We selected several image density indices to establish CAD for prediction of biopsy in lung diseases. Our results suggested that significant difference was not observed in the image density indices between bilateral lungs at each slice level. Our own designed image indices may be reliable parameters in the establishment of CAD system and pathologic diagnosis for lung disease [1,2].
CAD, Density index, Histogram, Frequency, Entropy
There has been a rapid progress in the modality of CT since it was developed by Mr. Hounsfield. The earlier CT had been upgraded to the helical CT and for the time being the MDCT is widely used in the radiology practice. The up-to-dated MDCT is supported by the detectors of 64 rows or more [3-5].
The slice thickness of CT has been reached to 0.1 mm, based on the noble high resolution it reflects the indirect the pathological findings and enables working on the algorithm and image density index anticipating the pathological diagnosis. Some researchers reported the characteristics of image density in healthy lungs using the various indices including the mean value, standard deviation, maximum in the region of interesting [6-8].
Recently, the free service of MDCT is provided for diagnosis of patients at some health facilities. Taking the advantage of the high resolution, we have selected the new quantitative index of image density other than HU and obtained the basic data for CAD and prediction of the pathological findings in lung diseases [9,10].
We analyzed the CT findings of 40 males and 40 females without respiratory symptoms and abnormal X-ray findings.
The findings of target group was disaggregated by sex and analyzed.
And we selected the image density index and compare the index results of the bilateral lungs at the level of vertebrae thoracales from No. 1 to 8.
Each image density indices were evaluated when setting range of HU from 0 to 5000 instead of -1000 to 4000.
1. The indices were selected to quantitatively evaluate the image density.
Density grade is Density ratio of interior half and exterior half of healthy lung
Average value of energy
Mf = Sf/Ly
Sf : Integration of quarter division of spectrum
Ly: Area of quarter division of spectrum
Average range ratio of high frequency and low frequency
Cf = Hf/Lf
Cf is the average range ratio of high frequency and low frequency of the regions in healthy lungs.
Hf: Average range of high frequency
Lf: Average range of low frequency
Histogram of parenchyma of healthy lungs
Rh = Hmax−Hmin
Hmax: Maximum density of histogram
Hmin: Minimum density of histogram
Average histogram value of healthy lung parenchyma
Mh = Th/Rh
Th: Total value of histogram
Rh: Range of histogram
Entropy
Entropy = ∑L−1It=0p(Zi) log2P(Zi)
2. The value of image density indices of bilateral lungs at each level of vertebrae thoracales are shown in the tables below.
As mentioned above, the quantitative indices have been newly identified to indicate the characteristics of image density of healthy lungs. Subsequently the diagnostic algorithm was drafted to compare the image density of ill lung and healthy lung at slice levels.
According to the results of study on image density of healthy lungs at the level of vertebrae thoracales from No. 1 to 8, the significant deviation was observed in the histogram at the level of vertebrae thoracales from No. 4 to 8, though not observed in the density grade, ratio of high frequency and low frequency, average frequency, histogram and entropy.
We could note that the comparison of image density of healthy and ill lungs at the appropriate slice level would be one of key approaches to anticipate the pathological diagnosis regarding the values of the indices vary from disease to disease.
The quantitative indices have been newly identified to indicate the characteristics of image density of healthy lungs. The significant deviation was observed in the histogram at the level of vertebrae thoracales from No. 4 to 8, though not observed in the density grade, ratio of high frequency and low frequency, average frequency, histogram and entropy.