Correlation between tumor size and surveillance of lymph node metastasis for IB and IIA cervical cancer by magnetic resonance images

Kim, See Hyung; Lee, Hee Jung; Kim, Young Whan

doi:10.1016/j.ejrad.2011.04.053

Cited by 12 publications

(5 citation statements)

References 18 publications

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“…In our study, some clinical characteristics were independently correlated with LNM status, including MRI-reported LN status and FIGO stage. These clinical characteristics were quite similar to those from other previous studies based on conventional MRI analytical methods, indicating that the LNM status was closely related to the total status of the primary tumor [ 24 , 25 , 28 ]. Recently, some studies [ 29 , 30 , 31 ] developed combined models for predicting LNM status in cervical cancer patients based on clinical and histological information and MRI images.…”

Section: Discussionsupporting

confidence: 85%

“…Although MRI has the potential to identify LNM status according to the MRI morphological appearances of PLNM, such as size and shape, its efficiency and sensitivity in diagnosing PLNM are unsatisfactory [ 23 ]. Several previous studies have shown that a considerable proportion of cervical cancer patients were misclassified according to morphologic criteria on MRI images [ 24 , 25 ]. Although PET-CT shows favorable performance and is superior to MRI, considering the availability of PET-CT devices and high inspection costs, its wide application has a long way to go [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

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Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer

Xiang

et al. 2022

Diagnostics

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The accurate prediction of the status of PLNM preoperatively plays a key role in treatment strategy decisions in early-stage cervical cancer. The aim of this study was to develop and validate a radiomics-based nomogram for the preoperative prediction of pelvic lymph node metastatic status in early-stage cervical cancer. One hundred fifty patients were enrolled in this study. Radiomics features were extracted from T2-weighted MRI imaging (T2WI). Based on the selected features, a support vector machine (SVM) algorithm was used to build the radiomics signature. The radiomics-based nomogram was developed incorporating radiomics signature and clinical risk factors. In the training cohort (AUC = 0.925, accuracy = 81.6%, sensitivity = 70.3%, and specificity = 92.0%) and the testing cohort (AUC = 0.839, accuracy = 74.2%, sensitivity = 65.7%, and specificity = 82.8%), clinical models that combine stromal invasion depth, FIGO stage, and MTD perform poorly. The combined model had the highest AUC in the training cohort (AUC = 0.988, accuracy = 95.9%, sensitivity = 92.0%, and specificity = 100.0%) and the testing cohort (AUC = 0.922, accuracy = 87.1%, sensitivity = 85.7%, and specificity = 88.6%) when compared to the radiomics and clinical models. The study may provide valuable guidance for clinical physicians regarding the treatment strategies for early-stage cervical cancer patients.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer

Xiang

et al. 2022

Diagnostics

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“…Because of its high soft tissue resolution, MRI can delineate the contour of tumor clearly in a three-dimensional way 6,19. Measurement of tumor size using MRI has proven to be more accurate than pelvic examination 20,21.…”

Section: Discussionmentioning

confidence: 99%

<p>Impact of pelvic MRI in routine clinical practice on staging of IB1–IIA2 cervical cancer</p>

