Aims and objectives
The bone suppression technique based on advanced image processing can suppress the conspicuity of bones on chest radiographs,
creating soft tissue images normally obtained by the dual-energy subtraction technique [1,2].
As bone suppression images are generated in a post-processing step,
no special hardware or double exposures as required in dual energy radiography are needed.
The bone suppression technique has already been commercially developed and was shown to improve radiologists’ accuracy for detecting lung nodules [3,4].
However,
this technique has not been applied to dynamic chest...
Methods and materials
Subjects
The study population consisted of 61 (abnormal,
n=33; normal,
n=28) patients.
The abnormal cases had been diagnosed with pulmonary diseases such as emphysema,
asthma,
interstitial pneumonia,
pulmonary fibrosis,
and pleural adhesions based on clinical and examination findings,
including 5 patients with unilateral ventilatory impairments.
The normal controls had no underlying pulmonary diseases or smoking history,
and they were confirmed to be normal based on chest radiographs and the results of pulmonary functional test.
Image acquisition
Posterior–anterior (PA) dynamic chest radiographs consisting of 30 frames...
Results
In normal controls,
color map images showed a left-right symmetric distribution increasing from the lung apex to the bottom region of the lung,
showing statistically-significant difference (P<0.05).
In addition,
there was a high correlation in respiratory changes in pixel values among both lungs (r=0.97) (Fig.
4).
In contrast,
many abnormal cases showed a nonuniform distribution on color map images that differed from the normal pattern.
The areas with decreased changes in pixel values were confirmed to correspond to ventilation defect areas found on the pulmonary...
Conclusion
Dynamic analysis of bone suppression images could detect pulmonary impairment as areas with decreased changes in pixel value.
Our results indicated that quantitative analysis of respiratory changes in pixel values could predict a pulmonary function in lung unit.
The present method is a potential functional imaging for use in daily clinical practice.
Further studies are required to investigate a local evaluation in many clinical cases.
Personal information
Rie Tanaka,
PhD
Department of Radiological Technology,
School of Health Sciences,
College of Medical,Pharmaceutical and Health Sciences,
Kanazawa University; Kanazawa,
Japan
[email protected]
---
Acknowledgement
This work was partially supported by the Mitsubishi Foundation,
the Mitani Foudation,
Grant-in-aid for Scientific Research (C) of Ministry of Education,
Culture,
Sports,
Science and Technology,
JAPAN (Grant number : 24601007),
and Canon Inc.,
Tokyo,
Japan.
Authors are thankful for the technical support of Staffs at Dept.
of Radiology,
Kanazawa university hospital.
References
Suzuki K,
Abe H,
MacMahon H et al.
Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN).
IEEE Trans Med Imaging 2006;25:406-416.
Hogeweg L,
Sánchez CI,
van Ginneken B.
Suppression of translucent elongated structures: applications in chest radiography.
IEEE Transactions on Medical Imaging 2013;32:2099-2113.
Freedman MT,
Lo SC,
Seibel JC,
et al.
Lung nodules: improved detection with software that suppresses the rib and clavicle on chest radiographs.
Radiology 2011;260:265–273.
Li F,
Hara T,
Shiraishi J,
et al....