Feasibility of computed tomography-derived surgical margin assessment in an ex vivo sublobar lung resection model.

Objectives: Computed tomography (CT) imaging of a sublobar resection specimen may inform intraoperative surgical margin assessment. However, consistency with final pathological margins has not been previously evaluated. In this study, we investigated the concordance between surgical margin measurements by CT versus pathology measurements using an ex vivo sublobar lung resection model.

Deep learning-based prediction of nodal metastasis in lung cancer using endobronchial ultrasound.

Objective: Endobronchial ultrasound-guided transbronchial needle aspiration is a vital tool for mediastinal and hilar lymph node staging in patients with lung cancer. Despite its high diagnostic performance and safety, it has a limited negative predictive value. Our objective was to evaluate the diagnostic performance of deep learning-based prediction of lung cancer lymph node metastases using convolutional neural networks developed from automatically extracted images of endobronchial ultrasound videos without supervision of the lymph node location.

Incidence and Clinical Presentation of Pre- and Postoperative Seizures in Patients With Posterior Fossa Meningiomas.

Introduction: Seizures are a common symptom of supratentorial meningiomas with pre- and postoperative seizure rates of approximately 30% and 12%, respectively, especially in parasagittal and convexity meningiomas. Less is known about the association between seizures and posterior fossa meningiomas. This study evaluates the prevalence, potential causes, and outcomes of seizures in patients who have undergone surgery for posterior fossa meningioma.

Investigating the effects of a temperature dependent photodynamic dose: A numerical study.

Significance: Photodynamic therapy (PDT) and photothermal therapy (PTT) show promise as cancer treatments, but challenges in generating large ablative volumes for deep-seated tumours persist. Using simulations, this study investigates combined PDT and PTT to increase treatment volumes, including the impact of a temperature-dependent PDT dose on the treatment volume radius.

Approach: A finite-element model, using the open-source SfePy package, was developed to simulate combined interstitial photothermal and photodynamic treatments.