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Halle MK, Hodneland E, Wagner-Larsen KS, Lura NG, Fasmer KE, Berg HF, Stokowy T, Srivastava A, Forsse D, Hoivik EA, Woie K, Bertelsen BI, Krakstad C, Haldorsen IS. Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer. Sci Rep 2024; 14:11339. [PMID: 38760387 PMCID: PMC11101482 DOI: 10.1038/s41598-024-61271-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 05/03/2024] [Indexed: 05/19/2024] Open
Abstract
Cervical cancer (CC) is a major global health problem with 570,000 new cases and 266,000 deaths annually. Prognosis is poor for advanced stage disease, and few effective treatments exist. Preoperative diagnostic imaging is common in high-income countries and MRI measured tumor size routinely guides treatment allocation of cervical cancer patients. Recently, the role of MRI radiomics has been recognized. However, its potential to independently predict survival and treatment response requires further clarification. This retrospective cohort study demonstrates how non-invasive, preoperative, MRI radiomic profiling may improve prognostication and tailoring of treatments and follow-ups for cervical cancer patients. By unsupervised clustering based on 293 radiomic features from 132 patients, we identify three distinct clusters comprising patients with significantly different risk profiles, also when adjusting for FIGO stage and age. By linking their radiomic profiles to genomic alterations, we identify putative treatment targets for the different patient clusters (e.g., immunotherapy, CDK4/6 and YAP-TEAD inhibitors and p53 pathway targeting treatments).
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Affiliation(s)
- Mari Kyllesø Halle
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Erlend Hodneland
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Mathematics, University of Bergen, Bergen, Norway
| | - Kari S Wagner-Larsen
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Section of Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Njål G Lura
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Section of Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Kristine E Fasmer
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Section of Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Hege F Berg
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Tomasz Stokowy
- Genomics Core Facility, Department of Clinical Science, University of Bergen, Bergen, Norway
- Section of Bioinformatics, Clinical Laboratory, Haukeland University Hospital, Bergen, Norway
| | - Aashish Srivastava
- Genomics Core Facility, Department of Clinical Science, University of Bergen, Bergen, Norway
- Section of Bioinformatics, Clinical Laboratory, Haukeland University Hospital, Bergen, Norway
| | - David Forsse
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Erling A Hoivik
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Kathrine Woie
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Bjørn I Bertelsen
- Department of Pathology, Haukeland University Hospital, Bergen, Norway
| | - Camilla Krakstad
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway.
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.
| | - Ingfrid S Haldorsen
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway.
- Section of Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway.
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Fischerova D, Smet C, Scovazzi U, Sousa DN, Hundarova K, Haldorsen IS. Staging by imaging in gynecologic cancer and the role of ultrasound: an update of European joint consensus statements. Int J Gynecol Cancer 2024; 34:363-378. [PMID: 38438175 PMCID: PMC10958454 DOI: 10.1136/ijgc-2023-004609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 01/05/2024] [Indexed: 03/06/2024] Open
Abstract
In recent years the role of diagnostic imaging by pelvic ultrasound in the diagnosis and staging of gynecological cancers has been growing exponentially. Evidence from recent prospective multicenter studies has demonstrated high accuracy for pre-operative locoregional ultrasound staging in gynecological cancers. Therefore, in many leading gynecologic oncology units, ultrasound is implemented next to pelvic MRI as the first-line imaging modality for gynecological cancer. The work herein is a consensus statement on the role of pre-operative imaging by ultrasound and other imaging modalities in gynecological cancer, following European Society guidelines.
