Journal: Clinical Nuclear Medicine

Article Title: Imaging of Small Lung Nodules on Modern SAFOV and LAFOV PET in Combination With Data-driven Motion Correction: Implications for Current Practice

doi: 10.1097/RLU.0000000000006278

Figure Lengend Snippet: Distribution of lung nodule SUV max with different PET imaging methods. Boxplots show the distribution of SUV max values for LAFOV and sSAFOV PET scans, with and without DDG. The central line represents the median and boxes the 25th to 75th percentile. The whiskers extend to the most extreme value within 1.5x IQR from the box edge. Beyond that, outliers are plotted as individual points. Asterisks indicate statistical significance between the connected groups (*** P <0.001). DDG indicates data-driven gating; LAFOV, long-axial field-of-view; sSAFOV, simulated short-axial field-of-view; IQR, interquartile range.

Article Snippet: We created reconstructions with and without data-driven gating (OncoFreeze AI, Siemens Healthineers, Erlangen, Germany) for both modes.

Techniques: Imaging

Journal: Clinical Nuclear Medicine

Article Title: Imaging of Small Lung Nodules on Modern SAFOV and LAFOV PET in Combination With Data-driven Motion Correction: Implications for Current Practice

doi: 10.1097/RLU.0000000000006278

Figure Lengend Snippet: Distribution of lung nodule SUV max by nodule size and PET imaging method. Boxplots show the distribution of SUV max values for nodules in different size categories, with each shade of gray representing a different PET imaging method. The central line represents the median and boxes the 25th to 75th percentile. The whiskers extend to the most extreme value within 1.5x IQR from the box edge. Beyond that, outliers are plotted as individual points. DDG indicates data-driven gating; LAFOV, long-axial field-of-view; sSAFOV, simulated short-axial field-of-view, IQR, interquartile range.

Article Snippet: We created reconstructions with and without data-driven gating (OncoFreeze AI, Siemens Healthineers, Erlangen, Germany) for both modes.

Techniques: Imaging

Journal: Clinical Nuclear Medicine

Article Title: Imaging of Small Lung Nodules on Modern SAFOV and LAFOV PET in Combination With Data-driven Motion Correction: Implications for Current Practice

doi: 10.1097/RLU.0000000000006278

Figure Lengend Snippet: Violin plots comparing noise levels in several reference organs across different PET imaging methods. The violin shapes represent the probability density of the noise values in the blood pool, liver, and lung parenchyma. Noise is expressed as SD of SUV mean . An interval plot is overlaid, depicting median (black dot), IQR (thick bars), and thin whiskers extending to the most extreme values within 1.5x IQR. DDG indicates data-driven gating; LAFOV, long-axial field-of-view; sSAFOV, simulated short-axial field-of-view; IQR, interquartile range.

Article Snippet: We created reconstructions with and without data-driven gating (OncoFreeze AI, Siemens Healthineers, Erlangen, Germany) for both modes.

Techniques: Imaging

Journal: Clinical Nuclear Medicine

Article Title: Imaging of Small Lung Nodules on Modern SAFOV and LAFOV PET in Combination With Data-driven Motion Correction: Implications for Current Practice

doi: 10.1097/RLU.0000000000006278

Figure Lengend Snippet: Improvement rate (%) for contrast-to-noise ratio by size and imaging method compared with sSAFOV. Boxplots show the distribution of relative improvement in CNR over sSAFOV (depicted as dashed horizontal bar) by adding data-driven gating (DDG), switching to long-axial field-of-view (LAFOV), or combining both methods (LAFOV + DDG). The central line represents the median and boxes the 25th to 75th percentile. The whiskers extend to the most extreme value within 1.5x IQR from the box edge. Beyond that, outliers are plotted as individual points. Asterisks indicate statistical significance between the connected groups (*** P <0.001). CNR indicates contrast-to-noise ratio; DDG, data-driven gating; LAFOV, long-axial field-of-view; sSAFOV, simulated short-axial field-of-view; IQR, interquartile range.

Article Snippet: We created reconstructions with and without data-driven gating (OncoFreeze AI, Siemens Healthineers, Erlangen, Germany) for both modes.

Techniques: Imaging

Journal: Clinical Nuclear Medicine

Article Title: Imaging of Small Lung Nodules on Modern SAFOV and LAFOV PET in Combination With Data-driven Motion Correction: Implications for Current Practice

doi: 10.1097/RLU.0000000000006278

Figure Lengend Snippet: Receiver operating characteristic (ROC) curves evaluating classification performance for different imaging methods. Facetted plot shows the ROC curves for nodules of different sizes: regardless of size ( A ), <6 mm ( B ), from 6 to 8 mm ( C ), and >8 mm ( D ). Colored lines represent different PET imaging methods. Curves plot Sensitivity versus 1-Specificity, with the dotted line indicating random chance (AUC = 0.5). DDG indicates data-driven gating; LAFOV, long-axial field-of-view; sSAFOV, simulated short-axial field-of-view.

Article Snippet: We created reconstructions with and without data-driven gating (OncoFreeze AI, Siemens Healthineers, Erlangen, Germany) for both modes.

Techniques: Imaging

Journal: Clinical Nuclear Medicine

Article Title: Imaging of Small Lung Nodules on Modern SAFOV and LAFOV PET in Combination With Data-driven Motion Correction: Implications for Current Practice

doi: 10.1097/RLU.0000000000006278

Figure Lengend Snippet: Example SUV images of a patient with malignant lung lesions. Shown are maximum intensity projections of the 4 different imaging methods ( A– D ) of the same patient. The patient is an 83-year-old man with small cell lung cancer, with lesions in the central and lower right lobe. The red arrow indicates the lung nodule of interest. This example displays the correction of breathing-related smearing artefacts with DDG and the improvement in image contrast with LAFOV. Lesion SUVmax were A: 13.3, B: 15.2, C: 7.6, D: 9.4. DDG indicates data-driven gating; LAFOV, long-axial field-of-view; sSAFO, simulated short-axial field-of-view.

Article Snippet: We created reconstructions with and without data-driven gating (OncoFreeze AI, Siemens Healthineers, Erlangen, Germany) for both modes.

Techniques: Imaging