This study provides a comprehensive assessment of own body representation and linguistic representation of bodies in general in women with typical and atypical anorexia nervosa (AN). Methods: In a series of desktop experiments, participants rated a set of adjectives according to their match with a series of computer generated bodies varying in body mass index, and generated prototypic body shapes for the same set of adjectives. We analysed how body mass index of the bodies was associated with positive or negative valence of the adjectives in the different groups. Further, body image and own body perception were assessed. Results: In a German-Italian sample comprising 39 women with AN, 20 women with atypical AN and 40 age matched control participants, we observed effects indicative of weight stigmatization, but no significant differences between the groups. Generally, positive adjectives were associated with lean bodies, whereas negative adjectives were associated with obese bodies. Discussion: Our observations suggest that patients with both typical and atypical AN affectively and visually represent body descriptions not differently from healthy women. We conclude that overvaluation of low body weight and fear of weight gain cannot be explained by generally distorted perception or cognition, but require individual consideration.

Our aim was to compare the image quality and patient dose of contrast-enhanced oncologic chest-CT of a first-generation photon-counting detector (PCD-CT) and a second-generation dual-source dual-energy CT (DSCT). For this reason, one hundred consecutive oncologic patients (63 male, 65 ± 11 years, BMI: 16–42 kg/m2) were prospectively enrolled and evaluated. Clinically indicated contrast-enhanced chest-CT were obtained with PCD-CT and compared to previously obtained chest-DSCT in the same individuals. The median time interval between the scans was three months. The same contrast media protocol was used for both scans. PCD-CT was performed in QuantumPlus mode (obtaining full spectral information) at 120 kVp. DSCT was performed using 100 kV for Tube A and 140 kV for Tube B. “T3D” PCD-CT images were evaluated, which emulate conventional 120 keV polychromatic images. For DSCT, the convolution algorithm was set at I31f with class 1 iterative reconstruction, whereas comparable Br40 kernel and iterative reconstruction strengths (Q1 and Q3) were applied for PCD-CT. Two radiologists assessed image quality using a five-point Likert scale and performed measurements of vessels and lung parenchyma for signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and in the case of pulmonary metastases tumor-to-lung parenchyma contrast ratio. PCD-CT CNRvessel was significantly higher than DSCT CNRvessel (all, p < 0.05). Readers rated image contrast of mediastinum, vessels, and lung parenchyma significantly higher in PCD-CT than DSCT images (p < 0.001). Q3 PCD-CT CNRlung_parenchyma was significantly higher than DSCT CNRlung_parenchyma and Q1 PCD-CT CNRlung_parenchyma (p < 0.01). The tumor-to-lung parenchyma contrast ratio was significantly higher on PCD-CT than DSCT images (0.08 ± 0.04 vs. 0.03 ± 0.02, p < 0.001). CTDI, DLP, SSDE mean values for PCD-CT and DSCT were 4.17 ± 1.29 mGy vs. 7.21 ± 0.49 mGy, 151.01 ± 48.56 mGy * cm vs. 288.64 ± 31.17 mGy * cm and 4.23 ± 0.97 vs. 7.48 ± 1.09, respectively. PCD-CT enables oncologic chest-CT with a significantly reduced dose while maintaining image quality similar to a second-generation DSCT for comparable protocol settings.

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