Evaluation of the 95% limits of agreement of the volumes of 5-year clinically stable solid nodules for the development of a follow-up system for indeterminate solid nodules in CT lung cancer screening.

BACKGROUND: This study sought to evaluate the 95% limits of agreement of the volumes of 5-year clinically stable solid nodules for the development of a follow-up system for indeterminate solid nodules. METHODS: The volumes of 226 solid nodules that had been clinically stable for 5 years were measured in 186 patients (53 female never-smokers, 36 male never-smokers, 51 males with <30 pack-years, and 46 males with ≥30 pack-years) using a three-dimensional semiautomated method. Volume changes were evaluated using three methods: percent change, proportional change and growth rate. The 95% limits of agreement were evaluated using the Bland-Altman method. RESULTS: The 95% limits of agreement were as follows: range of percent change, from ±34.5% to ±37.8%; range of proportional change, from ±34.1% to ±36.8%; and range of growth rate, from ±39.2% to ±47.4%. Percent change-based, proportional change-based, and growth rate-based diagnoses of an increase or decrease in ten solid nodules were made at a mean of 302±402, 367±455, and 329±496 days, respectively, compared with a clinical diagnosis made at 809±616 days (P<0.05). CONCLUSIONS: The 95% limits of agreement for volume change in 5-year stable solid nodules may enable the detection of an increase or decrease in the solid nodule at an earlier stage than that enabled by a clinical diagnosis, possibly contributing to the development of a follow-up system for reducing the number of additional Computed tomography (CT) scans performed during the follow-up period.

Algorithm Variability in the Estimation of Lung Nodule Volume From Phantom CT Scans: Results of the QIBA 3A Public Challenge.

RATIONALE AND OBJECTIVES: Quantifying changes in lung tumor volume is important for diagnosis, therapy planning, and evaluation of response to therapy. The aim of this study was to assess the performance of multiple algorithms on a reference data set. The study was organized by the Quantitative Imaging Biomarker Alliance (QIBA). MATERIALS AND METHODS: The study was organized as a public challenge. Computed tomography scans of synthetic lung tumors in an anthropomorphic phantom were acquired by the Food and Drug Administration. Tumors varied in size, shape, and radiodensity. Participants applied their own semi-automated volume estimation algorithms that either did not allow or allowed post-segmentation correction (type 1 or 2, respectively). Statistical analysis of accuracy (percent bias) and precision (repeatability and reproducibility) was conducted across algorithms, as well as across nodule characteristics, slice thickness, and algorithm type. RESULTS: Eighty-four percent of volume measurements of QIBA-compliant tumors were within 15% of the true volume, ranging from 66% to 93% across algorithms, compared to 61% of volume measurements for all tumors (ranging from 37% to 84%). Algorithm type did not affect bias substantially; however, it was an important factor in measurement precision. Algorithm precision was notably better as tumor size increased, worse for irregularly shaped tumors, and on the average better for type 1 algorithms. Over all nodules meeting the QIBA Profile, precision, as measured by the repeatability coefficient, was 9.0% compared to 18.4% overall. CONCLUSION: The results achieved in this study, using a heterogeneous set of measurement algorithms, support QIBA quantitative performance claims in terms of volume measurement repeatability for nodules meeting the QIBA Profile criteria.

Volume-based response evaluation with consensual lesion selection: a pilot study by using cloud solutions and comparison to RECIST 1.1.

