Variability Of Volume Measurements Research Articles

Test Retest Reproducibility of Organ Volume Measurements in ADPKD Using 3D Multimodality Deep Learning

Following autosomal dominant polycystic kidney disease (ADPKD) progression by measuring organ volumes requires low measurement variability. The objective of this study is to reduce organ volume measurement variability on MRI of ADPKD patients by utilizing all pulse sequences to obtain multiple measurements which allows outlier analysis to find errors and averaging to reduce variability. In order to make measurements on multiple pulse sequences practical, a 3D multi-modality multi-class segmentation model based on nnU-net was trained/validated using T1, T2, SSFP, DWIand CT from 413 subjects. Reproducibility was assessed with test-re-test methodology on ADPKD subjects (n=19) scanned twice within a 3-week interval correcting outliers and averaging the measurements across all sequences. Absolute percent differences in organ volumes were compared topaired students t-test. Dice similarlity coefficient >97%, Jaccard Index >0.94, mean surface distance <1mmand mean Hausdorff Distance <2cm for all three organs and all five sequences werefound on internal (n=25), external (n=37) and test-re-test reproducibility assessment (38 scans in 19 subjects). When averaging volumes measured from fiveMRI sequences, the model automatically segmented kidneys with test-re-test reproducibility (percent absolute difference between exam 1 and exam 2) of 1.3% which was better than all fiveexpert observers. It reliably stratified ADPKD into Mayo Imaging Classification (area under the curve=100%) compared to radiologist. 3D deep learning measures organ volumes on fiveMRI sequences leveraging the power of outlier analysis and averaging to achieve 1.3% total kidney test-re-test reproducibility.

Clinical Quality Control of MRI Total Kidney Volume Measurements in Autosomal Dominant Polycystic Kidney Disease.

Total kidney volume measured on MRI is an important biomarker for assessing the progression of autosomal dominant polycystic kidney disease and response to treatment. However, we have noticed that there can be substantial differences in the kidney volume measurements obtained from the various pulse sequences commonly included in an MRI exam. Here we examine kidney volume measurement variability among five commonly acquired MRI pulse sequences in abdominal MRI exams in 105 patients with ADPKD. Right and left kidney volumes were independently measured by three expert observers using model-assisted segmentation for axial T2, coronal T2, axial single-shot fast spin echo (SSFP), coronal SSFP, and axial 3D T1 images obtained on a single MRI from ADPKD patients. Outlier measurements were analyzed for data acquisition errors. Most of the outlier values (88%) were due to breathing during scanning causing slice misregistration with gaps or duplication of imaging slices (n = 35), slice misregistration from using multiple breath holds during acquisition (n = 25), composing of two overlapping acquisitions (n = 17), or kidneys not entirely within the field of view (n = 4). After excluding outlier measurements, the coefficient of variation among the five measurements decreased from 4.6% pre to 3.2%. Compared to the average of all sequences without errors, TKV measured on axial and coronal T2 weighted imaging were 1.2% and 1.8% greater, axial SSFP was 0.4% greater, coronal SSFP was 1.7% lower and axial T1 was 1.5% lower than the mean, indicating intrinsic measurement biases related to the different MRI contrast mechanisms. In conclusion, MRI data acquisition errors are common but can be identified using outlier analysis and excluded to improve organ volume measurement consistency. Bias toward larger volume measurements on T2 sequences and smaller volumes on axial T1 sequences can also be mitigated by averaging data from all error-free sequences acquired.

A Review of the Existing Literature on 3D Reconstruction Methods

Abstract: Using deep neural networks, supervised 3D reconstruction has made significant progress. However, large-scale annotations of 2D/3D data are necessary for this performance boost [4]. How to effectively represent 3D data to feed deep networks remains a challenge in 3D deep learning. Volumetricor point cloud representations have been used inrecent works, but these methods have a number of drawbacks, including computational complexity, unorganized data, and a lack of finer geometry [7]. The ultrasound (US) examination is onemethod usedto diagnose carotid artery disease. The flow conditions in the artery also play a role in the onset and progression of vascular diseases [5]. Stenting the carotid artery is a treatment option for carotid atherosclerosis. It is impossible to know for sure where an injection with a needle will begin. The place of the conduits is in the body, thusly, decidingthe beginning stage of needle infusion is finished byassessment just and can't not entirely set in stone. The first thing that must be done is to locate the carotid artery in order to identify it. To determine it,we propose a modified template matching based on the ellipse feature for a 3D reconstruction of the carotid artery [1]. Data acquisition, pre-processing, segmentation, outlier selection for ellipse parameterfitting, and visualization are all used to process it. In comparison to the template matching method and the Hough Circle method, the proposed procedure with pre-processing produces the highest accuracy [1]. The objective of this research was to create three- dimensional (3D) ultrasound imaging of the carotid arteries to lessen the variability of volume measurements between and within examiners duringfollow-up scans of atherosclerotic plaques.

