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Cancers
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Advances in Diagnostics and Prognostics in the Management of Intrathoracic...
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Advances in Diagnostics and Prognostics in the Management of Intrathoracic Malignancies

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

Deadline for manuscript submissions: 31 August 2025 | Viewed by 2261

Special Issue Editors

Dr. Akshay Jatin Patel

E-Mail Website
Guest Editor
1. Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK
2. Department of Thoracic Surgery, University Hospitals Birmingham, Birmingham, UK
Interests: thymic tumors; cardiothoracic surgery
Dr. Marcus Taylor

E-Mail Website
Guest Editor
Department of Thoracic Surgery, Manchester University Hospital NHS Foundation Trust, Wythenshawe Hospital, Manchester, UK
Interests: lung cancer; thoracic surgery

Special Issue Information

Dear Colleagues,

Within the dynamic landscape of oncology, the management of intrathoracic malignancies has always been at the forefront of medical and technological advances with respect to diagnostic and prognostic innovations. As we have delved deeper into the intricacies of this disease's biology, our understanding of its aggressiveness, patterns, and symptomatology has expanded. Consequently, there is a pressing need to further enhance our diagnostic methods, enabling the earlier detection and monitoring of minimal-residual disease and micro-metastatic disease. Traditional staging systems, while valuable, may fall short in elucidating the complexities of disease patterns in the current era. Thus, the integration of molecular biomarkers, radiomics, artificial intelligence, and immunobiological parameters is imperative to provide comprehensive insights into disease prognosis.

This Special Issue will delve into the pivotal strides made in diagnostics and prognostics for intrathoracic malignancies, illuminating contemporary approaches shaping clinical practice. By harnessing cutting-edge technologies and insights, this collection seeks to showcase real-world examples, providing clinicians with essential tools to navigate complexities, optimize patient care, and advance towards more precise, personalized therapeutic strategies in the fight against intrathoracic cancers.

Dr. Akshay Jatin Patel
Dr. Marcus Taylor
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intrathoracic malignancies
  • diagnostics
  • prognostics
  • molecular biomarkers
  • radiomics
  • artificial intelligence
  • immunobiological parameters
  • personalized therapy

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Published Papers (2 papers)

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Research

15 pages, 1410 KiB  
Article
Primary Intrathoracic Synovial Sarcoma: An Analysis of Outcomes of This Rare Disease
by Riddhi R. Patel, Andrew J. Bishop, Alexander J. Lazar, Patrick P. Lin, Robert S. Benjamin, Shreyaskumar R. Patel, Joseph Ludwig, Vinod Ravi, Ara A. Vaporciyan and Dejka M. Araujo
Cancers 2025, 17(5), 745; https://doi.org/10.3390/cancers17050745 - 22 Feb 2025
Viewed by 625
Abstract
Background: Primary intrathoracic synovial sarcoma (SS) is a rare entity. The objective of this study was to evaluate survival outcomes for patients with intrathoracic SS presenting with localized disease at diagnosis. Methods: We conducted a retrospective review of 63 patients diagnosed with intrathoracic [...] Read more.
Background: Primary intrathoracic synovial sarcoma (SS) is a rare entity. The objective of this study was to evaluate survival outcomes for patients with intrathoracic SS presenting with localized disease at diagnosis. Methods: We conducted a retrospective review of 63 patients diagnosed with intrathoracic SS between 1997 and 2020. The Kaplan–Meier method and log-rank test were used to estimate the progression-free survival (PFS), overall survival (OS), local recurrence-free survival (LRFS), and metastasis-free survival (MFS). The hazard ratios were estimated by using Cox proportional hazards regression. Median follow-up time, age-at-diagnosis, and primary tumor size were 31 months (range: 4–218 months), 43 years (range: 18–77), and 7 cm (range: 1–23), respectively. Results: Sixty-two of sixty-three (98%) patients had their primary tumor resected, from whom eighteen (29%) and forty-three (69%) had received neo/adjuvant radiotherapy and chemotherapy, respectively. Median PFS, OS, and MFS were 1.2, 3.0, and 1.1 years, respectively. Based on multivariable analyses, patients with ≥5 cm tumor size had poorer OS (versus < 5 cm; HR: 2.66; 95% CI: 1.16, 6.11; LR-p = 0.014). Importantly, the receipt of neo/adjuvant chemotherapy was the only factor associated with both a more favorable PFS (HR: 0.33; 95% CI: 0.17, 0.65; LR-p = 0.0002) and a more favorable MFS (median 1.33 years versus no chemo 0.5 years; HR: 0.35; 95% CI: 0.17, 0.73; LR-p = 0.005). Conclusions: Outcomes associated with intrathoracic SS remain poor. Factors associated with poorer outcomes include larger tumors and omission of chemotherapy in the management of localized disease. We recommend providing perioperative chemotherapy to all patients with ≥5 cm tumor size to improve progression and metastasis-free survival. Full article
(This article belongs to the Special Issue Advances in Diagnostics and Prognostics in the Management of Intrathoracic Malignancies)
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15 pages, 5785 KiB  
Article
Enhancing Survival Outcome Predictions in Metastatic Non-Small Cell Lung Cancer Through PET Radiomics Analysis
by Shuo Wang, Darryl Belemlilga, Yu Lei, Apar Kishor P Ganti, Chi Lin, Samia Asif, Jacob T Marasco, Kyuhak Oh and Sumin Zhou
Cancers 2024, 16(22), 3731; https://doi.org/10.3390/cancers16223731 - 5 Nov 2024
Viewed by 1163
Abstract
(1) Background: Advanced-stage lung cancer poses significant management challenges. The goal of this study was to identify crucial clinical and PET radiomics features that enable prognostic stratification for predicting outcomes. (2) Methods: PET radiomics features of the primary lung lesions were extracted from [...] Read more.
(1) Background: Advanced-stage lung cancer poses significant management challenges. The goal of this study was to identify crucial clinical and PET radiomics features that enable prognostic stratification for predicting outcomes. (2) Methods: PET radiomics features of the primary lung lesions were extracted from 99 patients with stage IVB NSCLC, and the robustness of these PET radiomics features was evaluated against uncertainties stemming from extraction parameters and contour variation. We trained three survival risk models (clinical, radiomics, and a composite) through a penalized Cox model framework. We also created a Balanced Random Forest classification predictive model, using the selected features, to predict 1-year survival. (3) Results: We identified 367 common PET radiomics features that exhibited robustness to perturbations introduced by contour variation and extraction parameters. Our findings indicated that both the radiomics and the composite model outperformed the clinical model in stratifying the risk for survival with statistical significance. In predicting 1-year survival, the radiomics model and the composite model also achieved better predicting accuracies compared to the clinical model. (4) Conclusions: Robust PET radiomics analysis successfully facilitated the stratification of patient risk for survival outcomes and predicted 1-year survival in stage IVB NSCLC. Full article
(This article belongs to the Special Issue Advances in Diagnostics and Prognostics in the Management of Intrathoracic Malignancies)
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