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Characterizing anatomical variability in breast CT images.

ABSTRACT: Previous work [Burgess et al., Med. Phys. 28, 419-437 (2001)] has shown that anatomical noise in projection mammography results in a power spectrum well modeled over a range of frequencies by a power law, and the exponent (beta) of this power law plays a critical role in determining the size at which a growing lesion reaches the threshold for detection. In this study, the authors evaluated the power-law model for breast computed tomography (bCT) images, which can be thought of as thin sections through a three-dimensional (3D) volume. Under the assumption of a 3D power law describing the distribution of attenuation coefficients in the breast parenchyma, the authors derived the relationship between the power-law exponents of bCT and projection images and found it to be betasection=betaproj-1. They evaluated this relationship on clinical images by comparing bCT images from a set of 43 patients to Burgess' findings in mammography. They were able to make a direct comparison for 6 of these patients who had both a bCT exam and a digitized film-screen mammogram. They also evaluated segmented bCT images to investigate the extent to which the bCT power-law exponent can be explained by a binary model of attenuation coefficients based on the different attenuation of glandular and adipose tissue. The power-law model was found to be a good fit for bCT data over frequencies from 0.07 to 0.45 cyc/mm, where anatomical variability dominates the spectrum. The average exponent for bCT images was 1.86. This value is close to the theoretical prediction using Burgess' published data for projection mammography and for the limited set of mammography data available from the authors' patient sample. Exponents from the segmented bCT images (average value: 2.06) were systematically slightly higher than bCT images, with substantial correlation between the two (r=0.84).

SUBMITTER: Metheany KG

PROVIDER: S-EPMC3304474 | biostudies-other | 2008 Oct

REPOSITORIES: biostudies-other

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Project description:PurposeAccurate lesion segmentation is a prerequisite for radiomic feature extraction. It helps to reduce the features variability so as to improve the reporting quality of radiomics study. In this research, we aimed to conduct a radiomic feature reproducibility test of inter-/intra-observer delineation variability in hepatocellular carcinoma using 3D-CT images, 4D-CT images and multiple-parameter MR images.Materials and methodsFor this retrospective study, 19 HCC patients undergoing 3D-CT, 4D-CT and multiple-parameter MR scans were included in this study. The gross tumor volume (GTV) was independently delineated twice by two observers based on contrast-enhanced computed tomography (CECT), maximum intensity projection (MIP), LAVA-Flex, T2W FRFSE and DWI-EPI images. We also delineated the peritumoral region, which was defined as 0 to 5 mm radius surrounding the GTV. 107 radiomic features were automatically extracted from CECT images using 3D-Slicer software. Quartile coefficient of dispersion (QCD) and intraclass correlation coefficient (ICC) were applied to assess the variability of each radiomic feature. QCD<10% and ICC≥0.75 were considered small variations and excellent reliability. Finally, the principal component analysis (PCA) was used to test the feasibility of dimensionality reduction.ResultsFor tumor tissues, the numbers of radiomic features with QCD<10% indicated no obvious inter-/intra-observer differences or discrepancies in 3D-CT, 4D-CT and multiple-parameter MR delineation. However, the number of radiomic features (mean 89) with ICC≥0.75 was the highest in the multiple-parameter MR group, followed by the 3DCT group (mean 77) and the MIP group (mean 73). The peritumor tissues also showed similar results. A total of 15 and 7 radiomic features presented excellent reproducibility and small variation in tumor and peritumoral tissues, respectively. Two robust features showed excellent reproducibility and small variation in tumor and peritumoral tissues. In addition, the values of the two features both represented statistically significant differences among tumor and peritumoral tissues (P<0.05). The PCA results indicated that the first seven principal components could preserve at least 90% of the variance of the original set of features.ConclusionDelineation on multiple-parameter MR images could help to improve the reproducibility of the HCC CT radiomic features and weaken the inter-/intra-observer influence.

Project description:To quantify interfractional anatomical variations and their dosimetric impact during the course of fractionated proton therapy (PT) of prostate cancer and to assess the robustness of the current treatment planning techniques.Simulation and daily in-room CT scans from ten prostate carcinoma patients were analyzed. PT treatment plans (78 Gy in 39 fractions of 2 Gy) were created on the simulation CT, delivering 25 fractions to PTV1 (expanded from prostate and seminal vesicles), followed by 14 boost fractions to PTV2 (expanded from prostate). Plans were subsequently applied to daily CT, with beams aligned to the prostate center in the sagittal plane. For five patients having a sufficiently large daily imaging volume, structure contours were manually drawn, and plans were evaluated for all CT sets. For the other five patients, the plans were evaluated for six selected fractions. The daily CT was matched to the simulation CT through deformable registration. The registration accuracy was validated for each fraction, and the three patients with a large number of accurately registered fractions were used for dose accumulation.In individual fractions, the coverage of the prostate, seminal vesicles, and PTV1 was generally maintained at the corresponding prescription dose. For PTV2, the volume covered by the fractional prescription dose of 2 Gy (i.e., V2) was, on average, reduced by less than 3% compared to the simulation plan. Among the 225 (39 x 5 + 6 x 5) fractions examined, 15 showed a V2 reduction larger than 5%, of which ten were caused by a large variation in rectal gas, and five were due to a prostate shift in the craniocaudal direction. The fractional dose to the anterior rectal wall was found to increase for one patient who had large rectal gas volume in 25 of the 39 fractions, and another who experienced significant prostate volume reduction during the treatment. The fractional bladder dose generally increased with decreasing fullness. In the total accumulated dose for the three patients after excluding a few fractions with inaccurate registration due to a large amount of rectal gas (a condition inconsistent with RTOG protocol), 98.5%, 96.6%, and 98.2% of the PTV2 received the prescription dose of 78 Gy. The V75 and V70 of the anterior rectal wall and bladder both remained within tolerance.The results confirm that the PT planning techniques and dose constraints used at our institution ensure that target coverage to the prescription dose is maintained in the presence of interfractional anatomical variations. Dose coverage in individual fractions can be compromised, and normal tissue dose increased, due to deviations in the bladder and rectal volume compared to the simulation plans or progressive changes in the prostate volume during the treatment. Deviations from the plan can be reduced with efforts aimed at maintaining consistent daily patient anatomy.

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Characterizing anatomical variability in breast CT images.

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