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Background And Purpose: Intravoxel-incoherent-motion (IVIM) magnetic-resonance-imaging (MRI) and positron-emission-tomography (PET) have been investigated independently but not voxel-wise to evaluate tumor microenvironment in cervical carcinoma patients. Whether regionally combined information of IVIM and PET offers additional predictive benefit over each modality independently has not been explored. Here, we investigated parametric-response-mapping (PRM) of co-registered PET and IVIM in cervical cancer patients to identify sub-volumes that may predict tumor shrinkage to concurrent-chemoradiation-therapy (CCRT).
Materials And Methods: Twenty cervical cancer patients (age: 63[41-85]) were retrospectively evaluated. Diffusion-weighted-images (DWIs) were acquired on 3.0 T MRIs using a free-breathing single-shot-spin echo-planar-imaging (EPI) sequence. Pre- and on-treatment (∼after four-weeks of CCRT) MRI and pre-treatment FDG-PET/CT were acquired. IVIM model-fitting on the DWIs was performed using a Bayesian-fitting simplified two-compartment model. Three-dimensional rigidly-registered maps of PET/CT standardized-uptake-value (SUV) and IVIM diffusion-coefficient () and perfusion-fraction () were generated. Population-means of PET-SUV, IVIM- and IVIM- from pre-treatment-scans were calculated and used to generate PRM via a voxel-wise joint-histogram-analysis to classify voxels as high/low metabolic-activity and with high/low (hi/lo) cellular-density. Similar PRM maps were generated for SUV and .
Results: Tumor-volume (p < 0.001) significantly decreased, while IVIM- (p = 0.002) and IVIM- (p = 0.03) significantly increased on-treatment. Pre-treatment tumor-volume (r = -0.45,p = 0.04) and PRM-SUV (r = -0.65,p = 0.002) negatively correlated with ΔGTV, while pre-treatment IVIM- (r = 0.64,p = 0.002), PRM-SUV (r = 0.52,p = 0.02), and PRM-SUV (r = 0.74,p < 0.001) positively correlated with ΔGTV.
Conclusion: IVIM and PET was performed on cervical cancer patients undergoing CCRT and we observed that both IVIM- and IVIM- increased during treatment. Additionally, PRM was applied, and sub-volumes were identified that were related to ΔGTV.
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http://dx.doi.org/10.1016/j.phro.2024.100630 | DOI Listing |
Int J Cancer
September 2025
Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Cervical cancer remains a significant public health issue, ranking as the fourth most common cancer in women globally. In the Netherlands, cervical cancer incidence declined steadily from 1989 to 2001 but increased between 2001 and 2007. This study updates trends in cervical cancer incidence from 1989 to 2023 in the Netherlands and evaluates the impact of screening practices and participation rates in the national population-based screening program.
View Article and Find Full Text PDFCochrane Database Syst Rev
September 2025
Institute for Evidence in Medicine, Medical Center - University of Freiburg / Medical Faculty - University of Freiburg, Freiburg, Germany.
Rationale: Cervical cancer is the fourth most common cancer affecting women worldwide, caused by persistent infection with oncogenic human papillomavirus (HPV) types. While HPV infections usually resolve spontaneously, persistent infections with high-risk HPV types can progress to premalignant glandular or - mostly - squamous intraepithelial lesions, usually classified in cervical intraepithelial neoplasia (CIN). Women with CIN 2 and CIN 3 (i.
View Article and Find Full Text PDFRep Pract Oncol Radiother
August 2025
University Teaching Department, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.
Cervical cancer continues to pose a significant global health challenge, highlighting the urgent need for accurate and efficient diagnostic techniques. Recent progress in deep learning has demonstrated considerable potential in improving the detection and classification of cervical cancer. This review presents a thorough analysis of deep learning methods utilized for cervical cancer diagnosis, with an emphasis on critical approaches, evaluation metrics, and the ongoing challenges faced in the field.
View Article and Find Full Text PDFRep Pract Oncol Radiother
August 2025
University Teaching Department, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.
Background: Cervical cancer (CC) is a leading cause of cancer-related deaths worldwide, emphasizing the need for accurate and efficient diagnostic tools. Traditional methods of cervical cell classification are time-consuming and susceptible to human error, highlighting the need for automated solutions.
Materials And Methods: This study introduces the modified hierarchical deep feature fusion (HDFF) method for cervical cell classification using the SIPaKMeD and Herlev datasets.
Front Oncol
August 2025
Hunan Cancer Hospital, The Affiliated Cancer Hospital, Xiangya School of Medicine, Central South University, Changsha, Hunan, China.
Tislelizumab, an anti-PD-1 monoclonal antibody, is associated with immune-related hepatitis in 1.8% of cases, but reports of acute liver failure (ALF) remain exceedingly rare. We present a case of fulminant hepatitis and ALF following Tislelizumab therapy in a 55-year-old woman with locally advanced cervical adenocarcinoma.
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