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Quantitative Analysis of Airway Tree in Low-dose Chest CT with a New Model-based Iterative Reconstruction Algorithm

Objective

We aimed to evaluate a new model-based iterative reconstruction (MBIRn) algorithm either with spatial resolution and noise reduction balance (MBIR STND ) or spatial resolution preference (MBIR RP20 ) for quantitative analysis of airway in low-dose chest computed tomography (CT) with a computer-aided detection (CAD) software, in comparison to adaptive statistical iterative reconstruction (ASIR) in routine-dose CT.

Methods

Thirty patients who underwent both the routine-dose (noise index [NI] = 14 HU) and low-dose (at 30% level with NI = 28 HU) CT examination for pulmonary disease were included. Image acquisition was performed with 120 kVp tube voltage and automatic tube current modulation. Routine-dose scans were reconstructed with ASIR, whereas low-dose scans were reconstructed with ASIR, MBIR STND , and MBIR RP20 . Airway dimensions of the right middle lobe bronchus from the four reconstructions were measured using CAD software. Two radiologists used a semiquantitative 5 scoring criteria (−2, inferior to; +2, superior to; −1 slightly inferior to; +1, slightly superior to; and 0, equal to ASIR in routine-dose CT) to rate the subjective image quality of MBIR STND and MBIR RP20 of airway trees. The paired t test and Wilcoxon signed-rank test were used for statistical comparison.

Results

The low-dose CT provided 70.76% dose reduction compared to the routine-dose CT (0.88 ± 0.83 mSv vs 3.01 ± 1.89 mSv). MBIR STND and MBIR RP20 with low-dose CT provided longer bronchial length measurements and were better in measurement variability and continuity and completeness of bronchial walls than ASIR in routine-dose CT ( P < .05). MBIR STND was better for subjective noise and MBIR RP20 for showing distal branches .

Conclusions

MBIR STND and MBIR RP20 algorithms provide better airway quantification at 30% of the radiation dose, compared to ASIR at routine-dose CT.

Introduction

Multidetector computed tomography (MDCT) has been widely used for the diagnosis and identification of lung disease, but the potential risk of radiation-induced carcinogenesis, particularly in younger patients, might limit a wider use of this imaging method in clinical practice. Although the introduction of low-dose chest computed tomography (CT) protocols was found effective in detecting peripheral lung cancers and small lung structure in lung , it may be more difficult in low-dose screening with the increased image noise and thin slice thickness.

The isotropic imaging of MDCT makes it possible for imaging-based computer-aided detection (CAD) to provide a three-dimensional automatic approach to identify the airway tree , and to improve the objectivity and repeatability of imaging diagnosis and therefore increase the diagnostic accuracy for lung diseases. However, the image noise, motion artifacts, and partial volume effects caused by the uneven distribution of gray in the airway will lead to distal local wall fracture and segmentation of the bronchioles , and may diffuse to cause leakage in the lung parenchyma when using CAD .

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Material and Methods

General Information

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CT Examinations and Image Reconstruction

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Figure 1, The flow diagram of study selection. ASIR, adaptive statistical iterative reconstruction; CAD, computer-aided detection; CT, computed tomography; MBIR, model-based iterative reconstruction; NI, noise index. (Color version of figure is available online.)

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Quantitative CT Airway Analysis

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Radiation Dose

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Statistical Analysis

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Results

Patient and Lobe Selection

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Subjective Image Quality Scores

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TABLE 1

Subjective Image Quality Scores on CAD for Quantitative Analysis of Airway Trees Reconstructed with ASIR, MBIR STND , and MBIR RP20 in Low-dose Chest CT: Comparisonto Adaptive Statistical Iterative Reconstruction in Routine-dose CT

