Soms is het nodig om röntgenonderzoek te laten doen. Met een röntgenonderzoek kunnen eventuele afwijkingen in het lichaam worden gevonden. Bijvoorbeeld met een röntgenfoto van je gebit bij de tandarts. Of een CT-scan van je buik om te kijken of hier een afwijking zit. Maar, is dit ook veilig wanneer je zwanger bent? Ongeboren kinderen zijn gevoeliger voor röntgenstraling dan volwassenen vanwege snel delende weefsels, vertelt onderzoeker en verloskundige Maria Dalmaijer. De risico’s lijken echter erg klein te zijn. Bovendien is de hoeveelheid straling die bij de baby komt verwaarloosbaar. Harmen Bijwaard, lector Medische Technologie aan Hogeschool Inholland legt uit dat röntgenonderzoeken tijdens de zwangerschap daarom veilig zijn. Bij een uitgebreidere CT-scan van de buik zal de arts bekijken of er andere onderzoeken mogelijk zijn.
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Stereotactische radiotherapie van wervelmetastasen vereist een hoge precisie in alle stappen van de behandeling. Deze techniek werd in het VU medisch centrum in 2009 geïntroduceerd. Data met betrekking tot de behandeling van de eerste 17 klinische patiënten is geëvalueerd. Deze patiënten werden behandeld op een Novalis Tx versneller die beschikt over zowel een kilovolt (kV) cone beam CT (CBCT) scan als het ExacTrac® kV röntgensysteem. De gebruikte methode van de verschillende beeldmodaliteiten voor positionering en verificatie, de behandelingstijd en de intrafractie beweging worden in dit artikel beschreven.
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Cone beam CT scanners use much less radiation than to normal CT scans. However, compared to normal CT scans the images are noisy, showing several artifacts. The UNet Convolutional Neural Network may provide a way to reconstruct the a CT image from cone beam scans.
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Background & aims: Low muscle mass and -quality on ICU admission, as assessed by muscle area and -density on CT-scanning at lumbar level 3 (L3), are associated with increased mortality. However, CT-scan analysis is not feasible for standard care. Bioelectrical impedance analysis (BIA) assesses body composition by incorporating the raw measurements resistance, reactance, and phase angle in equations. Our purpose was to compare BIA- and CT-derived muscle mass, to determine whether BIA identified the patients with low skeletal muscle area on CT-scan, and to determine the relation between raw BIA and raw CT measurements. Methods: This prospective observational study included adult intensive care patients with an abdominal CT-scan. CT-scans were analysed at L3 level for skeletal muscle area (cm2) and skeletal muscle density (Hounsfield Units). Muscle area was converted to muscle mass (kg) using the Shen equation (MMCT). BIA was performed within 72 h of the CT-scan. BIA-derived muscle mass was calculated by three equations: Talluri (MMTalluri), Janssen (MMJanssen), and Kyle (MMKyle). To compare BIA- and CT-derived muscle mass correlations, bias, and limits of agreement were calculated. To test whether BIA identifies low skeletal muscle area on CT-scan, ROC-curves were constructed. Furthermore, raw BIA and CT measurements, were correlated and raw CT-measurements were compared between groups with normal and low phase angle. Results: 110 patients were included. Mean age 59 ± 17 years, mean APACHE II score 17 (11–25); 68% male. MMTalluri and MMJanssen were significantly higher (36.0 ± 9.9 kg and 31.5 ± 7.8 kg, respectively) and MMKyle significantly lower (25.2 ± 5.6 kg) than MMCT (29.2 ± 6.7 kg). For all BIA-derived muscle mass equations, a proportional bias was apparent with increasing disagreement at higher muscle mass. MMTalluri correlated strongest with CT-derived muscle mass (r = 0.834, p < 0.001) and had good discriminative capacity to identify patients with low skeletal muscle area on CT-scan (AUC: 0.919 for males; 0.912 for females). Of the raw measurements, phase angle and skeletal muscle density correlated best (r = 0.701, p < 0.001). CT-derived skeletal muscle area and -density were significantly lower in patients with low compared to normal phase angle. Conclusions: Although correlated, absolute values of BIA- and CT-derived muscle mass disagree, especially in the high muscle mass range. However, BIA and CT identified the same critically ill population with low skeletal muscle area on CT-scan. Furthermore, low phase angle corresponded to low skeletal muscle area and -density. Trial registration: ClinicalTrials.gov (NCT02555670).