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Affiliation(s)
- Daniela Fischerova
- Gynecologic Oncology Center, Department of Gynecology, Obstetrics and Neonatology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Carolina Smet
- Department of Obstetrics and Gynecology, São Francisco de Xavier Hospital in Lisbon, Lisbon, Portugal
| | - Umberto Scovazzi
- Department of Gynecology and Obstetrics, Ospedale Policlinico San Martino and University of Genoa, Genoa, Italy
| | | | - Kristina Hundarova
- Department of Gynecology and Obstetrics A, Hospital and University Centre of Coimbra, Coimbra, Portugal
| | - Ingfrid Salvesen Haldorsen
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology and Department of Clinical Medicine, Haukeland University Hospital and the University of Bergen, Bergen, Norway
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Fischerova D, Frühauf F, Burgetova A, Haldorsen IS, Gatti E, Cibula D. The Role of Imaging in Cervical Cancer Staging: ESGO/ESTRO/ESP Guidelines (Update 2023). Cancers (Basel) 2024; 16:775. [PMID: 38398166 PMCID: PMC10886638 DOI: 10.3390/cancers16040775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 02/10/2024] [Accepted: 02/11/2024] [Indexed: 02/25/2024] Open
Abstract
Following the European Society of Gynaecological Oncology (ESGO), the European Society for Radiotherapy and Oncology (ESTRO), and the European Society of Pathology (ESP) joint guidelines (2018) for the management of patients with cervical cancer, treatment decisions should be guided by modern imaging techniques. After five years (2023), an update of the ESGO-ESTRO-ESP recommendations was performed, further confirming this statement. Transvaginal/transrectal ultrasound (TRS/TVS) or pelvic magnetic resonance (MRI) enables tumor delineation and precise assessment of its local extent, including the evaluation of the depth of infiltration in the bladder- or rectal wall. Additionally, both techniques have very high specificity to confirm the presence of metastatic pelvic lymph nodes but fail to exclude them due to insufficient sensitivity to detect small-volume metastases, as in any other currently available imaging modality. In early-stage disease (T1a to T2a1, except T1b3) with negative lymph nodes on TVS/TRS or MRI, surgicopathological staging should be performed. In all other situations, contrast-enhanced computed tomography (CECT) or 18F-fluorodeoxyglucose positron emission tomography combined with CT (PET-CT) is recommended to assess extrapelvic spread. This paper aims to review the evidence supporting the implementation of diagnostic imaging with a focus on ultrasound at primary diagnostic workup of cervical cancer.
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Affiliation(s)
- Daniela Fischerova
- Gynecologic Oncology Centre, Department of Gynaecology, Obstetrics and Neonatology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic; (F.F.); (D.C.)
| | - Filip Frühauf
- Gynecologic Oncology Centre, Department of Gynaecology, Obstetrics and Neonatology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic; (F.F.); (D.C.)
| | - Andrea Burgetova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic;
| | - Ingfrid S. Haldorsen
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, N-5021 Bergen, Norway;
- Section for Radiology, Department of Clinical Medicine, University of Bergen, 5020 Bergen, Norway
| | - Elena Gatti
- Department of Biomedical Science for Health, University of Milan, 20133 Milan, Italy;
| | - David Cibula
- Gynecologic Oncology Centre, Department of Gynaecology, Obstetrics and Neonatology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 121 08 Prague, Czech Republic; (F.F.); (D.C.)
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Halle MK, Bozickovic O, Forsse D, Wagner-Larsen KS, Gold RM, Lura NG, Woie K, Bertelsen BI, Haldorsen IS, Krakstad C. Clinicopathological and radiological stratification within FIGO 2018 stages improves risk-prediction in cervical cancer. Gynecol Oncol 2024; 181:110-117. [PMID: 38150835 DOI: 10.1016/j.ygyno.2023.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 12/13/2023] [Accepted: 12/16/2023] [Indexed: 12/29/2023]
Abstract
OBJECTIVE Assess the added prognostic value of the updated International Federation of Gynecology and Obstetrics (FIGO) 2018 staging system, and to identify clinicopathological and radiological biomarkers for improved FIGO 2018 prognostication. METHODS Patient data were retrieved from a prospectively collected patient cohort including all consenting patients with cervical cancer diagnosed and treated at Haukeland University Hospital during 2001-2022 (n = 948). All patients were staged according to the FIGO 2009 and FIGO 2018 guidelines based on available data for individual patients. MRI-assessed maximum tumor diameter and stromal tumor invasion, as well as histopathologically assessed lymphovascular space invasion were applied to categorize patients according to the Sedlis criteria. RESULTS FIGO 2018 stage yielded the highest area under the receiver operating characteristic (ROC) curve (AUC) (0.86 versus 0.81 for FIGO 2009) for predicting disease-specific survival. The most common stage migration in FIGO 2018 versus FIGO 2009 was upstaging from stages IB/II to stage IIIC due to suspicious lymph nodes identified by PET/CT and/or MRI. In FIGO 2018 stage III patients, extent and size of primary tumor (p = 0.04), as well as its histological type (p = 0.003) were highly prognostic. Sedlis criteria were prognostic within FIGO 2018 IB patients (p = 0.04). CONCLUSIONS Incorporation of cross-sectional imaging increases prognostic precision, as suggested by the FIGO 2018 guidelines. The 2018 FIGO IIIC stage could be refined by including the size and extent of primary tumor and histological type. The FIGO IB risk prediction could be improved by applying MRI-assessed tumor size and stromal invasion.
