on a per-patient basis and 2159 lesions on a per-lesion basis from 16 eligible studies were evaluated. The pooled patient-based sensitivity of DTS was 0.85 [95% confidence interval (CI) 0.83-0.88] and the specificity was 0.95 (0.93-0.96). The pooled sensitivity and specificity of chest radiography were 0.47 (0.44-0.51) and 0.37 (0.34-0.40), respectively. The per-lesion detection rate was 2.90 (95% CI 2.63-3.19). Conclusion: DTS has higher diagnostic accuracy than chest radiography for detection of pulmonary nodules. Chest radiography has low sensitivity but similar specificity, comparable with that of DTS. Advances in knowledge: DTS has higher diagnostic accuracy than chest radiography for the detection of pulmonary nodules.

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Section: Introductionmentioning

confidence: 99%

Comparison of digital tomosynthesis and chest radiography for the detection of pulmonary nodules: systematic review and meta-analysis

Kim¹,

Lee²,

Kim³

et al. 2016

The British Journal of Radiology

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“…With respect to images of similar-sized nodules, the contrast was greater when DT imaging was used for processing than when radiography was used [27][28][29]. In the observer study, there was no statistically significant difference between DT and CT; moreover, with regard to DI, CT and DT were similar.…”

Section: Discussionmentioning

confidence: 73%

Comparison between chest digital tomosynthesis and CT as a screening method to detect artificial pulmonary nodules: a phantom study

Gomi¹,

Nakajima²,

Fujiwara³

et al. 2012

BJR

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Objectives: The objective of this study was to evaluate the imaging capabilities of chest digital tomosynthesis (DT) as a screening method for the detection of artificial pulmonary nodules, and to compare its efficiency with that of CT. Methods: DT and CT were used to detect artificial pulmonary nodules (5 mm and 8 mm in diameter, ground-glass opacities) placed in a chest phantom. Using a threedimensional filtered back-projection algorithm at acquisition angles of 8 u , 20 u , 30 u and 40 u , DT images of the desired layer thicknesses were reconstructed from the image data acquired during a single tomographic scan. Both standard and sharp CT reconstruction kernels were used, and the detectability index (DI) valves computed for both the DT scan acquisition angles and CT reconstruction kernel types were considered. For the observer study, we examined 50 samples of artificial pulmonary nodules using both DT and CT imaging. On the basis of evaluations made by five thoracic radiologists, a jackknife free-response receiver operating characteristic (JAFROC) study was performed to compare and assess the differences in detection accuracy between CT and DT imaging. Results: For each increased acquisition angle, DI obtained by DT imaging was similar to that obtained by CT imaging. The difference in the observer-averaged JAFROC figure of merit for the five readings was 0.0363 (95% confidence interval: 20.18, 0.26; F50.101; p50.75). Conclusion: With the advantages of a decreased radiation dose and the practical accessibility of examination, DT may be a useful alternative to CT for the detection of artificial pulmonary nodules. Detecting and characterising pulmonary nodules is one of the most challenging tasks in thoracic imaging; even experienced chest radiologists may miss up to 30% of such lesions on conventional chest radiographs [1]. Nodules are often only retrospectively visible while reviewing previous images of patients with a known history of nodules [2], and identifying them prospectively remains a difficult task. Because of its high sensitivity, normal-dose helical CT is currently considered as the standard method for the diagnosis of lung cancer. Early reports indicate that low-dose helical CT has the potential to detect lung cancer in the initial stage, thus decreasing morbidity [3]. In addition, CT solves the problem of impaired visibility caused by overlapping anatomical structures, which leads to lower detection rates.X-ray CT has progressed over the last three decades, and it now constitutes a powerful tool for medical diagnosis. The use of CT as a non-invasive imaging technique has become essential, especially since the advent of spiral CT in the 1990s, which led to shorter scan times and improved three-dimensional (3D) spatial resolution. Although CT provides high resolution in the tomographic plane, it has limited axial resolution. Therefore, the partial-volume effect (PVE) may make it difficult to evaluate structures that are not oriented in the direction of the CT tomographic plane.CT-particularly high-r...