The Compressed Sensing MP2RAGE as a Surrogate to the MPRAGE for Neuroimaging at 3 T.

The magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) sequence provides quantitative T1 maps in addition to high-contrast morphological images. Advanced acceleration techniques such as compressed sensing (CS) allow its acquisition time to be compatible with clinical applications. To consider its routine use in future neuroimaging protocols, the repeatability of the segmented brain structures was evaluated and compared with the standard morphological sequence (magnetization-prepared rapid gradient echo [MPRAGE]). The repeatability of the T1 measurements was also assessed. Thirteen healthy volunteers were scanned either 3 or 4 times at several days of interval, on a 3 T clinical scanner, with the 2 sequences (CS-MP2RAGE and MPRAGE), set with the same spatial resolution (0.8-mm isotropic) and scan duration (6 minutes 21 seconds). The reconstruction time of the CS-MP2RAGE outputs (including the 2 echo images, the MP2RAGE image, and the T1 map) was 3 minutes 33 seconds, using an open-source in-house algorithm implemented in the Gadgetron framework.Both precision and variability of volume measurements obtained from CAT12 and VolBrain were assessed. The T1 accuracy and repeatability were measured on phantoms and on humans and were compared with literature.Volumes obtained from the CS-MP2RAGE and the MPRAGE images were compared using Student t tests (P < 0.05 was considered significant). The CS-MP2RAGE acquisition provided morphological images of the same quality and higher contrasts than the standard MPRAGE images. Similar intravolunteer variabilities were obtained with the CS-MP2RAGE and the MPRAGE segmentations. In addition, high-resolution T1 maps were obtained from the CS-MP2RAGE. T1 times of white and gray matters and several deep gray nuclei are consistent with the literature and show very low variability (<1%). The CS-MP2RAGE can be used in future protocols to rapidly obtain morphological images and quantitative T1 maps in 3-dimensions while maintaining high repeatability in volumetry and relaxation times.

Defining growth in small pulmonary nodules using volumetry: results from a \u201ccoffee-break\u201d CT study and implications for current nodule management guidelines

ObjectivesAn increase in lung nodule volume on serial CT may represent true growth or measurement variation. In nodule guidelines, a 25% increase in nodule volume is frequently used to determine that growth has occurred; this is based on previous same-day, test–retest (coffee-break) studies examining metastatic nodules. Whether results from prior studies apply to small non-metastatic nodules is unknown. This study aimed to establish the interscan variability in the volumetric measurements of small-sized non-metastatic nodules.MethodsInstitutional review board approval was obtained for this study. Between March 2019 and January 2021, 45 adults (25 males; mean age 65 years, range 37–84 years) with previously identified pulmonary nodules (30–150 mm3) requiring surveillance, without a known primary tumour, underwent two same-day CT scans. Non-calcified solid nodules were measured using commercial volumetry software, and interscan variability of volume measurements was assessed using a Bland–Altman method and limits of agreement.ResultsOne hundred nodules (range 28–170 mm3; mean 81.1 mm3) were analysed. The lower and upper limits of agreement for the absolute volume difference between the two scans were − 14.2 mm3 and 12.0 mm3 respectively (mean difference 1.09 mm3, range − 33–12 mm3). The lower and upper limits of agreement for relative volume difference were − 16.4% and 14.6% respectively (mean difference 0.90%, range − 24.1–32.8%).ConclusionsThe interscan volume variability in this cohort of small non-metastatic nodules was smaller than that in previous studies involving lung metastases of varying sizes. An increase of 15% in nodule volume on sequential CT may represent true growth, and closer surveillance of these nodules may be warranted.Key Points• In current pulmonary nodule management guidelines, a threshold of 25% increase in volume is required to determine that true growth of a pulmonary nodule has occurred.• This test–retest (coffee break) study has demonstrated that a smaller threshold of 15% increase in volume may represent true growth in small non-metastatic nodules.• Closer surveillance of some small nodules growing 15–25% over a short interval may be appropriate.