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Affiliation(s)
- Mari K Halle
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway; Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.
| | - Olivera Bozickovic
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway; Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - David Forsse
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway; Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Kari S Wagner-Larsen
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway; Section of Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Rose M Gold
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway; Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Njål G Lura
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway; Section of Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Kathrine Woie
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Bjørn I Bertelsen
- Department of Pathology, Haukeland University Hospital, 5021 Bergen, Norway
| | - Ingfrid S Haldorsen
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway; Section of Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Camilla Krakstad
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway; Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.
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Xie N, Lin J, Yu H, Liu L, Deng S, Liu L, Sun Y. A Diagnostic Nomogram Incorporating Prognostic Nutritional Index for Predicting Vaginal Invasion in Stage IB - IIA Cervical Cancer. Cancer Control 2024; 31:10732748241278479. [PMID: 39171582 PMCID: PMC11342438 DOI: 10.1177/10732748241278479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 08/07/2024] [Accepted: 08/12/2024] [Indexed: 08/23/2024] Open
Abstract
INTRODUCTION With the advancements in cancer prevention and diagnosis, the proportion of newly diagnosed early-stage cervical cancers has increased. Adjuvant therapies based on high-risk postoperative histopathological factors significantly increase the morbidity of treatment complications and seriously affect patients' quality of life. OBJECTIVES Our study aimed to establish a diagnostic nomogram for vaginal invasion (VI) among early-stage cervical cancer (CC) that can be used to reduce the occurrence of positive or close vaginal surgical margins. METHODS We assembled the medical data of early-stage CC patients between January 2013 and December 2021 from the Fujian Cancer Hospital. Data on demographics, laboratory tests, MRI features, physical examination (PE), and pathological outcomes were collected. Univariate and multivariate logistic regression analyses were employed to estimate the diagnostic variables for VI in the training set. Finally, the statistically significant factors were used to construct an integrated nomogram. RESULTS In this retrospective study, 540 CC patients were randomly divided into training and validation cohorts according to a 7:3 ratio. Multivariate logistic analyses showed that age [odds ratio (OR) = 2.41, 95% confidence interval (CI), 1.29-4.50, P = 0.006], prognostic nutritional index (OR = 0.18, 95% CI, 0.04-0.77, P = 0.021), histological type (OR = 0.28, 95% CI, 0.08-0.94, P = 0.039), and VI based on PE (OR = 3.12, 95% CI, 1.52-6.45, P = 0.002) were independent diagnostic factors of VI. The diagnostic nomogram had a robust ability to predict VI in the training [area under the receiver operating characteristic curve (AUC) = 0.76, 95% CI: 0.70-0.82] and validation (AUC = 0.70, 95% CI: 0.58-0.83) cohorts, and the calibration curves, decision curve analysis, and confusion matrix showed good prediction power. CONCLUSION Our diagnostic nomograms could help gynaecologists quantify individual preoperative VI risk, thereby optimizing treatment options, and minimizing the incidence of multimodality treatment-related complications and the economic burden.