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Background: Traumatic brain injury (TBI) is in the developed countries the most common cause of death and disability in childhood. Aim: The purpose of this study is to estimate the incidence of TBI for children and young people in an urbanised region of the Netherlands and to describe relevant characteristics of this group. Methods: Patients, aged 1 month - 24 years who presented with traumatic brain injury at the Erasmus University Hospital (including the Sophia Children's Hospital) in 2007 and 2008 were included in a retrospective study. Data were collected by means of diagnosis codes and search terms for TBI in patient records. The incidence of TBI in the different referral areas of the hospital for standard, specialised and intensive patient care was estimated. Results: 472 patients met the inclusion criteria. The severity of the Injury was classified as mild in 342 patients, moderate in 50 patients and severe in 80 patients. The total incidence of traumatic brain injury in the referral area of the Erasmus University Hospital was estimated at 113.9 young people per 100.000. The incidence for mild traumatic brain injury was estimated at 104.4 young people, for moderate 6.1 and for severe 3.4 young people per 100.000. Conclusion: The ratio for mild, moderate and severe traumatic brain injury in children and young people was 33.7e1.8e1.In the mild TBI group almost 17% of the patients reported sequelae. The finding that 42% of them had a normal brain CT scan at admission underwrites the necessity of careful follow up of children and young people with mild TBI.
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Generalized loss of muscle mass is associated with increased morbidity and mortality in patients with cancer. The gold standard to measure muscle mass is by using computed tomography (CT). However, the aim of this prospective observational cohort study was to determine whether point-of-care ultrasound (POCUS) could be an easy-to-use, bedside measurement alternative to evaluate muscle status. Patients scheduled for major abdominal cancer surgery with a recent preoperative CT scan available were included. POCUS was used to measure the muscle thickness of mm. biceps brachii, mm. recti femoris, and mm. vasti intermedius 1 day prior to surgery. The total skeletal muscle index (SMI) was derived from patients’ abdominal CT scan at the third lumbar level. Muscle force of the upper and lower extremities was measured using a handheld dynamometer. A total of 165 patients were included (55% male; 65 ± 12 years). All POCUS measurements of muscle thickness had a statistically significant correlation with CT-derived SMI (r ≥ 0.48; p < 0.001). The strongest correlation between POCUS muscle measurements and SMI was observed when all POCUS muscle groups were added together (r = 0.73; p < 0.001). Muscle strength had a stronger correlation with POCUS-measured muscle thickness than with CT-derived SMI. To conclude, this study indicated a strong correlation between combined muscle thickness measurements performed by POCUS- and CT-derived SMI and measurements of muscle strength. These results suggest that handheld ultrasound is a valid tool for the assessment of skeletal muscle status.
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Rationale: Patients with cancer of the upper gastrointestinal tract or lung are more likely to present with malnutrition at diagnosis than, for instance, patients with melanoma. Low muscle mass is an indicator of malnutrition and can be determined by computed tomography (CT) analysis of the skeletal muscle index (SMI) at the 3rd lumbar vertebra (L3) level. However, CT images at L3 are not always available. At each vertebra level, we determined if type of cancer, i.e., head and neck cancer (HNC), oesophageal cancer (OC) or lung cancer (LC) vs. melanoma (ME) was associated with lower SMI. Methods: CT images from adult patients with HNC, OC, LC or ME were included and analyzed. Scans were performed in the patient’s initial staging after diagnosis. MIM software version 7.0.1 was used to contour the muscle areas for all vertebra levels. Skeletal muscle area was corrected for stature to calculate SMI (cm2/m2). We tested for the association of HNC, OC, or LC diagnosis vs ME with SMI by univariate and multivariate linear regression analyses. In the multivariate analyses, age (years), sex, and body mass index (BMI; kg/m2) were included. Betas (B;95%CI) were calculated and statistical significance was set at p
