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Open research questions in Lung Cancer Diagnosis and Treatment

208 unresolved questions extracted from the limitations and future-work sections of 589 Lung Cancer Diagnosis and Treatment papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Further adaptation and fine-tuning of foundation models for clinical applications. Investigation of the effectiveness of the framework in different populations and settings.

    Imaging-based development and validation of artificial intelligence models for lung adenocarcinoma precursor lesions and early lung adenocarcinoma presenting as pulmonary nodules · 2026 · DOI

  • Conventional morphological assessment is partly subjective and may be insufficient for reliably differentiating pGGNs from mGGNs. Accurate preoperative assessment of pulmonary nodule invasiveness remains challenging.

    Imaging-based development and validation of artificial intelligence models for lung adenocarcinoma precursor lesions and early lung adenocarcinoma presenting as pulmonary nodules · 2026 · DOI

  • Further prospective and randomized studies are needed, - Studies should focus on radical-intent treatment of unresectable stage II-III disease, - Research should investigate the use of advanced radiation techniques

    Hypofractionation in Unresectable Stage II-III NSCLC: A Systematic Technical Review and Practical Recommendations · 2026 · DOI

  • There is a lack of prospective and randomized evidence for hypofractionation in unresectable stage II-III NSCLC. Published studies are heterogeneous in stage, intent, and technique. There is a need for caution and use of advanced radiation techniques when applying hypofractionation.

    Hypofractionation in Unresectable Stage II-III NSCLC: A Systematic Technical Review and Practical Recommendations · 2026 · DOI

  • Further clinical trials to establish comparative safety and efficacy, - Investigation of schedule-dependent interactions between pulsed radiation and PD-L1 blockade, - Research on the technical deliverability of PULSAR regimens

    Personalized Ultrafractionated Stereotactic Adaptive Radiotherapy in Lung Cancer and Lung Metastases: A Systematic Review · 2026 · DOI

  • algorithmic bias, - data integration, - regulatory approval, - ethical transparency, - limited by variability in diagnostic performance and prognostic value of biomarkers

    Artificial Intelligence in Oncologic Thoracic Surgery: Clinical Decision Support and Emerging Applications · 2026 · DOI

  • The gap in algorithmic bias and data integration limits the widespread adoption of AI in thoracic surgery. The need for multicenter validation and explainable AI to ensure safe and effective clinical integration. The lack of robust governance frameworks to ensure the responsible implementation of AI in thoracic surgery.

    Artificial Intelligence in Oncologic Thoracic Surgery: Clinical Decision Support and Emerging Applications · 2026 · DOI

  • While technical outcomes are well documented, patient experiences within clinical trials remain under-explored.

    Patient experiences in trials of minimally invasive thoracic surgery: A mixed-methods study · 2026 · DOI

  • Nevertheless, few studies have examined the impact of such AI-based software on the education and training of residents.

    Utilization of artificial intelligence-based pulmonary nodule target reconstruction software in clinical practice education for standardized training residents · 2025 · DOI

  • In NeoCOAST-2, the first neoadjuvant trial examining an ADC plus chemo-immunotherapy in resectable NSCLC, pCR rates were highest in the datopotamab-deruxtecan-containing arm, warranting further investigation in larger trials of ADCs and checkpoint inhibition in the neoadjuvant setting.

    Perioperative durvalumab plus chemotherapy plus new agents for resectable non-small-cell lung cancer: the platform phase 2 NeoCOAST-2 trial · 2025 · DOI

  • Approximately 20% of patients with NSCLC are diagnosed with stage IIIA-IIIB disease, for which the optimal treatment remains unclear.

    Surgical Techniques for Non-Small-Cell Lung Cancer After Neoadjuvant Chemo-Immunotherapy: State of Art and Review of the Literature · 2025 · DOI

  • Importance: Adherence to annual lung cancer screening (LCS) is a proposed quality metric for LCS programs, but data linking annual adherence to lung cancer outcomes are lacking.

