Objective: To evaluate the accuracy of clinical staging of advanced laryngeal cancer and to morphologically analyze the underestimated cases.
Design: We conducted a retrospective histopathologic study of larynges from patients who had had total laryngectomy and were seen over a 21-year period.
Setting: Academic tertiary referral medical center.
Participants: Forty-one patients had clinically staged T3 laryngeal cancer and 16 patients had T4 cancer.
Intervention: Patients all underwent wide-field total laryngectomy. All larynges were processed as whole-organ serial sections in the coronal plane.
Outcome Measure: The incidence of clinically underestimated laryngeal cancer. During this investigation, it became obvious that predictive indicators of thyroid cartilage involvement could be established.
Results: Clinical underestimation had been made in approximately 50% of all T3 laryngeal cancer cases. The extent of the cartilage involvement in the underestimated group was characterized by microinvasion without penetration; approximately 90% of the cartilage involvement affected the thyroid notch and adjacent area. We established five objective indicators of thyroid cartilage involvement: (1) extensive cartilage ossification (risk for cartilage involvement, 73%); (2) glottic fixation (54%); (3) transglottic cancer (74%); (4) tumor length longer than the entire vocal fold length or longer than 2 cm (66%); and (5) extensive involvement of the anterior commissure (67%).
Conclusions: Clinical underestimation of T4 laryngeal cancer was high because thyroid cartilage involvement was not accurately diagnosed. We believe our indicators of thyroid cartilage involvement will provide objective guidelines for laryngeal cancer staging and will contribute to more reliable clinical cancer-staging decisions.
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http://dx.doi.org/10.1001/archotol.1993.01880210038006 | DOI Listing |
BMC Surg
January 2025
Department of Cardiothoracic Surgery, Fifth Affiliated Hospital of Sun Yat-Sen University, No.52 East Meihua Road, Zhuhai, Guangdong Province, 519000, China.
Background: Laparoscopic-assisted single-port mediastinoscopic esophagectomy is a safe and effective emerging minimally invasive esophagectomy, but little has been reported about the learning curve for this technology. The goal of the study was to determine the number of procedures to achieve different levels of proficiency on the learning curve.
Methods: This study retrospectively analyzed data from consecutive surgeries performed by the same surgeon at the same center from 2016 to 2021.
JAMA Otolaryngol Head Neck Surg
January 2025
Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Importance: Intraoperative nerve monitoring (IONM) is not considered standard of care during thyroidectomy, and guidelines are vague about its use in the absence of strong evidence of superiority over visualization of the recurrent laryngeal nerve (RLN) alone.
Objective: To characterize patterns of IONM use during thyroidectomy in the US and evaluate the association of IONM with postoperative outcomes.
Design, Setting, And Participants: This cohort study used the National Surgical Quality Improvement Program (NSQIP) thyroidectomy data from January 1, 2016, to December 31, 2022.
Occup Med (Lond)
January 2025
Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Background: Exposure to strong inorganic acid mists (SIAMs) in the workplace has been linked to respiratory tract cancers.
Aims: We conducted a meta-analysis of cohort and case-control studies examining the association between occupational SIAMs and respiratory tract cancers other than laryngeal cancer, which is already established.
Methods: Studies mentioned in the 1992 IARC Monograph on carcinogenicity of SIAMs were combined with later studies identified from a systematic search of Scopus, PubMed and Embase.
Sci Rep
January 2025
Faculty of Applied Sciences, Macao Polytechnic University, Macao, 999078, China.
Data scarcity in medical images makes transfer learning a common approach in computer-aided diagnosis. Some disease classification tasks can rely on large homogeneous public datasets to train the transferred model, while others cannot, i.e.
View Article and Find Full Text PDFClin Lung Cancer
December 2024
Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA. Electronic address:
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