Variability of lung tumor measurements on repeat computed tomography scans taken within 15 minutes.
Ontology highlight
ABSTRACT: Purpose
We use changes in tumor measurements to assess response and progression, both in routine care and as the primary objective of clinical trials. However, the variability of computed tomography (CT) -based tumor measurement has not been comprehensively evaluated. In this study, we assess the variability of lung tumor measurement using repeat CT scans performed within 15 minutes of each other and discuss the implications of this variability in a clinical context.Patients and methods
Patients with non-small-cell lung cancer and a target lung lesion ≥ 1 cm consented to undergo two CT scans within a period of minutes. Three experienced radiologists measured the diameter of the target lesion on the two scans in a side-by-side fashion, and differences were compared.Results
Fifty-seven percent of changes exceeded 1 mm in magnitude, and 33% of changes exceeded 2 mm. Median increase and decrease in tumor measurements were +4.3% and -4.2%, respectively, and ranged from 23% shrinkage to 31% growth. Measurement changes were within ± 10% for 84% of measurements, whereas 3% met criteria for progression according to Response Evaluation Criteria in Solid Tumors (RECIST; ≥ 20% increase). Smaller lesions had greater variability of percent measurement change (P = .005).Conclusion
Apparent changes in tumor diameter exceeding 1 to 2 mm are common on immediate reimaging. Increases and decreases less than 10% can be a result of the inherent variability of reimaging. Caution should be exercised in interpreting the significance of small changes in lesion size in the care of individual patients and in the interpretation of clinical trial results.
SUBMITTER: Oxnard GR
PROVIDER: S-EPMC3157977 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundPancreatic perfusion computed tomography (CT) imaging is increasingly used for neoplastic grading, predicting prognosis, and evaluating the response to therapy. To optimize the clinical pancreatic CT perfusion imaging methods, we evaluated 2 different CT scanning protocols concerning pancreas perfusion parameters.MethodsA retrospective study was conducted on 40 patients who underwent whole pancreas CT perfusion scanning in The First Affiliated Hospital of Zhengzhou University. Of these 40 patients, 20 patients in group A underwent continuous perfusion scanning, while 20 patients in group B underwent intermittent perfusion scanning. For group A, continuous axial scanning was performed 25 times, and the total scan time was 50 s. For group B, arterial phase helical perfusion scanning was performed 8 times, and then venous phase helical perfusion scanning was performed 15 times, with a total scan time of 64.6 to 70.0 s. A comprehensive list of perfusion parameters between different parts of the pancreas and the 2 groups were compared. The effective radiation dose for the 2 scanning methods was analyzed.ResultsThe parameter of the mean slope of increase (MSI) at different pancreatic parts in group A differed (P=0.028). The pancreas head had the lowest value, and the tail had the highest (about a 20% difference). In group A compared to group B, the blood volume of the pancreatic head was smaller (15.256±2.925 vs. 16.953±3.602), the positive enhanced integral was smaller (0.307±0.050 vs. 0.344±0.060) and the permeability surface was larger (34.205±9. 612 vs. 24.377±8.413); the blood volume of the pancreatic neck was smaller (13.940±2.691 vs. 17.173±3.918), the positive enhanced integral was smaller (0.304±0.088 vs. 0.361±0.051) and the permeability surface was larger (34.898±11.592 vs. 25. 794±8.149); the blood volume of the pancreatic body was smaller (16.142±4.006 vs. 18.401±2.513), the positive enhanced integral was smaller (0.305±0.093 vs. 0.342±0.048) and the permeability surface was larger (28.861±10.448 vs. 22.158±6. 017); the blood volume of the pancreatic tail was smaller (16.446±3.709 vs. 17.374±3.781), the positive enhanced integral was smaller (0.304±0.057 vs. 0.350±0.073) and the permeability surface was larger (27.823±8.228 vs. 21.509±7.768) (P<0.05). The effective radiation dose in the intermittent scan mode was slightly lower at 16.657±2.259 mSv than in the continuous scan mode (17.973±3.698 mSv).ConclusionsDifferent CT scanning intervals had a significant influence on whole pancreas blood volume, permeability surface, and positive enhanced integral. These demonstrate the high sensitivity of intermittent perfusion scanning for identifying perfusion abnormalities. Therefore, for the diagnosis of pancreatic diseases, intermittent pancreatic CT perfusion may be more advantageous.
