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Objavljeno v DiRROS: 25.07.2024; Ogledov: 15; Prenosov: 3
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Ključne besede: medical physics, proton therapy, radiotherapy, medical imaging
Objavljeno v DiRROS: 25.07.2024; Ogledov: 18; Prenosov: 2
Celotno besedilo (1,08 MB)

Povzetek: Background. This randomised, double-blinded, single-centre study prospectively investigated the impact of goal directed therapy and fluid optimization with crystalloids or colloids on perioperative complications in patients un-dergoing brain tumour surgery. Main aim of the study was to investigate the impact of fluid type on postoperative complications.Patients and methods. 80 patients were allocated into two equal groups to be optimised with either crystalloids (n = 40) or colloids (n = 40). Invasive hemodynamic monitoring was used to adjust and maintain mean arterial pressure and cerebral oxygenation within the baseline values (± 20%) and stroke volume variation (SVV) ≤ 10%. Postoperative complications from different organ systems were monitored during the first 15 days after surgery. Hospital stay was also recorded.Results. Crystalloid group received significantly more fluids (p = 0.003) and phenylephrine (p = 0.02) compared to colloid group. This did not have any significant impact on perioperative complications and hospital stay, since no dif-ferences between groups were observed. Conclusions. Either crystalloids or colloids could be used for fluid optimization in brain tumour surgery. If protocol-ised perioperative haemodynamic management is used, the type of fluid does not have significant impact on the outcome.
Objavljeno v DiRROS: 25.07.2024; Ogledov: 20; Prenosov: 2
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Povzetek: Treatment of early-stage non-small cell lung cancer (NSCLC) is rapidly evolving. When introducing novelties, real-life data on effectiveness of currently used treatment strategies are needed. The present study evaluated outcomes of stage I–IIIA NSCLC patients treated with upfront radical surgery in everyday clinical practice, between 2010–2017. Data of 539 consecutive patients were retrieved from a prospective hospital-based registry. All diagnostic, treatment and follow-up procedures were performed at the same thoracic oncology centre according to the valid guidelines. The primary outcome was overall survival (OS) analysed by clinical(c) and pathological(p) TNM (tumour, node, metastases) stage. The impact of clinicopathological characteristics on OS was evaluated using univariable (UVA) and multivariable regression analysis (MVA). With a median follow-up of 53.9 months, median OS and 5-year OS rate in the overall population were 90.4 months and 64.4%. Five-year OS rates by pTNM stage I, II and IIIA were 70.2%, 60.21%, and 49.9%, respectively. Both cTNM and pTNM stages were associated with OS; but only pTNM retained its independent prognostic value (p = 0.003) in MVA. Agreement between cTNM and pTNM was 69.0%. Next to pTNM, age (p = 0.001) and gender (p = 0.004) retained their independent prognostic value for OS. The study showed favourable outcomes of resectable stage I–IIIA NSCLC treated with upfront surgery in real-life. Relatively low agreement between cTNM and pTNM stages and independent prognostic value of only pTNM, observed in real-life data, suggest that surgery remains the most accurate provider of the anatomical stage of disease and important upfront therapy.
Ključne besede: resectable NSCLC, upfront surgery, real-life data, overall survival, prognostic factors
Objavljeno v DiRROS: 25.07.2024; Ogledov: 15; Prenosov: 7
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Povzetek: In the setting of primary hyperparathyroidism (PHPT), [18F]fluorocholine PET/CT (FCH-PET) has excellent diagnostic performance, with experienced practitioners achieving 97.7% accuracy in localising hyperfunctioning parathyroid tissue (HPTT). Due to the relative triviality of the task for human readers, we explored the performance of deep learning (DL) methods for HPTT detection and localisation on FCH-PET images in the setting of PHPT. Patients and methods. We used a dataset of 93 subjects with PHPT imaged using FCH-PET, of which 74 subjects had visible HPTT while 19 controls had no visible HPTT on FCH-PET. A conventional Resnet10 as well as a novel mPETResnet10 DL model were trained and tested to detect (present, not present) and localise (upper left, lower left, upper right or lower right) HPTT. Our mPETResnet10 architecture also contained a region-of-interest masking algorithm that we evaluated qualitatively in order to try to explain the model’s decision process. Results. The models detected the presence of HPTT with an accuracy of 83% and determined the quadrant of HPTT with an accuracy of 74%. The DL methods performed statistically worse (p < 0.001) in both tasks compared to human readers, who localise HPTT with the accuracy of 97.7%. The produced region-of-interest mask, while not showing a consistent added value in the qualitative evaluation of model’s decision process, had correctly identified the foreground PET signal. Conclusions. Our experiment is the first reported use of DL analysis of FCH-PET in PHPT. We have shown that it is possible to utilize DL methods with FCH-PET to detect and localize HPTT. Given our small dataset of 93 subjects, results are nevertheless promising for further research
Ključne besede: primary hyperparathyroidism, deep learning, nuclear medicine
Objavljeno v DiRROS: 25.07.2024; Ogledov: 14; Prenosov: 8
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