Inter-observer and Intra-observer Variability in Volume Measurements of the Lower Extremity Using Perometer.

Background: The swelling of the extremities seen in lymphedema can be measured with many different volumetric devices; however, many methods lack important characteristics including reproducibility and independence from the subjectivity and skill of the operator. The aim of this study was to validate the use of the Perometer® as a possible standard for volumetric measurement methods based on the inter-observer and intra-observer variability when using a standard method of Perometry®. Methods and Results: Volumetric measurements were performed on 10 healthy test subjects by 5 individuals (the observers) who had been instructed in the measurement techniques to be used. The inter-observer variability was assessed by having the five observers measure all the test subjects both in the morning and in the early afternoon. The intra-observer variability was examined by having each observer measure all the 10 test subjects 4 times in a row in the aforementioned time frames. A data set was created using the measurements, allowing for the assessment of other parameters including variation of volume between the right and left leg and daily variation in swelling. Statistical measurements were performed using the Statistical Package for the Social Sciences (SPSS), from which it was determined that there was no statistically significant inter-observer (p-value 0.997) and intra-observer variation (p-value 0.995) based on a significance level of >5%. Furthermore, it was observed that a statistically significant difference in volume occurred in the leg volume during the day. Conclusion: It was concluded that the use of the Perometer provides consistent measurements of volume independent of the observer and therefore appears to provide a candidate standard for volumetric measurements.

Evidence-based MR imaging follow-up strategy for desmoid-type fibromatosis.

To propose a follow-up strategy for desmoid-type fibromatosis (DF) based on tumor growth behavior and the signal on T2-weighted MRI. We retrospectively reviewed 296 MRI studies of 34 patients with histologically proven DF. In each study, tumor volume and T2 signal relatively normal striated muscle were assessed. Volume variation and monthly growth rates were analyzed to determine lesion growth behavior (progressing versus stable/regressing lesions). Growth behavior was correlated with T2 signal, tumor location, β-catenin status, treatment strategy, and follow-up duration. Interobserver variability of volume measurements and interobserver measurement variation ratio were assessed. There were 25 women and 9 men with a mean age of 39.9 ± 19 (4-73) years. Mean follow-up time in the patients included was 55 ± 41 (12-148) months. In progressing lesions, the mean average monthly growth ratio was 10.9 ± 9.2 (1.1-42.5) %. Interobserver variability of volume measurements was excellent (ICC = 0.96). Mean interobserver measurement variation ratio was 20.4 ± 23.6%. The only factor correlated with tumor growth behavior was T2 signal ratio (p< 0.0001). Seventeen out of 34 (50%) patients presented a signal change over the threshold of 1 during follow-up. There were five occurrences of secondary growth after a period of stability with a mean delay until growth of 38.2 ± 44.2 (17-116) months. DF growth rate was quantitatively assessed. A threshold for volume variation detection was established. DF growth behavior was significantly related to T2 signal. An evidence-based follow-up strategy is proposed. • In progressing desmoid fibromatosis, the mean average monthly growth ratio was 10.9 ± 9.2%. • Lesions with muscle/tumor T2 signal ratios lower than 1 tended to be stable or regress over time. • Given the interobserver measurement variability and MRI in-plane spatial resolution, a variation higher than 42.6% in tumor volume is required to confirm punctual progression.

Stacked in-plane histology for quantitative validation of non-invasive imaging biomarkers: Application to an infiltrative brain tumour model

BackgroundWhile it is generally agreed that histopathology is the gold standard for assessing non-invasive imaging biomarkers, most validation has been by qualitative visual comparison. To date, the difficulties involved in accurately co-registering histology sections with imaging slices have prevented a voxel-by-voxel assessment of imaging modalities. By contrast with previous studies, which focus on improving the registration algorithms, we have taken the approach of improving the quality of the histological processing and analysis. New methodTo account for imaging slice orientation and thickness, multiple histology sections were cut in the MR imaging plane and averaged to produce stacked in-plane histology (SIH) maps. When combined with intensity sensitive staining this approach gives histopathology maps, which can be used as the gold standard to validate imaging biomarkers. ResultsWe applied this pipeline to a patient-derived mouse model of glioblastoma multiforme (GBM). Increasing the number of stacked histology sections significantly increased SIH measured tumour volume. The SIH technique proposed here resulted in reduced variability of volume measurements and this allowed significant improvements in the quantitative volumetric assessment of multiple MRI modalities. Further, high quality registration enabled a voxel-wise comparison between MRI and histopathology maps.Previous approaches to the validation of imaging biomarkers with histology, have been either qualitative or of limited accuracy. Here we propose a pipeline that allows for a more accurate validation via co-registration with SIH maps, potentially allowing validation in a voxel-wise mode. ConclusionThis work demonstrates that methodically produced SIH maps facilitate the quantitative histopathologic assessment of imaging biomarkers.