RATIONALE AND OBJECTIVES: Lesion volume is considered as a promising alternative to Response Evaluation Criteria in Solid Tumors (RECIST) to make tumor measurements more accurate and consistent, which would enable an earlier detection of temporal changes. In this article, we report the results of a pilot study aiming at evaluating the effects of a consensual lesion selection on volume-based response (VBR) assessments. MATERIALS AND METHODS: Eleven patients with lung computed tomography scans acquired at three time points were selected from Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) and proprietary databases. Images were analyzed according to RECIST 1.1 and VBR criteria by three readers working in different geographic locations. Cloud solutions were used to connect readers and carry out a consensus process on the selection of lesions used for computing response. Because there are not currently accepted thresholds for computing VBR, we have applied a set of thresholds based on measurement variability (-35% and +55%). The benefit of this consensus was measured in terms of multiobserver agreement by using Fleiss kappa (κfleiss) and corresponding standard errors (SE). RESULTS: VBR after consensual selection of target lesions allowed to obtain κfleiss = 0.85 (SE = 0.091), which increases up to 0.95 (SE = 0.092), if an extra consensus on new lesions is added. As a reference, the agreement when applying RECIST without consensus was κfleiss = 0.72 (SE = 0.088). These differences were found to be statistically significant according to a z-test. CONCLUSIONS: An agreement on the selection of lesions allows reducing the inter-reader variability when computing VBR. Cloud solutions showed to be an interesting and feasible strategy for standardizing response evaluations, reducing variability, and increasing consistency of results in multicenter clinical trials.

BTK: an open-source toolkit for fetal brain MR image processing.

Studies about brain maturation aim at providing a better understanding of brain development and links between brain changes and cognitive development. Such studies are of great interest for diagnosis help and clinical course of development and treatment of illnesses. However, the processing of fetal brain MR images remains complicated which limits the translation from the research to the clinical domain. In this article, we describe an open-source image processing toolkit dedicated to these images. In this toolkit various tools are included such as: denoising, image reconstruction, super-resolution and tractography. The BTK resource program (distributed under CeCILL-B license) is developed in C++ and relies on common medical imaging libraries such as Insight Toolkit (ITK), Visualization Toolkit (VTK) and Open Multi-Processing (OpenMP).

Thick corpus callosum: a clue to the diagnosis of fetal septopreoptic holoprosencephaly?

We describe fetal septopreoptic holoprosencephaly (HPE) associated with a thick corpus callosum (CC) diagnosed with MRI in a fetus at 31 weeks' gestation. Our report supports a recently published study connecting a thick fetal CC to other brain abnormalities. On diffusion tensor imaging (DTI), the body of the CC contained an abnormal longitudinal bundle, presumed to be a congenital heterotopic cingulum. Prenatal and postmortem brain MRI with DTI, CT, and pathological analyses are described and illustrated.

Reconstruction of scattered data in fetal diffusion MRI.

In this paper we present a method for reconstructing diffusion-weighted MRI data on regular grids from scattered data. The proposed method has the advantage that no specific diffusion model needs to be assumed. Previous work assume the tensor model, but this is not suitable under certain conditions like intravoxel orientational heterogeneity (IVOH). Data reconstruction is particularly important when studying the fetal brain in utero, since registration methods applied for movement and distortion correction produce scattered data in spatial and diffusion domains. We propose the use of a groupwise registration method, and a dual spatio-angular interpolation by using radial basis functions (RBF). Leave-one-out experiments performed on adult data showed a high accuracy of the method. The application to fetal data showed an improvement in the quality of the sequences according to objective criteria based on fractional anisotropy (FA) maps, and differences in the tractography results.

Reconstruction of scattered data in fetal diffusion MRI.

In this paper we present a method for reconstructing D-MRI data on regular grids from sparse data without assuming specific diffusion models. This is particularly important when studying the fetal brain in utero, since registration methods applied for movement and distortion correction produce scattered data in spatial and angular (gradient) domains. We propose the use of a groupwise registration method, and a dual spatio-angular interpolation by using radial basis functions (RBF). Experiments performed on adult data showed a high accuracy of the method when estimating diffusion images in unavailable directions. The application to fetal data showed an improvement in the quality of the sequences according to criteria based on fractional anisotropy (FA) maps, and differences in the tractography results.

A point-wise quantification of asymmetry using deformation fields: application to the study of the Crouzon mouse model.

