Risk of Second Primary Malignancies among Patients with Early Gastric Cancer Exposed to Recurrent Computed Tomography Scans.
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SUBMITTER: Kim TJ
PROVIDER: S-EPMC7962111 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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: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:ObjectiveTo assess the cancer risk in children and adolescents following exposure to low dose ionising radiation from diagnostic computed tomography (CT) scans.DesignPopulation based, cohort, data linkage study in Australia. COHORT MEMBERS: 10.9 million people identified from Australian Medicare records, aged 0-19 years on 1 January 1985 or born between 1 January 1985 and 31 December 2005; all exposures to CT scans funded by Medicare during 1985-2005 were identified for this cohort. Cancers diagnosed in cohort members up to 31 December 2007 were obtained through linkage to national cancer records.Main outcomeCancer incidence rates in individuals exposed to a CT scan more than one year before any cancer diagnosis, compared with cancer incidence rates in unexposed individuals.Results60,674 cancers were recorded, including 3150 in 680,211 people exposed to a CT scan at least one year before any cancer diagnosis. The mean duration of follow-up after exposure was 9.5 years. Overall cancer incidence was 24% greater for exposed than for unexposed people, after accounting for age, sex, and year of birth (incidence rate ratio (IRR) 1.24 (95% confidence interval 1.20 to 1.29); P<0.001). We saw a dose-response relation, and the IRR increased by 0.16 (0.13 to 0.19) for each additional CT scan. The IRR was greater after exposure at younger ages (P<0.001 for trend). At 1-4, 5-9, 10-14, and 15 or more years since first exposure, IRRs were 1.35 (1.25 to 1.45), 1.25 (1.17 to 1.34), 1.14 (1.06 to 1.22), and 1.24 (1.14 to 1.34), respectively. The IRR increased significantly for many types of solid cancer (digestive organs, melanoma, soft tissue, female genital, urinary tract, brain, and thyroid); leukaemia, myelodysplasia, and some other lymphoid cancers. There was an excess of 608 cancers in people exposed to CT scans (147 brain, 356 other solid, 48 leukaemia or myelodysplasia, and 57 other lymphoid). The absolute excess incidence rate for all cancers combined was 9.38 per 100,000 person years at risk, as of 31 December 2007. The average effective radiation dose per scan was estimated as 4.5 mSv.ConclusionsThe increased incidence of cancer after CT scan exposure in this cohort was mostly due to irradiation. Because the cancer excess was still continuing at the end of follow-up, the eventual lifetime risk from CT scans cannot yet be determined. Radiation doses from contemporary CT scans are likely to be lower than those in 1985-2005, but some increase in cancer risk is still likely from current scans. Future CT scans should be limited to situations where there is a definite clinical indication, with every scan optimised to provide a diagnostic CT image at the lowest possible radiation dose.
| S-EPMC3660619 | biostudies-literature
Project description:BackgroundEarly gastric cancer (EGC) is defined as a lesion restricted to the mucosa or submucosa, independent of size or evidence of regional lymph node metastases. Although computed tomography (CT) is the main technique for determining the stage of gastric cancer (GC), the accuracy of CT for determining tumor invasion of EGC was still unsatisfactory by radiologists. In this research, we attempted to construct an AI model to discriminate EGC in portal venous phase CT images.MethodsWe retrospectively collected 658 GC patients from the first affiliated hospital of Nanchang university, and divided them into training and internal validation cohorts with a ratio of 8:2. As the external validation cohort, 93 GC patients were recruited from the second affiliated hospital of Soochow university. We developed several prediction models based on various convolutional neural networks, and compared their predictive performance.ResultsThe deep learning model based on the ResNet101 neural network represented sufficient discrimination of EGC. In two validation cohorts, the areas under the curves (AUCs) for the receiver operating characteristic (ROC) curves were 0.993 (95% CI: 0.984-1.000) and 0.968 (95% CI: 0.935-1.000), respectively, and the accuracy was 0.946 and 0.914. Additionally, the deep learning model can also differentiate between mucosa and submucosa tumors of EGC.ConclusionsThese results suggested that deep learning classifiers have the potential to be used as a screening tool for EGC, which is crucial in the individualized treatment of EGC patients.