The natural history of prostate cancer on MRI: lessons from an active surveillance cohort.

Multiparametric magnetic resonance imaging (mpMRI) is being used increasingly in the setting of active surveillance (AS) for prostate cancer. We investigated changes in the mpMRI appearance of lesions on AS, to show the variability of volume measurements in visible lesions and assess change in lesion size according to grade. We retrospectively retrieved 86 men on AS (NICE guidelines) with more than one mpMRI (the first before 2013). Two radiologists, in consensus, were blinded to patient demographics and date of scan. The scans were randomly reported to reduce any bias. For visible lesions, we measured volume by planimetry on the sequence best showing the most conspicuous (index) tumour and attributed a 5-point Likert score. 43/86 men did not have a visible lesion on the initial mpMRI (≤2/5). Of these, 5/43 had developed a lesion scoring ≥3/5 ata median of 3.6 years of follow up. 40/86 had a lesion scoring ≥3/5 on two or more scans. There was a significant increase in volume over 3.6 years by a median of 10% (p < 0.01)-by a median of 6% for Gleason 3+3 and 18% for 3+4 (p = 0.058). Thirty-five men had a visible lesion on two scans separated by <2 years; of these, 21/35 showed a 78% median increase in tumour size between the two scans and 11/35 showed an apparent 25% median decrease in lesion size. A total of 17% of men with no visible lesion developed a visible lesion at a median follow up of 3.6 years. It is possible to show significant growth in patients with a visible lesion, but variability in volume measurements between scans means that it is difficult to reliably detect increases of this order. This variability may inform the design of mpMRI protocols in AS and the time between follow up scans.

Initiating a lymphedema screening program for breast cancer patients: Determining variability as a first step towards standardization.

267 Background: Breast cancer-related lymphedema (BCRL) is a known morbidity from treatment, and yet published estimates of its incidence are highly variable. Typically, a single volume measurement is recorded and the degree of intra-rater variability undefined. A threshold 5% limb volume change over time is used to define “mild lymphedema.” Therefore, small variations in volume measurements could substantially lead to over or under-diagnosis of BRCL. Gage R&amp;R is a measurement systems analysis tool that quantifies the amount of variability induced in measurements by the measurement system itself and compares this to the total variability observed. The objective of this study was to define the degree of variability in perometer arm volume measurements and factors contributing to this. Methods: A medical assistant (MA) was trained by a certified lymphedema therapist (CLT) to perform perometer-based lymphedema screening in the MD Anderson Nellie B. Connally Breast Center. Three measurements of each arm were taken and intra-rater variability against the mean calculated. Gage R&amp;R testing was performed by the MA and CLT, to determine the degree of repeatability and reproducibility variation. As a part of this analysis, 30 patients had both their left and right arm volume measured 3 times by each measurer. Results: Over 6 months, 565 breast cancer patients had preoperative BCRL screening by the MA, with an overall intra-rater variability of 2.2%. Among the 30 patients in the Gage R&amp;R study, median body mass index (BMI) was 27.7 (range 19.7-38.3), median height 1.61m (range 1.52-1.73m), intrarater variability of the MA was 2.07% and of the CLT was 1.21%. Gage R&amp;R accounted for 4.77% of total variability, 1.26% repeatability and 3.51% reproducibility. Regression analysis demonstrated that patient BMI and height impacted variability in measurements (R2= 16.27). Conclusions: Intra-rater variability for perometer arm measurements diminishes with experience. Gage R&amp;R variability is acceptable per industry standards, but there is room for improvement. Our findings suggest a role for targeted interventions to minimize variability in the diagnosis of BCRL based on patient characteristics.