Comparison to ASIR in Routine-dose CT Number of Scores

(−2/−1/0/1/2) ASIR MBIR STND MBIR RP20 MBIR RP20 vs MBIR STND in Low-dose CT Subjective Image Quality of Airway Trees ASIR MBIR STND MBIR RP20 Z Value_P_ Value_Z_ Value_P_ Value Z Value_P_ Value_Z_ Value_P_ Value Subjective noise Reader 1 30/−0/0/0/0 0/0/0/6/24 0/0/3/9/18 −5.477 † .000 −5.108 \* .000 −4.730 \* .000 −2.310 † .021 Reader 2 30/−0/0/0/0 0/0/0/5/25 0/0/2/9/19 −5.477 † .000 −5.152 \* .000 −4.824 \* .014 −2.530 † .011 Continuity and completeness Reader 1 26/4/0/0/0 0/0/2/7/21 0/0/1/6/23 −5.503 † .000 −4.882 \* .000 −5.014 \* .000 −1.000 \* .317 Reader 2 25/5/0/0/0 0/0/1/6/23 0/0/0/6/24 −5.152 † .000 −5.014 \* .000 −5.108 \* .000 −1.414 \* .157 Bronchial end shows Reader 1 30/−0/0/0/0 0/0/4/15/11 0/0/0/10/20 −5.477 † .000 −4.604 \* .000 −4.983 \* .000 −3.153 \* .002 Reader 2 30/−0/0/0/0 0/0/3/16/11 0/0/0/8/22 −5.477 † .000 −4.696 \* .000 −5.035 \* .000 −3.500 \* .000

ASIR, adaptive statistical iterative reconstruction; CAD, computer-aided detection; CT, computed tomography; MBIR RP20 , model-based iterative reconstruction with spatial resolution; MBIR STND , model-based iterative reconstruction with balance spatial resolution and noise reduction.

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Figure 2, ASIR and MBIR performed on a 60-year-old woman, multiple lungs with small patchy real shadow, consistent with chronic pneumonia. Performance of CAD for quantitative analysis of airway tree in two scans with different reconstruction algorithms and different bronchioles were expressed in different colors. Bronchial truncation (hollow arrow) and leakage (solid arrow) were used to subjectively evaluate bronchial continuity and clarity. (a) ASIR reconstruction in routine-dose CT; (b) ASIR reconstruction in low-dose CT; (c) MBIR RP20 reconstruction in low-dose CT. ASIR, adaptive statistical iterative reconstruction; CAD, computer-aided detection; CT, computed tomography; MBIR, model-based iterative reconstruction; MBIR RP20 , model-based iterative reconstruction with spatial resolution. (Color version of figure is available online.)

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Objective Measurement

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TABLE 2

Measured Right Middle Lobe Bronchus Length (mm) of Airway Trees with Images Reconstructed with ASIR, MBIR STND , and MBIR RP20 in Low-dose CT Compared to ASIR in Routine-dose CT (Mean ± Standard Deviation)

Compared to ASIR in Routine-dose ( P Value) ASIR

(NI = 14) ASIR

(NI = 28) MBIR RP20

(NI = 28) MBIR STND

(NI = 28) ASIR (NI = 28) MBIR RP20 (NI = 28) MBIR STND (NI = 28) Bronchus length 21.54 ± 2.97 19.50 ± 2.60 21.54 ± 3.08 21.76 ± 3.12 0.000 0.937 0.038

ASIR, adaptive statistical iterative reconstruction; CT, computed tomography; MBIR, model-based iterative reconstruction; MBIR RP20 , model-based iterative reconstruction with spatial resolution; MBIR STND , model-based iterative reconstruction with balance spatial resolution and noise reduction; NI, noise index.

Figure 3, ASIR and MBIR performed on a 42-year-old man, left lower lobe soft tissue nodules. Performance of CAD for quantitative analysis of airway tree in two scans with different reconstruction algorithms. (a) ASIR reconstruction in routine-dose CT; (b) ASIR reconstruction in low-dose CT; (c) MBIR RP20 reconstruction in low-dose CT; (d) MBIR STND reconstruction in low-dose CT. The CAD provided CPR, airway tree, and CTVE images. The measured length of the middle lobe bronchus in the right lung from (a) was significantly longer than that in (b), almost the same as that in (c) , but shorter than that in (d) extracted by CAD. ASIR, adaptive statistical iterative reconstruction; CAD, computer-aided detection; CPR, curved planar reconstruction; CT, computed tomography; CTVE, computed tomography virtual endoscopy; MBIR, model-based iterative reconstruction; MBIR RP20 , model-based iterative reconstruction with spatial resolution; MBIR STND , model-based iterative reconstruction with balance spatial resolution and noise reduction; NI, noise index. (Color version of figure is available online.)

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Radiation Doses

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Discussion

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Conclusion

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