Background: A pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NACRT) ensures long-term survival in esophageal squamous cell carcinoma (ESCC) patients following esophagectomy, but pCR patients are a minority. The aim here was to identify prognostic factors in patients with non-pCR ESCC after NACRT.
Methods: This is a retrospective study. Investigated were 5-year overall survival (OS), disease-specific survival (DSS), and relapse-free survival (RFS) among non-pCR ESCC patients divided into pT0N0, primary site pCR (pT0N+), lymph node pCR (pT+N0), and non-pCR in both the tumor and lymph node (pT+N+) subgroups after NACRT and esophagectomy. Focusing on the SUV reduction rate in the primary tumor in 88 patients who underwent FDG-PET before and after NACRT, we used univariate and multivariate Cox proportional hazard models to identify prognostic factors.
Results: Although there were no significant survival differences among non-pCR ESCC patients with pT0N+, pT+N0, or pT+N+, survival rate among pT+N+patients was the poorest. After setting a 60% cutoff for the SUV reduction rate in the tumor, RFS curves for non-pCR patients significantly differed between patients above the cutoff and those below it. For pT+N+ patients, the SUV reduction rate (<60% vs ≥ 60%) was an independent prognostic factor of OS, DSS, and RFS.
Conclusion: Because ESCC patients with SUV reduction rates of <60% in the tumor after NACRT and categorized as pT+N+ after NACRT had significantly poorer prognoses, even after esophagectomy, a change in treatment strategy may be an option to improve survival.
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http://dx.doi.org/10.1186/s12957-021-02208-3 | DOI Listing |
Global Spine J
January 2025
Department of Spinal Surgery, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Study Design: Retrospective Cohort Study.
Objectives: The current recommended treatment for Giant Cell Tumour (GCT) of the spine is en bloc excision. Denosumab is a monoclonal antibody reducing osteoclast activity that shows promising results when used as a neo - adjuvant treatment.
Pharmaceutics
December 2024
Department of Urology and Department of Nuclear Medicine, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai 201399, China.
Background/objectives: The purpose of this study was to develop the gemcitabine-loaded drug-eluting beads (G-DEBs) for transarterial chemoembolization (TACE) in rabbit renal tumors and to evaluate their antitumor effect using 2-deoxy-2-[(18)F]fluoro-D-glucose positron emission tomography/X-ray computed tomography (F-FDG PET/CT).
Methods: DEBs were prepared by polyvinyl alcohol-based macromer crosslinked with -acryl tyrosine and ,'-methylenebis(acrylamide). Gemcitabine was loaded through ion change to obtain G-DEBs.
Asia Ocean J Nucl Med Biol
January 2025
Department of Nuclear Medicine, Saitama Medical University Hospital, Saitama, Japan.
Endocrine
December 2024
Nuclear Medicine and Molecular Imaging, Institut de Cancérologie Strasbourg Europe (ICANS), University Hospitals of Strasbourg, University of Strasbourg, Strasbourg, France.
Purpose: To evaluate organ-specific response to [Lu]DOTATATE Peptide Receptor Radionuclide Therapy (PRRT) in patients with small intestine neuroendocrine tumor (SiNET) through [Ga]DOTATOC PET/CT, and to analyze tumor uptake and functional volume variations at different metastatic sites in relation to disease progression during clinical follow-up after treatment.
Methods: A retrospective analysis was conducted on 33 metastatic patients. PET/CT were performed pre-treatment (PET0), mid-treatment after two PRRT cycles (PET2), and post-treatment (PET4).
Sensors (Basel)
November 2024
Department of Automotive Engineering, Gyeonggi University of Science and Technology, Siheung 15073, Republic of Korea.
In this study, we propose an enhanced LiDAR-based mapping and localization system that utilizes a camera-based YOLO (You Only Look Once) algorithm to detect and remove dynamic objects, such as vehicles, from the mapping process. GPS, while commonly used for localization, often fails in urban environments due to signal blockages. To address this limitation, our system integrates YOLOv4 with LiDAR, enabling the removal of dynamic objects to improve map accuracy and localization in high-traffic areas.
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