Carotid plaque morphometric assessment with three-dimensional ultrasound imaging

As investigations into nonsurgical treatment for atherosclerosis expand, the measurement of plaque regression and progression has become an important end point to evaluate. Measurements of three-dimensional (3D) plaque volume are more reliable and sensitive to change than are traditional estimates of stenosis severity or cross-sectional area. 3D ultrasound (3D US) imaging may allow monitoring of plaque volume changes but has not been used routinely due to the cumbersome motorized units required to drive transducers. We investigated the variability, reliability, and the least amount of change detectable by 1D plaque measures, as well as 2D and 3D measures of plaque morphometry, that can be applied in a clinical environment. 3D US imaging was obtained in 10 patients with carotid stenosis. The lumen and outer wall boundaries were outlined in serial cross-sectional images 1 mm apart. Three observers manually segmented vessel wall volumes (VWVs), and the segmentation was repeated again 4 weeks later. This allowed measurement of interobserver and intraobserver variability of 6 pairs of observations. We measured Bland-Altman statistics, intraclass correlation coefficients, coefficient of variability, and the minimum detectable plaque change for each morphometric measure. The mean VWV of carotid lesions in the study was 1276.8 mm(3) (range, 620.6-1956.3 mm(3)). Bland-Altman plots demonstrated low interobserver and intraobserver variability. The interobserver variability of volume measurements as a function of mean volume was 14.8% and interobserver variability was 8.9%. Reliability was 87% as quantified by the interclass correlation and was 95% by the intraclass correlation. The least detectable change in VWV was 12.9% for interobserver variability and 4.5% for intraobserver variability for the three observers. Carotid plaque diameter measurements from B-mode images have high variability. Plaque burden, as estimated by VWV, can be measured reliably with a 3D US technique using a clinical scanner. The volumetric change, with 95% confidence, that must be observed to establish that a plaque has undergone growth or regression is ∼12.9% for different observers and 4.5% for the same observer performing the follow-up study.

Carotid Artery Disease Imaging: A Home-Produced, Easily Made Phantom for Two- and Three-Dimensional Ultrasound Simulation

Background and Purpose —Ultrasound (US) plaque characterization has great potential with regard to maximizing the information traditionally gathered with spectral Doppler examination. It can directly visualize plaque and quantify better features such as surface morphology, geometry, volume, and echotexture via B-mode and the three-dimensional (3D) imaging mechanism. One of the major pitfalls of carotid imaging is the use of freehand manual manipulation. The application of angling, steering, as well as variability in the technical parameters, can increase the interobservation inconsistency. A limited number of commercial phantoms are available to teach this advanced technique but come at a high cost. We developed a home-produced phantom model to practice and teach carotid atherosclerotic disease imaging. We also investigated interobservation variability using two-dimensional (2D) characterization and 3D mechanical planimetry. This study presents a recipe to create an ultrasonic phantom that simulates a diseased carotid artery segment and how it can be used in identifying the 2D and 3D US interobservation variability. Methods —We created five tissue-like phantoms to simulate various types of diseased plaque segments. To simulate the plaque, a piece of frankfurter was cut and detailed to represent various forms of diseased plaque. Each mould contained dissimilar types of mimicked-plaque, including a soft-plaque, fissured, ulcerated, irregular surfaced, and calcified segment. We used a mixture of gelatin and Metamucil to mimic a previously published soft-tissue mixture. To create a vessel, we used a powder-free, nitrile examination glove. The frankfurter was held in place inside the middle finger of the glove using adhesive gel and filled with mineral oil. Preparation included interval refrigeration of the concoction of the mould. Trained sonographers imaged the plaque using a linear small parts probe for 2D and a mechanical 3D probe for 3D US. Two neuroradiologists assessed the corresponding images and reported their findings including the internal plaque contents, volume, and geometry. Analysis was performed on the inter-observation and inter-reading variability. Results —Interobserver and interreader reliabilities were high, and plaque volume measurement variability decreased with increasing plaque volume. There was increased sensitivity and specificity for each plaque phantom with the use of 3D versus 2D alone. Neuroradiologists reports were 96% sensitive and 97% specific, respectively, when they used combined 2D and 3D US. Conclusion —We created a 2D and 3D vascular US carotid phantom. This phantom is an excellent educational tool to simulate various degrees of diseased carotid segments; moreover, it can be made easily and inexpensively and is reusable. This phantom represents the vessel anatomy and pathology extremely well. We implemented a standardized scanning protocol and created a plaque morphological worksheet to cover all plaque characterization criteria and achieve optimal imaging. Results indicated minimal interobservation and interreader variability. Additional studies are required to address the phantom's longevity and whether or not it can improve the sonographer's skills.