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Affiliation(s)
- Ning Xie
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Jie Lin
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Haijuan Yu
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Li Liu
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Sufang Deng
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Linying Liu
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Yang Sun
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
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Wagner‐Larsen KS, Hodneland E, Fasmer KE, Lura N, Woie K, Bertelsen BI, Salvesen Ø, Halle MK, Smit N, Krakstad C, Haldorsen IS. MRI-based radiomic signatures for pretreatment prognostication in cervical cancer. Cancer Med 2023; 12:20251-20265. [PMID: 37840437 PMCID: PMC10652318 DOI: 10.1002/cam4.6526] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/16/2023] [Accepted: 08/31/2023] [Indexed: 10/17/2023] Open
Abstract
BACKGROUND Accurate pretherapeutic prognostication is important for tailoring treatment in cervical cancer (CC). PURPOSE To investigate whether pretreatment MRI-based radiomic signatures predict disease-specific survival (DSS) in CC. STUDY TYPE Retrospective. POPULATION CC patients (n = 133) allocated into training(T) (nT = 89)/validation(V) (nV = 44) cohorts. FIELD STRENGTH/SEQUENCE T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) at 1.5T or 3.0T. ASSESSMENT Radiomic features from segmented tumors were extracted from T2WI and DWI (high b-value DWI and apparent diffusion coefficient (ADC) maps). STATISTICAL TESTS Radiomic signatures for prediction of DSS from T2WI (T2rad ) and T2WI with DWI (T2 + DWIrad ) were constructed by least absolute shrinkage and selection operator (LASSO) Cox regression. Area under time-dependent receiver operating characteristics curves (AUC) were used to evaluate and compare the prognostic performance of the radiomic signatures, MRI-derived maximum tumor size ≤/> 4 cm (MAXsize ), and 2018 International Federation of Gynecology and Obstetrics (FIGO) stage (I-II/III-IV). Survival was analyzed using Cox model estimating hazard ratios (HR) and Kaplan-Meier method with log-rank tests. RESULTS The radiomic signatures T2rad and T2 + DWIrad yielded AUCT /AUCV of 0.80/0.62 and 0.81/0.75, respectively, for predicting 5-year DSS. Both signatures yielded better or equal prognostic performance to that of MAXsize (AUCT /AUCV : 0.69/0.65) and FIGO (AUCT /AUCV : 0.77/0.64) and were significant predictors of DSS after adjusting for FIGO (HRT /HRV for T2rad : 4.0/2.5 and T2 + DWIrad : 4.8/2.1). Adding T2rad and T2 + DWIrad to FIGO significantly improved DSS prediction compared to FIGO alone in cohort(T) (AUCT 0.86 and 0.88 vs. 0.77), and FIGO with T2 + DWIrad tended to the same in cohort(V) (AUCV 0.75 vs. 0.64, p = 0.07). High radiomic score for T2 + DWIrad was significantly associated with reduced DSS in both cohorts. DATA CONCLUSION Radiomic signatures from T2WI and T2WI with DWI may provide added value for pretreatment risk assessment and for guiding tailored treatment strategies in CC.