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“…Given these results, we believe that the MITSa7 method is an improvement over traditional MITS for thoracic imaging and the pulmonary nodule detection task, and have selected the MITSa7 approach for use in all future research using MITS at our institution. 4 …”

Section: Discussionmentioning

confidence: 99%

“…4,[12][13][14][15][16][17][18] The focus of the method is an attempt to separate true in-plane detail from undesirable tomographic blur in a set of conventional tomosynthesis (also known as "shift-and-add" or backprojection) reconstructed planes, oriented parallel to the image receptor. MITS models the conventional tomosynthesis blurring process by introducing a set of impulse response functions which describe how detail in each plane is blurred onto all of the other tomosynthesis planes during the backprojection process.…”

Section: Iia Mits Overviewmentioning

confidence: 99%

“…2, 3 Preliminary investigations into the use of tomosynthesis for chest imaging suggest that tomosynthesis is significantly superior to conventional radiographic imaging for the detection of both pulmonary nodules [4][5][6][7][8] and pulmonary mycobacterial lesions. 9 Anatomic detail in conventional backprojection (shift-andadd) tomosynthesis is obscured by tomographic blur from structures located outside the plane of interest.…”

Section: Introductionmentioning

confidence: 99%

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The effect of averaging adjacent planes for artifact reduction in matrix inversion tomosynthesis

2013

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Purpose: Matrix inversion tomosynthesis (MITS) uses linear systems theory and knowledge of the imaging geometry to remove tomographic blur that is present in conventional backprojection tomosynthesis reconstructions, leaving in-plane detail rendered clearly. The use of partial-pixel interpolation during the backprojection process introduces imprecision in the MITS modeling of tomographic blur, and creates low-contrast artifacts in some MITS planes. This paper examines the use of MITS slabs, created by averaging several adjacent MITS planes, as a method for suppressing partialpixel artifacts. Methods: Human chest tomosynthesis projection data, acquired as part of an IRB-approved pilot study, were used to generate MITS planes, three-plane MITS slabs (MITSa3), five-plane MITS slabs (MITSa5), and seven-plane MITS slabs (MITSa7). These were qualitatively examined for partialpixel artifacts and the visibility of normal and abnormal anatomy. Additionally, small (5 mm) subtle pulmonary nodules were simulated and digitally superimposed upon human chest tomosynthesis projection images, and their visibility was qualitatively assessed in the different reconstruction techniques. Simulated images of a thin wire were used to generate modulation transfer function (MTF) and slice-sensitivity profile curves for the different MITS and MITS slab techniques, and these were examined for indications of partial-pixel artifacts and frequency response uniformity. Finally, meansubtracted, exposure-normalized noise power spectra (ENNPS) estimates were computed and compared for MITS and MITS slab reconstructions, generated from 10 sets of tomosynthesis projection data of an acrylic slab. The simulated in-plane MTF response of each technique was also combined with the square root of the ENNPS estimate to yield stochastic signal-to-noise ratio (SNR) information about the different reconstruction techniques. Results: For scan angles of 20• and 5 mm plane separation, seven MITS planes must be averaged to sufficiently remove partial-pixel artifacts. MITSa7 does appear to subtly reduce the contrast of highfrequency "edge" information, but the removal of partial-pixel artifacts makes the appearance of low-contrast, fine-detail anatomy even more conspicuous in MITSa7 slices. MITSa7 also appears to render simulated subtle 5 mm pulmonary nodules with greater visibility than MITS alone, in both the open lung and regions overlying the mediastinum. Finally, the MITSa7 technique reduces stochastic image variance, though the in-plane stochastic SNR (for very thin objects which do not span multiple MITS planes) is only improved at spatial frequencies between 0.05 and 0.20 cycles/mm. Conclusions: The MITSa7 method is an improvement over traditional single-plane MITS for thoracic imaging and the pulmonary nodule detection task, and thus the authors plan to use the MITSa7 approach for all future MITS research at the authors' institution.

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Digital tomosynthesis of the chest for lung nodule detection: Interim sensitivity results from an ongoing NIH‐sponsored trial

Cited by 103 publications

References 8 publications

Comparison of digital tomosynthesis and chest radiography for the detection of pulmonary nodules: systematic review and meta-analysis

Comparison of digital tomosynthesis and chest radiography for the detection of pulmonary nodules: systematic review and meta-analysis

Comparison between chest digital tomosynthesis and CT as a screening method to detect artificial pulmonary nodules: a phantom study

The effect of averaging adjacent planes for artifact reduction in matrix inversion tomosynthesis

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