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Robotic and Thoracoscopic Surgery for Lung Cancer

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: 28 February 2027 | Viewed by 620

Editor


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Guest Editor
Division of Cardiothoracic Surgery, Department of Surgery, University of Alabama-Birmingham Medical Center, Birmingham, AL, USA
Interests: robotic surgery; lung resection; esophagectomy; segmentectomy; lobectomy

Special Issue Information

Dear Colleagues,

Minimally invasive lung resection has become the standard of care for early-stage lung cancer over the past two decades, and studies have demonstrated its superiority over lung resection via thoracotomy with regard to patient recovery, perioperative complications, and even oncologic outcomes and survival. Current research focuses on comparisons between robotic and non-robotic thoracoscopic lung resections, each of which offers advantages and disadvantages over the other. Recently, attention has focused on controversial topics such as the role of lobectomy vs. sublobar resection for lung cancer, radiomic and pathologic indicators of increased recurrence risk (“high risk” stage I lung cancer), the recommended extent of lymph node dissection, and the role of neoadjuvant chemoimmunotherapy in the care of lung cancer patients. This Special Issue will examine the current data on some of these controversial issues to help guide the practice of modern-day general thoracic surgeons. 

Prof. Dr. Benjamin Wei
Guest Editor

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Keywords

  • robotic
  • thoracoscopic
  • lobectomy
  • segmentectomy
  • wedge resection
  • lymph node dissection
  • neoadjuvant therapy
  • immunotherapy
  • spread through air spaces
  • radiomics

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Published Papers (1 paper)

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Research

14 pages, 1117 KB  
Article
Machine Learning-Driven Radiomics for an Early-Stage Predictive Model of Nodal Upstaging in Thoracic Oncology
by Ivan Lomangino, Giacomo Grisorio, Domenico Albano, Luca Vecchiarelli, Matteo Rota, Matteo Baldi, Letizia Perri, Mauro Roberto Benvenuti, Salvatore Grisanti and Francesco Bertagna
Cancers 2026, 18(15), 2470; https://doi.org/10.3390/cancers18152470 - 31 Jul 2026
Viewed by 312
Abstract
Objectives: Precise lymph node staging remains a cornerstone in the management of early-stage and locally advanced non-small cell lung cancer (NSCLC), directly influencing surgical planning and multimodal therapy. Despite the widespread use of 2-[18F]FDG PET/CT, occult nodal metastases frequently lead to unexpected upstaging [...] Read more.
Objectives: Precise lymph node staging remains a cornerstone in the management of early-stage and locally advanced non-small cell lung cancer (NSCLC), directly influencing surgical planning and multimodal therapy. Despite the widespread use of 2-[18F]FDG PET/CT, occult nodal metastases frequently lead to unexpected upstaging after surgery, potentially affecting prognosis and therapeutic strategies. This study aimed to investigate whether radiomic features derived from preoperative PET/CT scans can predict nodal involvement in patients with early-stage lung cancer. Methods: A retrospective analysis was conducted on 124 patients with cT1N0 NSCLC who underwent 2-[18F]FDG PET/CT scans as part of the preoperative workup, followed by anatomical lung resection and systematic mediastinal lymph node dissection. Radiomic features were extracted from PET predictive of pathological nodal upstaging. Results: During the study period, 67 patients who underwent anatomical lung resection for early-stage lung cancer demonstrated unexpected nodal metastasis; a continuous series of 57 patients with the same clinical TMN was enrolled as a control group. Several radiomic parameters were significantly associated with nodal upstaging. According to variable importance (VIMP) analysis, metabolic tumor volume (MTV), total lesion glycolysis (TLG), run-length non-uniformity (RLNU), and gray-level non-uniformity (GLNU) emerged as the strongest predictors of lymph node involvement. Conclusions: Although the clinical utility of these findings remains to be validated, radiomic analysis of 2-[18F]FDG PET/CT imaging offers non-invasive biomarkers that may enhance the preoperative prediction of nodal involvement in early-stage NSCLC. Integrating radiomics into clinical workflows could improve surgical decision-making, refine patient selection, and reduce the incidence of unforeseen nodal upstaging. Full article
(This article belongs to the Special Issue Robotic and Thoracoscopic Surgery for Lung Cancer)
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