Computer-Aided Analysis of Orbital Volume

: To demonstrate the accuracy and efficiency of a novel software tool designed specifically for volumetric analysis of the orbit. : The software was evaluated for accuracy and speed in analysis of orbital CT data sets. The analysis included: 1) intraoperator error: one operator repeatedly evaluated a single orbit multiple times. The variation in volumes was compared; 2) interoperator error: 3 operators evaluated the same orbits multiple times. The variation in volume measurements among operators was compared; 3) interscan error: one operator evaluated the volume of single orbit scanned on multiple occasions by different CT scanners. The variation in volume measurements among scans performed at different times was compared; and 4) time for analysis: one operator evaluated 52 orbits, recording the time it took to analyze each orbit. : Intraoperator error was 0.08 cc (95% confidence interval, 0.06-0.10). Interoperator error was 0.18 cc (95% confidence interval, 0.14-0.20). Interscan variability data showed a trend toward increasing error for repeated patient scans using different CT scanners. Average time for analysis of single orbit was 138 seconds (standard deviation = 24; range, 95-217 seconds). : Maxillo is an accurate and efficient tool for semiautomatic evaluation of orbital volume in nontraumatized orbits.

Semi-automatic Volumetric Measurement of Lung Cancer Using Multi-detector CT: Effects of Nodule Characteristics

The aims of this study were to determine interobserver variability in volume measurements of lung tumors (including part-solid and nonsolid types) using novel computer-aided diagnosis (CAD) tools and a machine learning approach and to determine the potential reasons for variability. In 60 consecutive patients with peripheral lung cancer, the three-dimensional volumes of nodules were measured using the perimeter method by an experienced chest radiologist. In addition, for the same patients, maximal diameters and three-dimensional volumes were measured with and without a novel CAD tool by six observers. The coefficient of variance (CV) as index of interobserver variability was calculated. For the measurement of volume, the results of the perimeter method were compared to those of the CAD method. Furthermore, the CV was calculated for the following subgroups: nodule diameter, internal opacity, margin, spiculation, and adherence to vessels and the chest wall. There was significant interobserver variability among the six observers for manual, but not CAD, measurements of maximal diameter (P < .001 and P = .207, respectively). Volume measured with the perimeter method by a chest radiologist was well correlated with volume measured with the aid of the CAD system by six radiologists (r = 0.98-0.99). There was no significant difference in the CV for size, internal opacity, spiculation of nodules, or adherence to pulmonary vessels and the chest wall. The CV was significantly higher for obscure marginal nodules than for clear marginal nodules (P < .01). The novel CAD tool could be used to measure the volume of not only solid but also part-solid and nonsolid lung tumors.

In Vivo Repeatability of Automated Volume Calculations of Small Pulmonary Nodules With CT

The objectives of our study were to evaluate the in vivo reproducibility of automated volume calculations of small lung nodules with both low-dose and standard-dose CT and to assess whether repeatability within each technique varies according to the diameter, site, or morphology of the nodule or to percentage of emphysema. Sixty-six subjects with 83 solid pulmonary nodules between 5 and 10 mm in diameter were enrolled in this prospective study. Four consecutive MDCT data sets, two low dose and two standard dose, were obtained for each nodule on separate breath-holds during the same session. The volume of each nodule was calculated by automated software. Repeatability was evaluated by Bland-Altman's approach and the coefficient of repeatability. Associations of the percentage of volume variation between two measurements with nodule diameter, emphysema percentage, nodule site, and nodule morphology were assessed by Spearman's correlation coefficient and the Kruskal-Wallis test. A p value of < 0.05 was considered statistically significant. The range of variation of the volumes of pulmonary nodules between two subsequent measurements was -38% +/- 60% for low-dose CT and -27% +/- 40% for standard-dose CT. No significant statistical association was found between variation in volume measurements and nodule site, nodule diameter, nodule morphology, or emphysema percentage by semiautomated calculation of lung density. Automated volume calculations of small pulmonary nodules can significantly differ between two subsequent breath-holds with both low-dose and standard-dose CT techniques; in clinical practice we recommend that a volume variation of greater than 30% for nodules between 5 and 10 mm should be confirmed by follow-up CT to be sure that a nodule is actually growing.

