Tumor volume measurement error using computed tomography imaging in a phase II clinical trial in lung cancer

Abstract

Abstract. To address the error introduced by computed tomography (CT) scanners when assessing volume and unidimensional measurement of solid tumors, we scanned a precision manufactured pocket phantom simultaneously with patients enrolled in a lung cancer clinical trial. Dedicated software quantified bias and random error in the X ; Y , and Z dimensions of a Teflon sphere and also quantified response evaluation criteria in solid tumors and volume measurements using both constant and adaptive thresholding. We found that underestimation bias was essentially the same for X ; Y , and Z dimensions using constant thresholding and had similar values for adaptive thresholding. The random error of these length measurements as measured by the standard deviation and coefficient of variation was 0.10 mm (0.65), 0.11 mm (0.71), and 0.59 mm (3.75) for constant thresholding and 0.08 mm (0.51), 0.09 mm (0.56), and 0.58 mm (3.68) for adaptive thresholding, respectively. For random error, however, Z lengths had at least a fivefold higher standard deviation and coefficient of variation than X and Y . Observed Z -dimension error was especially high for some 8 and 16 slice CT models. Error in CT image formation, in particular, for models with low numbers of detector rows, may be large enough to be misinterpreted as representing either treatment response or disease progression.

Generation of realistic virtual nodules based on three‐dimensional spatial resolution in lung computed tomography: A pilot phantom study

“…This method potentially overcomes the limitations of previous simulation techniques for pulmonary nodules. [4][5][6][7][8][9][10][11][13][14][15][16][17][18]21 Our proposed method includes direct deconvolution by division of spatial frequencies. This analysis is essentially the same as a common image deblurring (or restoration).…”

“…Three types of simulation techniques are currently in use. The first technique is utilization of physical nodules contained in a lung phantom . Although this technique has been widely used, it is difficult to build a large set of different physical phantoms that will realistically cover all variations in the anatomical structures and nodule characteristics within an entire patient population.…”

“…These pulmonary nodule-simulating techniques have been widely applied not only in investigations of the influence of the radiation dose but also in various studies that were difficult to perform with human subjects. [5][6][7][8][9][10][11] In addition, Huo et al 12 discussed the importance and necessity of quality assurance of computer-aided detection/diagnosis systems used for lung cancer CT screening; for this purpose, they suggested the application of simulated nodules. The development of techniques with which to simulate pulmonary nodules has become an important research interest.…”

“…The first technique is utilization of physical nodules contained in a lung phantom. [5][6][7][8][9] Although this technique has been widely used, it is difficult to build a large set of different physical phantoms that will realistically cover all variations in the anatomical structures and nodule characteristics within an entire patient population. In the second technique, the nodules segmented from one patient's images are digitally inserted into another patient's images.…”

The impact of respiratory gating on improving volume measurement of murine lung tumors in micro-CT imaging

“…Additionally, we evaluated the utility of retrospectively gated images as an alternative to prospective gating with reduced scan time. Finally, we have designed a clinically-inspired "pocket phantom" (i.e., a reference standard) for external use during scanning to aid in assessing gating protocols [7]. We performed a series of in vivo scans on tumor-bearing mice while varying the animal's position (test-retest), and performing the analyses in triplicate (repeated measures) to assess the effects of gating on tumor detection and volumetric assessment.…”