Prognostic significance of lymphovascular space invasion for stage IA1 and IA2 cervical cancer

Margolis, Benjamin; Cagle-Colon, Kayla; Chen, Ling; Tergas, Ana I.; Boyd, Leslie R.; Wright, Jason D.

doi:10.1136/ijgc-2019-000849

Cited by 22 publications

(17 citation statements)

References 17 publications

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“…Lymphovascular space invasion (LVSI) refers to the presence of cancer cell clusters in the vascular and/or lymphatic lumen (2). LVSI increases the risk of lymph node metastases (LNM), which is an independent high-risk factor for tumor recurrence and influences treatment methods (3)(4)(5). Studies have shown that LVSI is associated with decreased survival rates in women with stage IA2 (5), IB, and II CC [defined according to the Federation International of Gynecology and Obstetrics (FIGO)] (3,6).…”

Section: Introductionmentioning

confidence: 99%

“…LVSI increases the risk of lymph node metastases (LNM), which is an independent high-risk factor for tumor recurrence and influences treatment methods (3)(4)(5). Studies have shown that LVSI is associated with decreased survival rates in women with stage IA2 (5), IB, and II CC [defined according to the Federation International of Gynecology and Obstetrics (FIGO)] (3,6). Satellite LVSIs also significantly increase the risk of death and recurrence (7).…”

Section: Introductionmentioning

confidence: 99%

“…A definitive diagnosis can only be made through a histopathological examination of the surgical specimens. However, pathological analysis is not universally applicable, and there is wide interobserver variability in determining LVSI ( 5 ). A reformative, non-invasive, real-time, and cost-efficient preoperative test method for risk identification will have a considerable clinical impact on women with CC.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion

et al. 2022

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BackgroundDetection of lymphovascular space invasion (LVSI) in early cervical cancer (CC) is challenging. To date, no standard clinical markers or screening tests have been used to detect LVSI preoperatively. Therefore, non-invasive risk stratification tools are highly desirable.ObjectiveTo train and validate a multi-parametric magnetic resonance imaging (mpMRI)-based radiomics model to detect LVSI in patients with CC and investigate its potential as a complementary tool to enhance the efficiency of risk assessment strategies.Materials and MethodsThe model was developed from the tumor volume of interest (VOI) of 125 patients with CC. A total of 1037 radiomics features obtained from conventional magnetic resonance imaging (MRI), including a small field-of-view (sFOV) high-resolution (HR)-T2-weighted MRI (T2WI), apparent diffusion coefficient (ADC), T2WI, fat-suppressed (FS)-T2WI, as well as axial and sagittal contrast-enhanced T1-weighted MRI (T1c). We conducted a radiomics-based characterization of each tumor region using pretreatment image data. Feature selection was performed using the least absolute shrinkage and selection operator method on the training set. The predictive performance was compared with single variates (clinical data and single-layer radiomics signatures) analyzed using a receiver operating characteristic (ROC) curve. Three-fold cross-validation performed 20 times was used to evaluate the accuracy of the trained classifiers and the stability of the selected features. The models were validated by using a validation set.ResultsFeature selection extracted the six most important features (3 from sFOV HR-T2WI, 1 T2WI, 1 FS-T2WI, and 1 T1c) for model construction. The mpMRI-combined radiomics model (area under the curve [AUC]: 0.940) reached a significantly higher performance (better than the clinical parameters [AUC: 0.730]), including any single-layer model using sFOV HR-T2WI (AUC: 0.840), T2WI (AUC: 0.770), FS-T2WI (AUC: 0.710), ADC maps (AUC: 0.650), sagittal, and axial T1c values (AUC: 0.710, 0.680) in the validation set.ConclusionBiomarkers using multi-parametric radiomics features derived from preoperative MR images could predict LVSI in patients with CC.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion

et al. 2022

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“…The risk of recurrence after initial surgery is evaluated by pathological criteria such as lymph node metastasis, LVSI, depth of stromal invasion, parametrial invasion, tumor size, and positive surgical margins. 14,15 According to a recent report, 16 among patients with stage IA1 and IA2 disease, 10.5% and 18.8% had LVSI. Wenzel et al 12 reported that for tumors with an invasion depth of ≤5 mm and a horizontal spread of >7 mm, the incidence of LVSI and lymph node metastasis was 26.9% and 3.5%, respectively.…”

Section: Discussionmentioning

confidence: 99%

Validation of the FIGO 2018 staging system of cervical cancer: Retrospective analysis of FIGO 2009 stage IB1 cervical cancer with tumor under 2 cm