WE‐E‐210A‐03: 3D Carotid Ultrasound Imaging for Monitoring Carotid Atherosclerosis

Atherosclerosis is characterized by the development of plaques in the arterial wall, ultimately leading to heart attacks and strokes. Quantitative measurements of the progression and regression of carotid plaque burden are important in monitoring patients and evaluating new treatment options. 3D carotid ultrasound (3D US) has the potential to be an effective method to monitor the progression of carotid artery plaques in symptomatic and asymptomatic patients. To meet this challenge, we developed a 3D carotid US system that allows detailed studies of plaques in 3D. Our software includes 3D reconstruction, viewing, and segmentation of carotid plaques, surface morphology analysis, and registration software to allow quantitative tracking of plaque changes. We used our system to examine the detailed relationship between the 3D US‐based measurement of plaque volume, the 3D scanning parameters, volume measurement variability, and plaque surface morphology. In this paper, we describe the acquisition and reconstruction of 3D carotid US images, and extended concepts used in intima‐media thickness (IMT) measurements based on 2D images to a metric we call the 3D vessel‐wall‐plus‐plaque thickness (3D VWT), which is obtained by computing the distance between the carotid wall and lumen surfaces on a point‐by‐point basis in a 3D image of the carotid arteries. The VWT measurements can be superimposed on the arterial wall to produce the 3D VWT map. Since changes in plaque thickness is important in monitoring patients who are at risk for stroke, we also compute the change of VWT by comparing the 3D VWT maps obtained at two different times. To facilitate the visualization and interpretation of the 3D VWT and 3D VWT‐Change maps, we developed a technique to flatten these maps in an area‐preserving manner.Learning Objectives:1. Understand the limitations of conventional carotid ultrasound imaging2. Understand the methods that can be used to overcome the limitations of the use of conventional ultrasound to monitor progression of carotid disease3. Understand the advantages of 3D ultrasound images to monitor progression of carotid disease

Intra- and Interobserver Variability of Aortic Aneurysm Volume Measurement With Fast CTA Postprocessing Software

To study inter- and intraobserver variability of volume measurements with a new, fast semi-automatic method and compare the results to a previously validated standard manual method for volume measurement. Twenty abdominal computed tomographic angiography (CTA) datasets of patients with abdominal aortic aneurysms undergoing endovascular aneurysm repair (EVAR) were randomly selected from a clinical database (10 pre and 10 post EVAR). Aneurysm sac volume was measured by 2 independent observers using both the standard and semi-automatic methods. Intra- and interobserver variabilities and variability between the 2 methods were studied. Differences of each pair of measurements were plotted against their mean, and the repeatability coefficient (RC) was calculated according to Bland and Altman. For the standard method, the intraobserver mean difference was 0.9 mL (0.4% of the first measurement), with an RC of 8.4 mL (4.2%); the interobserver mean difference was 0.0 mL (0.0%), with a RC of 11.8 mL (5.9%). For the semi-automatic method, the intraobserver mean difference was 1.4 mL (0.7%), with an RC of 7.8 mL (4.1%); the interobserver mean difference was -1.8 mL (-1.0%), with an RC of 10.8 mL (5.7%). The mean difference between the methods was 8.3 mL (4.2%), with an RC of 25.1 mL (12.6%) for observer 1, and a mean difference of 6.4 mL (3.2%) and an RC of 21.3 mL (10.7%) for observer 2. The semi-automatic method showed good intra- and interobserver variability for volume measurements of aortic aneurysms before and after EVAR. Volume measurements with the semi-automatic method correspond to measurements with the standard method. Sophisticated and fast postprocessing software may facilitate acceptance and clinical application of volume measurements in daily practice. The cutoff of 5% for relevant volume changes during follow-up, as advised in the reporting standards for EVAR, is sustained.

Variability of Semiautomated Lung Nodule Volumetry on Ultralow-Dose CT: Comparison with Nodule Volumetry on Standard-Dose CT