This paper introduces a novel approach to quantify asymmetry in each point of a surface. The measure is based on analysing displacement vectors resulting from nonrigid image registration. A symmetric atlas, generated from control subjects is registered to a given subject image. A comparison of the resulting displacement vectors on the left and right side of the symmetry plane, gives a point-wise measure of asymmetry. The asymmetry measure was applied to the study of Crouzon syndrome using Micro CT scans of genetically modified mice. Crouzon syndrome is characterised by the premature fusion of cranial sutures, which gives rise to a highly asymmetric growth. Quantification and localisation of this asymmetry is of high value with respect to surgery planning and treatment evaluation. Using the proposed method, asymmetry was calculated in each point of the surface of Crouzon mice and wild-type mice (controls). Asymmetry appeared in similar regions for the two groups but the Crouzon mice were found significantly more asymmetric. The localisation ability of the method was in good agreement with ratings from a clinical expert. Validating the quantification ability is a less trivial task due to the lack of a gold standard. Nevertheless, a comparison with a different, but less accurate measure of asymmetry revealed good correlation.

Computational mouse atlases and their application to automatic assessment of craniofacial dysmorphology caused by the Crouzon mutation Fgfr2(C342Y).

Crouzon syndrome is characterized by premature fusion of sutures and synchondroses. Recently, the first mouse model of the syndrome was generated, having the mutation Cys342Tyr in Fgfr2c, equivalent to the most common human Crouzon/Pfeiffer syndrome mutation. In this study, a set of micro-computed tomography (CT) scannings of the skulls of wild-type mice and Crouzon mice were analysed with respect to the dysmorphology caused by Crouzon syndrome. A computational craniofacial atlas was built automatically from the set of wild-type mouse micro-CT volumes using (1) affine and (2) non-rigid image registration. Subsequently, the atlas was deformed to match each subject from the two groups of mice. The accuracy of these registrations was measured by a comparison of manually placed landmarks from two different observers and automatically assessed landmarks. Both of the automatic approaches were within the interobserver accuracy for normal specimens, and the non-rigid approach was within the interobserver accuracy for the Crouzon specimens. Four linear measurements, skull length, height and width and interorbital distance, were carried out automatically using the two different approaches. Both automatic approaches assessed the skull length, width and height accurately for both groups of mice. The non-rigid approach measured the interorbital distance accurately for both groups while the affine approach failed to assess this parameter for both groups. Using the full capability of the non-rigid approach, local displacements obtained when registering the non-rigid wild-type atlas to a non-rigid Crouzon mouse atlas were determined on the surface of the wild-type atlas. This revealed a 0.6-mm bending in the nasal region and a 0.8-mm shortening of the zygoma, which are similar to characteristics previously reported in humans. The most striking finding of this analysis was an angulation of approximately 0.6 mm of the cranial base, which has not been reported in humans. Comparing the two different methodologies, it is concluded that the non-rigid approach is the best way to assess linear skull parameters automatically. Furthermore, the non-rigid approach is essential when it comes to analysing local, non-linear shape differences.

CFD analysis incorporating the influence of wall motion: application to intracranial aneurysms.

Haemodynamics, and in particular wall shear stress, is thought to play a critical role in the progression and rupture of intracranial aneurysms. A novel method is presented that combines image-based wall motion estimation obtained through non-rigid registration with computational fluid dynamics (CFD) simulations in order to provide realistic intra-aneurysmal flow patterns and understand the effects of deforming walls on the haemodynamic patterns. In contrast to previous approaches, which assume rigid walls or ad hoc elastic parameters to perform the CFD simulations, wall compliance has been included in this study through the imposition of measured wall motions. This circumvents the difficulties in estimating personalized elasticity properties. Although variations in the aneurysmal haemodynamics were observed when incorporating the wall motion, the overall characteristics of the wall shear stress distribution do not seem to change considerably. Further experiments with more cases will be required to establish the clinical significance of the observed variations.