| S-EPMC9748811 | biostudies-literature
Project description:This retrospective study analyzed a large population of gastric cancer (GC) patients treated between 2010 and 2015 to investigate the clinical features and predictive risk factors for developing secondary primary malignancies (SPMs). The cumulative incidence of SPM was assessed using Kaplan-Meier analysis. Competing risk analyses adjusted for mortality were conducted using stratified Cox proportional hazard regression models and multivariate analyses to identify independent predictors of SPM. A total of 3289 out of 167,747 GC patients were included in the analytic cohort, with 155 patients diagnosed with SPM. Patients whose histologic type other than adenocarcinomas (AC) and signet ring cell carcinoma (SRCC) emerged as an independent risk factor for developing SPM (hazard ratio [HR] 2.262, 95% confidence interval [CI] 1.146-4.465, P = 0.019) in multivariate Cox regression analysis. The surgical method, including biopsy/local excision (HR 2.3, [CI] 1.291-4.095, P = 0.005) and subtotal/total resection ([HR] 1.947, [CI] 1.028-3.687, P = 0.041), chemotherapy ([HR] 1.527, [CI] 1.006-2.316, P = 0.047), and histologic type ([HR] 2.318, [CI] 1.193-4.504, P = 0.013)), were identified as independent risk factors in the competitive risk model. Subgroup analyses, stratified by chemotherapy, revealed an increased risk of SPM among older patients. Furthermore, a nomogram was developed and internally validated to predict the cumulative incidence of SPM in GC patients (C-index = 0.73 for 72 months). These findings suggested that in specific histologic types of GC, the lymph node infiltration region missed after local surgical resection, and concomitant chemotherapy would have an increased risk of SPM for cancer survivors.
| S-EPMC11291716 | biostudies-literature
Project description:BackgroundRate of second primary malignancies (SPM) is steadily increasing over the last decades. New therapies, early diagnostic markers, screening tests for a larger number of individuals contribute to the increase prevalence of SPM. In the current study, we try to described the demographic composition of SPM victims, distribution of primary sites, and the impact of related factors on prognosis.MethodsWe conducted a retrospective study identifying patients over the age of 18 who were diagnosed with SPM from the 16 most common cancer sites between 2000 and 2013 from Surveillance, Epidemiology, and End Results data. Cox proportional hazards regression was used to analyze the relationship between different factors associated to the prognosis of SPM. Standard incidence rate of multiple primary (MP-SIR) was also calculated.ResultsA total of 303,753 patients were diagnosis with SPM and 76,168 of whom (25.08%) were included in our analytic cohort. Patients with prostate cancer was vulnerable to SPM, accounting for 34.59%, and SPM was prone to occur in lung and bronchus, accounting for 24.90%. The heat map shows that esophagus cancer survivors have the highest risk of developing stomachache tumors (SIR =5.08). The result of Cox regression suggests that a history of liver was associated with the shortest survival time (HR =1.64, 95% CI, 1.54-1.75, P<0.001).ConclusionsWith the advancement of medical standards, the survival time of cancer patients is prolonged, but the occurrence of SPM is also increasing, and the prognosis is not optimistic. More attention needs to be invested in the prevention and treatment of SPM.
| S-EPMC7290649 | biostudies-literature
Project description:Because the high-cost of medical imaging can cause a tremendous economic burden across the health care system, we investigated factors associated with taking additional computed tomography (CT) scans. Data of gastric cancer patients were eligible for analysis if the patient underwent a gastrectomy during the study period (2002-2013). We defined initial CT scans as those taken within 90 days from the surgery date. If there was an additional CT scan between the date of an initial CT scan and the surgery date, we regarded it as a reexamination. We used multivariate logistic regression analysis for reexamination CT scans. Among 3342 gastrectomy patients, 1165 participants underwent second CT scans. Transfer experience (adjusted odds ratio (OR) = 23.87, 95% confidence interval (CI) = 18.15-31.39) was associated with higher OR for reexamination. Among transferred patients, an increased number per 100 beds at the initial CT hospital was associated with a decreased OR for reexamination (OR = 0.88, 95% CI = 0.83-0.94), but increased beds in surgery hospitals was related to an increased OR for reexamination (OR = 1.29, 95% CI = 1.20-1.36). In our study, transfer experience, initial CT scan in a low-volume hospital, and surgical treatment in a high-volume hospital were associated with reexamination CT scans.
| S-EPMC7151052 | 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