Zhang

Chen

Liu

et al. 2019

CMAR

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Purpose: To evaluate the impact of pelvic magnetic resonance imaging (MRI) on staging of IB1–IIA2 cervical cancer in routine clinical practice. Patients and Methods: A total of 1,016 patients with IB1-IIA2 cervical cancer who underwent primary surgery and preoperative pelvic MRI between January 2009 and December 2015 were identified in a retrospective multicentre study. Data on clinical stage, MRI reports and surgicopathologic findings were extracted from medical records. The impact of MRI on clinical staging was evaluated by comparison before and after combination of MRI. Using surgicopathologic findings as the reference standard, the impact of pelvic MRI on the accuracy of clinical staging was evaluated. Furthermore, the impact on the accuracy of individual staging parameters such as maximal tumor diameter, vaginal involvement or parametrial infiltration were also evaluated. Results: After combination of pelvic MRI, clinical stage remained unchanged in 59.7%, upstaged in 17.2%, and downstaged in 23.0% of the patients. The overall accuracy of clinical staging increased from 61.0% to 81.4% in our study ( P <0.05). As for individual staging parameters, the area under the curve (AUC) for maximal tumor diameter increased from 0.58 to 0.81 ( P <0.05). However, the AUC for vaginal involvement decreased from 0.61 to 0.57 ( P >0.05). The AUC for parametrial infiltration was also suboptimal (AUC=0.56, P <0.05). Conclusion: In routine clinical practice, MRI could increase the overall accuracy of clinical staging in IB1–IIA2 cervical cancer. For staging parameters, it only significantly increased the accuracy of maximal tumor diameter.

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“…However, these pathological factors cannot be used to define the prognosis prior to treatment or for patients who have not received surgery. In addition, many studies have reported that imaging modalities such as CT, MRI, and positron emission tomography are unsuitable to evaluate these factors in patients who have not received surgery [6,7,8,9]. …”

Section: Introductionmentioning

confidence: 99%

Pretreatment Factors Associated with Recurrence for Patients with Cervical Cancer International Federation of Gynecology and Obstetrics Stage IB1 Disease

Liu

Huang²,

Hu³

et al. 2015

Gynecol Obstet Invest

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Background: Pretreatment prognostic information is lacking for patients with cervical cancer International Federation of Gynecology and Obstetrics (FIGO) stage IB1 disease. Thus, we attempted to identify a high-risk subgroup among them prior to treatment. Methods: Cervical cancer FIGO stage IB1 patients who had received curative treatment with various modalities in our institute between January 2004 and December 2010 were enrolled. Pretreatment clinical parameters including age, squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen, hemoglobin (Hb) level, platelet count, histological type, and treatment modality were analyzed for treatment outcomes. Results: One hundred ninety-seven patients were included with a median follow-up of 66 months (range 6-119 months). In Cox regression analysis, only SCC histology (HR 0.457, 95% CI 0.241-0.967, p = 0.017) was an independent factor predicting better disease-free survival (DFS). Among SCC histology, patients with an Hb level less than 12 g/dl and a SCC-Ag level more than 3 ng/ml had worse treatment outcomes. The 5-year DFS rates were 89.2, 69.3, and 44.4% for the patients at low-risk (SCC, Hb >12 g/dl, SCC-Ag ≤3 ng/ml), intermediate-risk (non-SCC), and high-risk (SCC, Hb ≤12 g/dl, SCC-Ag >3 ng/ml), respectively (p < 0.001). Conclusion: Non-SCC and SCC histology with both anemia and high pretreatment SCC-Ag level were associated with recurrence. Further validation studies are warranted for clarification.

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Correlation between tumor size and surveillance of lymph node metastasis for IB and IIA cervical cancer by magnetic resonance images

Cited by 12 publications

References 18 publications

Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer

Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer

<p>Impact of pelvic MRI in routine clinical practice on staging of IB1–IIA2 cervical cancer</p>

Pretreatment Factors Associated with Recurrence for Patients with Cervical Cancer International Federation of Gynecology and Obstetrics Stage IB1 Disease

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Correlation between tumor size and surveillance of lymph node metastasis for IB and IIA cervical cancer by magnetic resonance images

Cited by 12 publications

References 18 publications

Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer

Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer

<p>Impact of pelvic MRI in routine clinical practice on staging of IB1&ndash;IIA2 cervical cancer</p>

Pretreatment Factors Associated with Recurrence for Patients with Cervical Cancer International Federation of Gynecology and Obstetrics Stage IB1 Disease

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<p>Impact of pelvic MRI in routine clinical practice on staging of IB1–IIA2 cervical cancer</p>