Takahashi

Sakai

Iwasa

et al. 2021

J of Obstet and Gynaecol

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Aim The International Federation of Gynecology and Obstetrics (FIGO) revised the cervical cancer staging system in 2018. This study aims to validate the revised staging system in patients with tumors <2 cm in size who were classified as FIGO 2009 stage IB1. Methods We evaluated 62 women with stage IB1 cervical cancer (FIGO 2009) who underwent radical hysterectomy as the initial treatment between November 2004 and August 2018 in our institution. The patients with FIGO 2009 stage IB1 and tumors <2 cm in size were enrolled. We reclassified their stage according to the FIGO 2018 staging system and analyzed their clinicopathological data retrospectively. Results Twenty‐five patients met the inclusion criteria. According to the FIGO 2018 classification, 9 (36.0%) patients were classified as stage IA, 13 (52.0%) as stage IB1, and 3 (12.0%) as stage IIIC, respectively. One (11.1%), six (46.2%), and three (100%) patients with lymphovascular space invasion were classified as stage IA, IB1, and IIIC, respectively. No significant differences were found in the 5‐year overall survival or progression‐free survival among the three stages. Conclusions As many as 36.0% of patients classified as FIGO 2009 stage IB1 with a tumor <2 cm in size were classified as stage IA in the FIGO 2018 classification. For these cases, a treatment less invasive than radical hysterectomy or radiotherapy might be sufficient. Our results suggest that cervical cancer patients with tumors <2 cm should be carefully diagnosed by performing cervical conization and assessed the pathological findings before hysterectomy.

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“…In addition, it guides postoperative treatment planning in early cervical cancer. [ 2 ] Pelvic lymphadenectomy procedure as well as radical hysterectomy procedure is routinely used as the treatment in order to avoid the under diagnosis of lymph node metastasis. From the past to the present, removal of pelvic lymph nodes has shown poor clinical effects, including nerve damage, lymphedema and lymphocyst formation, contributing to increased operative time, blood loss.…”

Section: Introductionmentioning

confidence: 99%

Sentinel lymph node mapping in early-stage cervical cancer

Wang

Liu

et al. 2021

Medicine

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Background: The value of sentinel lymph node (SLN) mapping for early-stage cervical cancer remains controversial. Therefore, we collected data to investigate the feasibility and diagnostic accuracy of SLN in patients with early-stage (IA-IIA) cervical cancer. Methods: We searched Embase, PubMed, and the Cochrane Library databases issued before June 1, 2020. The sample size of the selected study was at least 10 patients with early-stage (IA-IIA) cervical cancer, the pooled detection rates and the separate detection rate (overall detection rate, bilateral detection rate) using blue dye with Tc, technetium 99 (Tc) and indocyanine green (ICG) technique of early-stage cervical cancer was reported. R-3.6.1 software was used to evaluate pooled detection rate and sensitivity. Results: Two thousand one hundred sixty-four patients included for analysis in 28 studies ranging from 12 to 405 patients. The combined overall detection rate of SLN mapping was 95% with a 72% pooled bilateral detection rate. The sensitivity of the combined overall detection rate of SLN mapping was 94.99% as well as a sensitivity of 72.43% bilateral detection rate. The overall detection rate of SLN was 96% for blue dye with Tc, 95% for Tc, 98% for ICG technique. The bilateral detection rate of SLN was 76% for blue dye with Tc, 63% for Tc, 85% for ICG technique. The sensitivity of the overall detection rate of SLN mapping was 97.76% as well as a sensitivity of 84.96% bilateral detection rate of ICG technique. Conclusion: In early-stage cervical cancer, overall detection rate of SLN mapping is elevated while bilateral detection rate is lower. The overall detection rate (98%) as well as bilateral rate (85%) of ICG seems to be a better SLN mapping technique among the method of SLN mapping (using blue dye with Tc, Tc or ICG). We believe SLN mapping may be considered contemporary technique which could provide additional benefits over traditional pelvic lymphadenectomy. While promising results in SLN mapping has been found, larger patient samples, including randomized studies, are required at the same time.

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Prognostic significance of lymphovascular space invasion for stage IA1 and IA2 cervical cancer

Cited by 22 publications

References 17 publications

Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion

Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion

Validation of the FIGO 2018 staging system of cervical cancer: Retrospective analysis of FIGO 2009 stage IB1 cervical cancer with tumor under 2 cm

Sentinel lymph node mapping in early-stage cervical cancer

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