| S-EPMC10167426 | biostudies-literature
Project description:ObjectiveTo determine inter-observer and inter-examination variability of manual attenuation measurements of the vertebrae in low-dose unenhanced chest computed tomography (CT).MethodsThree hundred and sixty-seven lung cancer screening trial participants who underwent baseline and repeat unenhanced low-dose CT after 3 months because of an indeterminate lung nodule were included. The CT attenuation value of the first lumbar vertebrae (L1) was measured in all CTs by one observer to obtain inter-examination reliability. Six observers performed measurements in 100 randomly selected CTs to determine agreement with limits of agreement and Bland-Altman plots and reliability with intraclass correlation coefficients (ICCs). Reclassification analyses were performed using a threshold of 110 HU to define osteoporosis.ResultsInter-examination reliability was excellent with an ICC of 0.92 (p < 0.001). Inter-examination limits of agreement ranged from -26 to 28 HU with a mean difference of 1 ± 14 HU. Inter-observer reliability ICCs ranged from 0.70 to 0.91. Inter-examination variability led to 11.2 % reclassification of participants and inter-observer variability led to 22.1 % reclassification.ConclusionsVertebral attenuation values can be manually quantified with good to excellent inter-examination and inter-observer reliability on unenhanced low-dose chest CT. This information is valuable for early detection of osteoporosis on low-dose chest CT.Key points• Vertebral attenuation values can be manually quantified on low-dose unenhanced CT reliably. • Vertebral attenuation measurements may be helpful in detecting subclinical low bone density. • This could become of importance in the detection of osteoporosis.
| S-EPMC4972882 | biostudies-literature
Project description:Introduction Accurate identification of infarcts in non-contrast computed tomography (NC-CT) scans of the brain is fundamental in the diagnosis and management of patients with stroke. Quantification of image contrast properties at the boundaries of ischemic infarct regions in NC-CT can contribute to a more precise manual or automatic delineation of these regions. Here we explore these properties quantitatively. Methods We retrospectively investigated 519 NC-CT studies of 425 patients with clinically confirmed ischemic strokes. The average and standard deviation (SD) of patients' age was 67.5?±?12.4 years and the average(median)±SD time from symptoms onset to NC-CT examination was 27.4(12)±35.7?h. For every scan with an ischemic lesion identified by experts, the image contrast of the lesion vs. normal surrounding parenchyma was calculated as a difference of mean Hounsfield Unit (HU) of 1-5 consecutive voxels (the contrast window width) belonging to the lesion and to the parenchyma. This contrast was calculated at each single voxel of ischemic lesion boundaries (previously delineated by the experts) in horizontal and vertical directions in each image. The distributions of obtained horizontal, vertical and both contrasts combined were calculated among all 519 NC-CTs. Results The highest applicative contrast window width was identified as 5 voxels. The ischemic infarcts were found to be characterized by 6.60?HU, 8.28?HU and 7.55?HU mean values for distributions of horizontal, vertical and combined contrasts. Approximately 40-50% of the infarct boundary voxels were found to refer to the image contrast below 5?HU. Conclusion Low image contrast of ischemic lesions prevents accurate delineation of the infarcts in NC-CT.
| S-EPMC5564335 | biostudies-literature
Project description:A cervicogenic headache (CEH) is difficult to diagnose due to its varied pathology. We evaluated the usefulness of single-photon emission computed tomography/computed tomography (SPECT/CT) in diagnosing CEH and its interventional treatment. Retrospectively, 23 patients diagnosed with CEH between March 2016 to August 2018 were allocated to SPECT/CT (n = 11) and control (n = 12) groups. The SPECT/CT group was further stratified into SPECT/CT(+) and SPECT/CT(-) groups according to the presence of positive findings. Patients in the SPECT/CT group underwent an intra-articular injection at a radiologically verified lesion site, whereas those in the control group underwent third occipital nerve block. Clinical outcomes were evaluated with the visual analog scale (VAS), neck disability index (NDI), and global perceived effect (GPE) scale at baseline, and at one, three, and six months postoperatively. The SPECT/CT group showed less VAS, NDI, and GPE scores at six months postoperatively (2.91 ± 2.30 vs. 4.42 ± 1.62, p = 0.08; 38.00 ± 16.54 vs. 48.7 ± 12.40, p = 0.093; 2.00 ± 1.41 vs. 3.17 ± 1.11, p = 0.039). Successful responders at six months postoperatively were higher in the SPECT/CT(+) group than in the control group (75% vs. 0%). SPECT/CT can identify arthritic changes and accurately define therapeutic targets.