The study investigates the effect of a substantial dose reduction on the variability of lung nodule volume measurements by assessing and comparing nodule volumes using a dedicated semiautomated segmentation software on ultralow-dose computed tomography (ULD-CT) and standard-dose computed tomography (SD-CT) data. In 20 patients, thin-slice chest CT datasets (1 mm slice thickness; 20% reconstruction overlap) were acquired at ultralow-dose (120 kV, 5 mAs) and at standard-dose (120 kV, 75 mAs), respectively, and analyzed using the segmentation software OncoTREAT (MeVis, Bremen, Germany; version 1.3). Interobserver variability of volume measurements of 202 solid pulmonary nodules (mean diameter 11 mm, range 3.2-44.5 mm) was calculated for SD-CT and ULD-CT. With respect to interobserver variability, the 95% confidence interval for the relative differences in nodule volume in the intrascan analysis was measured with -9.7% to 8.3% (mean difference -0.7%) for SD-CT and with -12.6% to 12.4% (mean difference -0.2%) for ULD-CT. In the interscan analysis, the 95% confidence intervals for the differences in nodule volume ranged with -25.1% to -23.4% and 26.2% to 28.9% (mean difference 1.4% to 2.1%) dependent on the combination of readers and scans. Intrascan interobserver variability of volume measurements was comparable for ULD-CT and SD-CT data. The calculated variability of volume measurements in the interscan analysis was similar to the data reported in the literature for CT data acquired with equal radiation dose. Thus, the evaluated segmentation software provides nodule volumetry that appears to be independent of the dose level with which the CT source dataset is acquired.

Effect of Nodule Characteristics on Variability of Semiautomated Volume Measurements in Pulmonary Nodules Detected in a Lung Cancer Screening Program

To retrospectively assess volume measurement variability in solid pulmonary nodules (volume, 15-500 mm(3)) detected at lung cancer screening and to quantify the independent effects of nodule morphology, size, and location. This retrospective study was a substudy of the screening program that was approved by the Dutch Ministry of Health, and all participants provided written informed consent. Two independent readers used semiautomated software to measure the volume of pulmonary nodules detected in 6774 participants aged 50-75 years (5917 men). Nodules were classified according to their location (purely intraparenchymal, pleural based, juxtavascular, or fissure attached), morphology (smooth, polylobulated, spiculated, or irregular), and size (<or=50 mm(3) or >50 mm(3)). The level of agreement was expressed by using the absolute values of the relative volume differences (RVDs). Multivariate logistic regression analysis was performed, and odds ratios (ORs) were computed to quantify the independent effects of morphology, location, and size on RVD categories. Altogether, 4225 nodules in 2239 participants were included. Complete agreement in volume was obtained for 3646 (86%) of the nodules. Disagreement was small (absolute value of RVD < 5%) for 173 (4%) nodules, moderate (absolute value of RVD >or= 5% but < 15%) for 232 (6%), and large (absolute value of RVD >or= 15%) for 174 (4%). Multivariate analysis showed that the ORs of volume disagreement were 15.7, 3.1, and 1.9 for irregular, spiculated, and polylobulated nodules, respectively; 3.5, 2.6, and 2.1 for juxtavascular, pleural-based, and fissure-attached nodules, respectively; and 1.3 for large nodules compared with smooth, purely intraparenchymal, and small reference nodules. Nodule morphology, location, and size influence volume measurement variability, particularly for juxtavascular and irregular nodules.

3D ultrasound analysis of carotid plaque volume and surface morphology

Morphological characterization of carotid plaques has been used for risk stratification and evaluation of response to therapy, evaluation of new risk factors, genetic research, and for quantifying effects of new anti-atherosclerotic therapies. We developed a 3D US system that allows detailed studies of carotid plaques in 3D. Our software includes 3D reconstruction, viewing, manual and semi-automated segmentation of carotid plaques, and surface morphology analysis to be used for quantitative tracking of plaque changes. We evaluated our plaque quantification software by examining plaque volume measurement accuracy, variability, and plaque surface morphology. We used vascular test phantoms to study segmentation accuracy, and used 48 3D US carotid plaques of patients ranging in size from 13.2 mm 3 to 544.0 mm 3 to study plaque volume measurement variability. We compared results from the semi-automated plaque measurements to the results obtained from manual measurements, which were used as the “gold” standard. We developed a surface plaque morphology quantification technique based on the segmented plaque surface curvature and used it to analyze plaques. Accuracy of plaque volume measurements for the simulated plaques ranged from 4.2% to 1.5% for volumes ranging from 68.5 mm 3 to 286 mm 3. The variability study showed that coefficients of variation in the measurement of plaque volume decreased with increasing plaque size for both inter- (90.8–3.9%) and intra-observer (70.2–3.1%) measurements over the plaque sizes measured. Surface morphology analysis showed that 1 mm ulceration could be quantified and monitored for changes over time. The automated plaque quantification approach showed a little higher intra-observer variability than the manual technique, and its performance was better for segmenting the wall than the lumen. Our results indicate that our approach is sensitive tool and can be used in studies of plaque progression and regression as it relates to atherosclerosis treatment effects and can be used effectively in longitudinal studies for direct measurement carotid plaque volume.