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BACKGROUND: In critically ill patients, muscle loss is associated with adverse outcomes. Raw bioelectrical impedance analysis (BIA) parameters (eg, phase angle [PA] and impedance ratio [IR]) have received attention as potential markers of muscularity, nutrition status, and clinical outcomes. Our objective was to test whether PA and IR could be used to assess low muscularity and predict clinical outcomes.METHODS: Patients (≥18 years) having an abdominal computed tomography (CT) scan and admitted to intensive care underwent multifrequency BIA within 72 hours of scan. CT scans were landmarked at the third lumbar vertebra and analyzed for skeletal muscle cross-sectional area (CSA). CSA ≤170 cm(2) for males and ≤110 cm(2) for females defined low muscularity. The relationship between PA (and IR) and CT muscle CSA was evaluated using multivariate regression and included adjustments for age, sex, body mass index, Charlson Comorbidity Index, and admission type. PA and IR were also evaluated for predicting discharge status using dual-energy X-ray absorptiometry-derived cut-points for low fat-free mass index.RESULTS: Of 171 potentially eligible patients, 71 had BIA and CT scans within 72 hours. Area under the receiver operating characteristic (c-index) curve to predict CT-defined low muscularity was 0.67 (P ≤ .05) for both PA and IR. With covariates added to logistic regression models, PA and IR c-indexes were 0.78 and 0.76 (P < .05), respectively. Low PA and high IR predicted time to live ICU discharge.CONCLUSION: Our study highlights the potential utility of PA and IR as markers to identify patients with low muscularity who may benefit from early and rigorous intervention.
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A growing body of evidence indicates that natural environments can positively influence people. This study investigated whether the use of motion nature projection in computed tomography (CT) imaging rooms is effective in mitigating psycho-physiological anxiety (vs. no intervention) using a quasirandomized experiment (N ¼ 97). Perceived anxiety and pleasantness of the room were measured using a questionnaire, and physiological arousal was measured using a patient monitor system. A mediation analysis showed that motion nature projection had a negative indirect effect on perceived anxietythrough a higher level of perceived pleasantness of the room. A linear-mixed-model showed that heart rate and diastolic blood pressure were lower when motion nature was projected. In conclusion, by creating a more pleasant imaging room through motion nature projection, hospitals can indirectly reduce patient's psycho-physiological anxiety (vs. no image projection) during a CT scan.
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INTRODUCTION: In patients with cancer, low muscle mass has been associated with a higher risk of fatigue, poorer treatment outcomes, and mortality. To determine body composition with computed tomography (CT), measuring the muscle quantity at the level of lumbar 3 (L3) is suggested. However, in patients with cancer, CT imaging of the L3 level is not always available. Thus far, little is known about the extent to which other vertebra levels could be useful for measuring muscle status. In this study, we aimed to assess the correlation of the muscle quantity and quality between any vertebra level and L3 level in patients with various tumor localizations.METHODS: Two hundred-twenty Positron Emission Tomography (PET)-CT images of patients with four different tumor localizations were included: 1. head and neck ( n = 34), 2. esophagus ( n = 45), 3. lung ( n = 54), and 4. melanoma ( n = 87). From the whole body scan, 24 slices were used, i.e., one for each vertebra level. Two examiners contoured the muscles independently. After contouring, muscle quantity was estimated by calculating skeletal muscle area (SMA) and skeletal muscle index (SMI). Muscle quality was assessed by calculating muscle radiation attenuation (MRA). Pearson correlation coefficient was used to determine whether the other vertebra levels correlate with L3 level. RESULTS: For SMA, strong correlations were found between C1-C3 and L3, and C7-L5 and L3 ( r = 0.72-0.95). For SMI, strong correlations were found between the levels C1-C2, C7-T5, T7-L5, and L3 ( r = 0.70-0.93), respectively. For MRA, strong correlations were found between T1-L5 and L3 ( r = 0.71-0.95). DISCUSSION: For muscle quantity, the correlations between the cervical, thoracic, and lumbar levels are good, except for the cervical levels in patients with esophageal cancer. For muscle quality, the correlations between the other levels and L3 are good, except for the cervical levels in patients with melanoma. If visualization of L3 on the CT scan is absent, the other thoracic and lumbar vertebra levels could serve as a proxy to measure muscle quantity and quality in patients with head and neck, esophageal, lung cancer, and melanoma, whereas the cervical levels may be less reliable as a proxy in some patient groups.
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