| S-EPMC7074323 | biostudies-literature
Project description:PurposeTo examine the use of multiple fast-helical free breathing computed tomography (FHFBCT) scans for ventilation measurement.MethodsTen patients were scanned 25 times in alternating directions using a FHFBCT protocol. Simultaneously, an abdominal pneumatic bellows was used as a real-time breathing surrogate. Regions-of-interest (ROIs) were selected from the upper right lungs of each patient for analysis. The ROIs were first registered using a published registration technique (pTV). A subsequent follow-up registration employed an objective function with two terms, a ventilation-adjusted Hounsfield Unit difference and a conservation-of-mass term labeled ΔΓ that denoted the difference between the deformation Jacobian and the tissue density ratio. The ventilations were calculated voxel-by-voxel as the slope of a first-order fit of the Jacobian as a function of the breathing amplitude.ResultsThe ventilations of the 10 patients showed different patterns and magnitudes. The average ventilation calculated from the deformation vector fields (DVFs) of the pTV and secondary registration was nearly identical, but the standard deviation of the voxel-to-voxel differences was approximately 0.1. The mean of the 90th percentile values of ΔΓ was reduced from 0.153 to 0.079 between the pTV and secondary registration, implying first that the secondary registration improved the conservation-of-mass criterion by almost 50% and that on average the correspondence between the Jacobian and density ratios as demonstrated by ΔΓ was less than 0.1. This improvement occurred in spite of the average of the 90th percentile changes in the DVF magnitudes being only 0.58 mm.ConclusionsThis work introduces the use of multiple free-breathing CT scans for free-breathing ventilation measurements. The approach has some benefits over the traditional use of 4-dimensional CT (4DCT) or breath-hold scans. The benefit over 4DCT is that FHFBCT does not have sorting artifacts. The benefits over breath-hold scans include the relatively small motion induced by quiet respiration versus deep-inspiration breath hold and the potential for characterizing dynamic breathing processes that disappear during breath hold.
| S-EPMC8568635 | biostudies-literature
Project description:Pulmonary emphysema is a destructive disease of the lungs that is currently diagnosed via visual assessment of lung Computed Tomography (CT) scans by a radiologist. Visual assessment can have poor inter-rater reliability, is time consuming, and requires access to trained assessors. Quantitative methods that reliably summarize the biologically relevant characteristics of an image are needed to improve the way lung diseases are characterized. The goal of this work was to show how spatial point process models can be used to create a set of radiologically derived quantitative lung biomarkers of emphysema. We formalized a general framework for applying spatial point processes to lung CT scans, and developed a Shot Noise Cox Process to quantify how radiologically based emphysematous tissue clusters into larger structures. Bayesian estimation of model parameters was done using spatial Birth-Death MCMC (BD-MCMC). In simulations, we showed the BD-MCMC estimation algorithm is able to accurately recover model parameters. In an application to real lung CT scans from the COPDGene cohort, we showed variability in the clustering characteristics of emphysematous tissue across disease subtypes that were based on visual assessments of the CT scans.
| S-EPMC6867806 | biostudies-literature
Project description:This study's objective was to determine the accuracy of using current computed tomography (CT) scan and software techniques for rapid prototyping by quantifying the margin of error between CT models and laser scans of canine skull specimens. Twenty canine skulls of varying morphology were selected from an anatomy collection at a veterinary school. CT scans (bone and standard algorithms) were performed for each skull, and data segmented (testing two lower threshold settings of 226HU and -650HU) into 3-D CT models. Laser scans were then performed on each skull. The CT models were compared to the corresponding laser scan to determine the error generated from the different types of CT model parameters. This error was then compared between the different types of CT models to determine the most accurate parameters. The mean errors for the 226HU CT models, both bone and standard algorithms, were not significant from zero error (p = 0.1076 and p = 0.0580, respectively). The mean errors for both -650HU CT models were significant from zero error (p < 0.001). Significant differences were detected between CT models for 3 CT model comparisons: Bone (p < 0.0001); Standard (p < 0.0001); and -650HU (p < 0.0001). For 226HU CT models, a significant difference was not detected between CT models (p = 0.2268). Independent of the parameters tested, the 3-D models derived from CT imaging accurately represent the real skull dimensions, with CT models differing less than 0.42 mm from the real skull dimensions. The 226HU threshold was more accurate than the -650HU threshold. For the 226HU CT models, accuracy was not dependent on the CT algorithm. For the -650 CT models, bone was more accurate than standard algorithms. Knowing the inherent error of this procedure is important for use in 3-D printing for surgical planning and medical education.
