Citations

ABSTRACT Objective There is limited consensus on endoscopic skull base surgery (ESBS) reconstruction principles. This study aims to generate comprehensive themes regarding ESBS reconstruction by pooling the experiences of ESBS experts, with comparison to a literature review of current published evidence. Methods Structured qualitative interviews of ESBS experts regarding postoperative management and reconstruction of various defect locations were conducted. Results A total of 68 experts comprising 40 academic teams across 13 countries with an average of 18 years of ESBS experience were included. We propose 10 stepwise algorithms for common skull base reconstruction scenarios based on these expert interviews. When available, the nasoseptal flap is used for all high_flow cerebrospinal leak defects. Multilayered reconstruction is favored at all anatomical subsites with increasing number of layers for increasing defect size and complexity. Heterogeneity exists in terms of inlay technique and materials, free grafting versus various pedicled flap options for low‐flow defects or in the absence of a nasal septum, nasal packing, tissue sealant, lumbar drain use, and postoperative management. Commonalities and discrepancies between experts were summarized. Conclusion Skull base reconstruction and post‐ESBS management is highly complex with a wide variety of practice patterns and expert strategies. Further research of higher quality evidence is warranted to identify optimal management patterns, though the current work aims to inform surgeons on these controversial areas by drawing from numerous experiences.

Pulmonary auscultation is essential for detecting abnormal lung sounds during physical assessments, but its reliability depends on the operator. Machine learning (ML) models offer an alternative by automatically classifying lung sounds. ML models require substantial data, and public databases aim to address this limitation. This systematic review compares characteristics, diagnostic accuracy, concerns, and data sources of existing models in the literature. Papers published from five major databases between 1990 and 2022 were assessed. Quality assessment was accomplished with a modified QUADAS-2 tool. The review encompassed 62 studies utilizing ML models and public-access databases for lung sound classification. Artificial neural networks (ANN) and support vector machines (SVM) were frequently employed in the ML classifiers. The accuracy ranged from 49.43% to 100% for discriminating abnormal sound types and 69.40% to 99.62% for disease class classification. Seventeen public databases were identified, with the ICBHI 2017 database being the most used (66%). The majority of studies exhibited a high risk of bias and concerns related to patient selection and reference standards. Summarizing, ML models can effectively classify abnormal lung sounds using publicly available data sources. Nevertheless, inconsistent reporting and methodologies pose limitations to advancing the field, and therefore, public databases should adhere to standardized recording and labeling procedures.

The accurate measurement of the linear accelerator (linac) radiation isocenter is critical, especially for stereotactic treatment. Traditional quality assurance (QA) procedure focuses on the measurement of single radiation isocenter, usually of 6 megavoltage (MV) photon beams. Single radiation isocenter is also commonly assumed in treatment planning systems (TPS). Due to different flattening filters and bending magnet and steering parameters, the radiation isocenter of one energy mode can deviate from another if no special effort was devoted. We present the first experience of the multiradiation isocenters alignment on an Elekta linac, as well as its corresponding QA procedure and clinical impact. An 8 mm ball‐bearing (BB) phantom was placed at the 6 MV radiation isocenter using an Elekta isocenter search algorithm, based on portal images. The 3D radiation isocenter shifts of other photon energy modes relative to the 6 MV were determined. Beam profile scanning for different field sizes was used as an independent method to determine the 2D multiradiation isocenters alignment. To quantify the impact of radiation isocenter offset on targeting accuracy, the 10 MV radiation isocenter was manually offset from that for 6 MV by adjusting the bending magnet current. Because our table isocenter was mechanically aligned to the 6 MV radiation isocenter, the deviation of the table isocentric rotation from the "shifted" 10 MV radiation isocenter after bending magnet adjustment was assessed. Winston‐Lutz test was also performed to confirm the overall radiation isocenter positioning accuracy for all photon energies. The portal image method showed the radiation isocenter of the 10 MV flattening filter‐free mode deviated from others before beam parameter adjustment. After the adjustment, the deviation was greatly improved from 0.96 to 0.35 mm relative to the 6 MV radiation isocenter. The same finding was confirmed by the profile‐scanning method. The maximum deviation of the table isocentric rotation from the 10 MV radiation isocenter was observed to linearly increase with the offset between 6 and 10 MV radiation isocenter; 1 mm radiation isocenter offset can translate to almost 2 mm maximum deviation of the table isocentric rotation from the 10 MV radiation isocenter. The alignment of the multiradiation isocenters is particularly important for high‐precision radiotherapy. Our study provides the medical physics community with a quantitative measure of the multiradiation isocenters alignment. A routine QA method should be considered, to examine the radiation isocenters alignment during the linac acceptance.PACS number: 87.55.Qr, 87.56.bd, 87.56.Fc