    Adherence to Annual Lung Cancer Screening and Rates of Cancer Diagnosis · 2025 · DOI

  • However, the sex-specific outcomes and drawbacks of screening INS remain unexplored, with data predominantly focused on women.

    Gender Disparities and Lung Cancer Screening Outcomes Among Individuals Who Have Never Smoked · 2025 · DOI

  • However, few studies have examined how institutional proficiency evolves with the introduction of new surgeons and how this transition impacts surgical outcomes in RATS.

    Institutional proficiency and learning curves in robotic-assisted thoracoscopic surgery: a single-center retrospective analysis using the cumulative sum method · 2025 · DOI

  • However, only a few data are available about the ES-NSCLC molecular landscape and the impact of oncogene addiction on therapy definition.

    Early-Stage Non-Small Cell Lung Cancer: Prevalence of Actionable Alterations in a Monocentric Consecutive Cohort · 2024 · DOI

  • Future research should focus on optimizing screening strategies to capture more at-risk populations and enhance the detection of harder-to-diagnose subtypes like squamous cell carcinoma.

    Changes in Staging and Management of Non-Small Cell Lung Cancer (NSCLC) Patients Following the Implementation of Low-Dose Chest Computed Tomography (LDCT) Screening at Kaohsiung Medical University Hospital · 2024 · DOI

  • Although sampling with conventional bronchoscopy presents lower complication rates compared to transthoracic needle biopsy (TTNB), it is limited by the inability to reach distal airways.

    Robotic Bronchoscopy in Lung Cancer Diagnosis · 2024 · DOI

  • The specific effects of varying heart and lung doses on OS in LA-NSCLC patients have not been thoroughly investigated, especially their combined impact on survival.

    Risk Stratification by Combination of Heart and Lung Dose in Locally Advanced Non-Small-Cell Lung Cancer after Radiotherapy · 2024 · DOI

  • Only a few reports have discussed specific techniques, particularly for complex segmentectomies.

    Uniportal Video-Assisted Thoracoscopic Segmentectomy for Early-Stage Non-Small Cell Lung Cancer: Overview, Indications, and Techniques · 2024 · DOI

  • Although endobronchial ultrasound-guided transbronchoscopic lung biopsy (EBUS-TBLB) has been found to be useful for the assessment of intrapulmonary nodules in adults, few data are available for the clinical diagnosis of pulmonary tuberculosis.

    Diagnostic efficacy of endobronchial ultrasound-guided transbronchoscopic lung biopsy for identifying tuberculous nodules · 2024 · DOI

  • Future studies are needed to determine the significance of TME on prognosis and treatment.

    Combined expert-in-the-loop—random forest multiclass segmentation U-net based artificial intelligence model: evaluation of non-small cell lung cancer in fibrotic and non-fibrotic microenvironments · 2024 · DOI

  • There is a need for reliable diagnostic tools capable of detecting subtle functional impairments in long COVID patients. The study highlights the gap in understanding the functional consequences of pulmonary abnormalities in long COVID patients.

    Functional alterations due to post-COVID-19 lung lesions — lessons from a multicenter V/Q SPECT/CT based registry · 2026 · DOI

  • To evaluate the proposed framework on other datasets and domains. To develop more efficient and scalable methods for improving the robustness of deep learning models. To apply the proposed approach to other medical imaging tasks.

    Robust Histopathology Subtyping via Perturbation Fidelity in Deep Classifier · 2026 · DOI

  • The vulnerability of deep learning models to real-world imaging perturbations. The need for more robust deep learning models for histopathology subtyping. The lack of effective methods for improving the reliability of deep learning models.

    Robust Histopathology Subtyping via Perturbation Fidelity in Deep Classifier · 2026 · DOI

  • The current process of interpreting lung CT scans is time-consuming and relies heavily on radiologists' experience. There is a need for an automated system that can accurately detect lung cancer.

    Lung cancer detection using Deep learning · 2026 · DOI

Most-cited papers in Lung Cancer Diagnosis and Treatment

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208 open questions have been extracted from the limitations and future-work passages of 589 Lung Cancer Diagnosis and Treatment papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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