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Affiliation(s)
- Kari S. Wagner‐Larsen
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of RadiologyHaukeland University HospitalBergenNorway
- Section for Radiology, Department of Clinical MedicineUniversity of BergenBergenNorway
| | - Erlend Hodneland
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of RadiologyHaukeland University HospitalBergenNorway
- Department of MathematicsUniversity of BergenBergenNorway
| | - Kristine E. Fasmer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of RadiologyHaukeland University HospitalBergenNorway
- Section for Radiology, Department of Clinical MedicineUniversity of BergenBergenNorway
| | - Njål Lura
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of RadiologyHaukeland University HospitalBergenNorway
- Section for Radiology, Department of Clinical MedicineUniversity of BergenBergenNorway
| | - Kathrine Woie
- Department of Obstetrics and GynecologyHaukeland University HospitalBergenNorway
| | | | - Øyvind Salvesen
- Clinical Research Unit, Department of Clinical and Molecular MedicineNorwegian University of Science and TechnologyTrondheimNorway
| | - Mari K. Halle
- Department of Obstetrics and GynecologyHaukeland University HospitalBergenNorway
- Centre for Cancer Biomarkers (CCBIO), Department of Clinical ScienceUniversity of BergenBergenNorway
| | - Noeska Smit
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of RadiologyHaukeland University HospitalBergenNorway
- Department of InformaticsUniversity of BergenBergenNorway
| | - Camilla Krakstad
- Department of Obstetrics and GynecologyHaukeland University HospitalBergenNorway
- Centre for Cancer Biomarkers (CCBIO), Department of Clinical ScienceUniversity of BergenBergenNorway
| | - Ingfrid S. Haldorsen
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of RadiologyHaukeland University HospitalBergenNorway
- Section for Radiology, Department of Clinical MedicineUniversity of BergenBergenNorway
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Schleder S, May M, Scholz C, Dinkel J, Strotzer Q, Einspieler I, Dollinger M, Schreyer AG, Grassinger J, Schicho A. Diagnostic Value of Diffusion-Weighted Imaging with Background Body Signal Suppression (DWIBS) for the Pre-Therapeutic Loco-Regional Staging of Cervical Cancer: A Feasibility and Interobserver Reliability Study. Curr Oncol 2023; 30:1164-1173. [PMID: 36661738 PMCID: PMC9857406 DOI: 10.3390/curroncol30010089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/30/2022] [Accepted: 01/10/2023] [Indexed: 01/19/2023] Open
Abstract
(1) Background: cervical cancer is one of the leading causes of cancer-related deaths and the fourth most common cancer among women worldwide. Magnetic resonance imaging (MRI) is the modality of choice for loco-regional staging of cervical cancer in the primary diagnostic workup beginning with at least stage IB. (2) Methods: we retrospectively analyzed 16 patients with histopathological proven cervical cancer (FIGO IB1−IVA) for the diagnostic accuracy of standard MRI and standard MRI with diffusion-weighted imaging with background body signal suppression (DWIBS) for the correct pre-therapeutic assessment of the definite FIGO category. (3) Results: In 7 out of 32 readings (22%), DWIBS improved diagnostic accuracy. With DWIBS, four (13%) additional readings were assigned the correct major (I−IV) FIGO stages pre-therapeutically. Interobserver reliability of DWIBS was weakest for parametrial infiltration (k = 0.43; CI-95% 0.00−1.00) and perfect for tumor size <2 cm, infiltration of the vaginal lower third, infiltration of adjacent organs and loco-regional nodal metastases (k = 1.000; CI-95% 1.00−1.00). (4) Conclusions: the pre-therapeutic staging of cervical cancer has a high diagnostic accuracy and interobserver reliability when using standard MRI but can be further optimized with the addition of DWIBS sequences when reporting is performed by an experienced radiologist.
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Affiliation(s)
- Stephan Schleder
- Department of Diagnostic and Interventional Radiology, Merciful Brothers Hospital St. Elisabeth, 94315 Straubing, Germany
| | - Matthias May
- Department of Urology, Merciful Brothers Hospital St. Elisabeth, 94315 Straubing, Germany
| | - Carsten Scholz
- Department of Gynecology and Obstetrics, Merciful Brothers Hospital St. Elisabeth, 94315 Straubing, Germany
| | - Johannes Dinkel
- Department of Radiology, University Medical Center Regensburg, 93055 Regensburg, Germany
| | - Quirin Strotzer
- Department of Radiology, University Medical Center Regensburg, 93055 Regensburg, Germany
| | - Ingo Einspieler
- Department of Radiology, University Medical Center Regensburg, 93055 Regensburg, Germany
| | - Marco Dollinger
- Department of Radiology, University Medical Center Regensburg, 93055 Regensburg, Germany
| | - Andreas G. Schreyer
- Department of Diagnostic and Interventional Radiology, University Hospital Brandenburg, Brandenburg Medical School Theodor Fontane, 14770 Brandenburg, Germany
| | - Jochen Grassinger
- Department of Hematology and Oncology, Merciful Brothers Hospital St. Elisabeth, 94315 Straubing, Germany
| | - Andreas Schicho
- Department of Radiology, University Medical Center Regensburg, 93055 Regensburg, Germany
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