| S-EPMC6433237 | biostudies-literature
Project description:ImportanceThe American College of Radiology (ACR) has recognized the importance of minimizing radiation doses used for lung cancer screening (LCS) computed tomography (CT). However, without standard protocols, doses could still be unnecessarily high, reducing screening margin of benefit.ObjectiveTo characterize LCS CT radiation doses and identify factors explaining variation.Design, setting, and participantsWe prospectively collected LCS examination dose metrics, from 2016 to 2017, at US institutions in the University of California, San Francisco International Dose Registry. Institution-level factors were collected through baseline survey. Mixed-effects linear and logistic regression models were estimated using forward variable selection. Results are presented as percentage excess dose and odds ratios (ORs) with 95% confidence intervals (CIs). The analysis was conducted between 2018 and 2019.Main outcomes and measuresLog-transformed measures of (1) mean volume CT dose index (CTDIvol, mGy), reflecting the average radiation dose per slice; (2) mean effective dose (ED, mSv), reflecting the total dose received and estimated future cancer risk; (3) proportion of CT scans using radiation doses above ACR benchmarks (CTDIvol >3 mGy, ED >1 mSv); and (4) proportion of CT scans using radiation doses above 75th percentile of registry doses (CTDIvol >2.7 mGy, ED >1.4 mSv).ResultsData were collected for 12 529 patients undergoing LCS CT scans performed at 72 institutions. Overall, 7232 participants (58%) were men, and the median age was 65 years (interquartile range [IQR], 60-70). Of 72 institutions, 15 (21%) had median CTDIvol and 47 (65%) had median ED above ACR guidelines. Institutions allowing any radiologists to establish protocols had 44% higher mean CTDIvol (mean dose difference [MDD], 44%; 95% CI, 19%-69%) and 27% higher mean ED (MDD, 27%; 95% CI, 5%-50%) vs those limiting who established protocols. Institutions allowing any radiologist to establish protocols had higher odds of examinations exceeding ACR CTDIvol guidelines (OR, 12.0; 95% CI, 2.0-71.4), and 75th percentile of registry CTDIvol (OR, 19.0; 95% CI, 1.9-186.7) or ED (OR, 8.5; 95% CI, 1.7-42.9). Having lead radiologists establish protocols resulted in lower odds of doses exceeding ACR ED guidelines (OR, 0.01; 95% CI, 0.001-0.1). Employing external vs internal medical physicists was associated with increased odds of exceeding ACR CTDIvol guidelines (OR, 6.1; 95% CI, 1.8-20.8). Having medical physicists establish protocols was associated with decreased odds of exceeding 75th percentile of registry CTDIvol (OR, 0.09; 95% CI, 0.01-0.59). Institutions reporting protocol updates as needed had 27% higher mean CTDIvol (MDD, 27%; 95% CI, 8%-45%).Conclusions and relevanceFacilities varied in LCS CT radiation dose distributions. Institutions limiting protocol creation to lead radiologists and having internal medical physicists had lower doses.
| S-EPMC6764003 | biostudies-literature
Project description:Frontal sinus variation has been used in forensic anthropology to aid in positive identification since the 1920s. As imaging technology has evolved, so has the quality and quantity of data that practitioners can collect. This study examined frontal sinus morphological and dimensional variation on computed tomography (CT) scans in 325 individuals for assigned sex females and males from African-, Asian-, European-, and Latin American-derived groups. Full coronal sinus outlines from medically derived CT images were transferred into SHAPE v1.3 for elliptical Fourier analysis (EFA). The dimensional data were measured directly from the images using the MicroDicom viewer. Statistical analyses-Pearson's chi-square, ANOVA, and Tukey post hoc tests-were run in R Studio. Results indicated that 3.7% lacked a frontal sinus and 12.0% had a unilateral sinus, usually on the left (74.3%). Additionally, no statistically significant morphological clustering using EFA was found based on assigned sex and/or population affinity. However, there were statistically significant differences dimensionally (height and depth) when tested against assigned sex and population affinity, indicating that the interactive effects of sexual dimorphism and adaptive population histories influence the dimensions but not the shape of the frontal sinus.
| S-EPMC9405290 | biostudies-literature
Project description:Contrast-enhanced computed tomography scans (CECT) are routinely used in the evaluation of different clinical scenarios, including the detection and characterization of hepatocellular carcinoma (HCC). Quantitative medical image analysis has been an exponentially growing scientific field. A number of studies reported on the effects of variations in the contrast enhancement phase on the reproducibility of quantitative imaging features extracted from CT scans. The identification and labeling of phase enhancement is a time-consuming task, with a current need for an accurate automated labeling algorithm to identify the enhancement phase of CT scans. In this study, we investigated the ability of machine learning algorithms to label the phases in a dataset of 59 HCC patients scanned with a dynamic contrast-enhanced CT protocol. The ground truth labels were provided by expert radiologists. Regions of interest were defined within the aorta, the portal vein, and the liver. Mean density values were extracted from those regions of interest and used for machine learning modeling. Models were evaluated using accuracy, the area under the curve (AUC), and Matthew's correlation coefficient (MCC). We tested the algorithms on an external dataset (76 patients). Our results indicate that several supervised learning algorithms (logistic regression, random forest, etc.) performed similarly, and our developed algorithms can accurately classify the phase of contrast enhancement.
| S-EPMC10836663 | biostudies-literature