The added role of MR imaging in treatment stratification of patients with gynecologic malignancies: what the radiologist needs to know

Magnetic resonance imaging evaluation of gynecological mass lesions: A comprehensive analysis with histopathological correlation

Evaluating gynecological mass lesions and reviewing their morphological characteristics based on their imaging appearance on magnetic resonance imaging (MRI), and correlating the MRI findings with histopathological findings, was the central theme of our study. This observational cross-sectional study was conducted on 60 female patients with clinically suspected gynecological mass lesions upon physical examination and/or ultrasonography, referred for MRI at a tertiary care hospital over a 1-year period between June 2022 and July 2023. A broad spectrum of differential diagnoses of gynecological masses was observed. In our study, the ratio of benign versus malignant disease was 1.6:1, with 37 benign and 23 malignant masses identified. The most common benign masses were uterine fibroids (n = 14; 23.3%), followed by endometriosis (n = 8; 13.3%), and ovarian dermoid cysts (n = 4; 6.6%). Among the malignant lesions, cervical cancer was the most common (n = 11; 18.3%), followed by endometrial carcinoma (n = 7; 11.6%), ovarian carcinoma (n = 3; 5%), and vaginal carcinoma (n = 2; 3%). Benign lesions mostly appeared hypo- to isointense on T1-weighted imaging and iso- to hyperintense on T2-weighted imaging, while malignant lesions appeared isointense on T1-weighted and hyperintense on T2-weighted imaging. Hemorrhage and fat were well appreciated on MRI and aided in diagnosis. T2 shading was present in 7 out of 8 endometriotic cysts, demonstrating a specificity of 100% and a sensitivity of 83%. For determining parametrial invasion in cervical carcinoma, MRI showed an accuracy of 91%, specificity of 100%, and positive predictive value, negative predictive value, and sensitivity of 100%, 75%, and 88%, respectively. In cases of endometrial carcinoma, MRI demonstrated a sensitivity and specificity of 87% and 91%, respectively, with a positive predictive value of 87% and a negative predictive value of 91% for identifying myometrial invasion greater than 50%. Compared to other modalities, MRI provided substantial information regarding uterine and adnexal masses and surrounding structures, facilitating accurate staging of lesions.

3D MR elastography-based stiffness as a marker for predicting tumor grade and subtype in cervical cancer

BACKGROUND

Increasing evidence has indicated that high tissue stiffness (TS) may be a potential biomarker for evaluation of tumor aggressiveness.

PURPOSE

To investigate the value of magnetic resonance elastography (MRE)-based quantitative parameters preoperatively predicting the tumor grade and subtype of cervical cancer (CC).

STUDY TYPE

Retrospective.

POPULATION

Twenty-five histopathology-proven CC patients and 7 healthy participants.

FIELD STRENGTH/SEQUENCE

3.0T, magnetic resonance imaging (MRI) (LAVA-flex) and MRE with a three-dimensional spin-echo echo-planar imaging.

ASSESSMENT

The regions of interest (ROIs) were manually drawn by two observers in tumors to measure mean TS, storage modulus (G'), loss modulus (G″) and damping ratio (DR) values. Surgical specimens were evaluated for tumor grades and subtypes.

STATISTICAL TESTS

Intraclass correlation coefficient (ICC) was expressed in terms of inter-observer agreements. t-test or Mann-Whitney nonparametric test was used to compare the complex modulus and apparent diffusion coefficient (ADC) values between different tumor groups. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the diagnostic performance.

RESULTS

The TS of endocervical adenocarcinoma (ECA) group was significantly higher than that in squamous cell carcinoma (SCC) group (5.27 kPa vs. 3.44 kPa, P = 0.042). The TS also showed significant difference between poorly and well/moderately differentiated CC (5.21 kPa vs. 3.47 kPa, P = 0.038), CC patients and healthy participants (4.18 kPa vs. 1.99 kPa, P < 0.001). The cutoff value of TS to discriminate ECA from SCC was 4.10 kPa (AUC: 0.80), while it was 4.42 kPa to discriminate poorly from well/moderately differentiated CC (AUC: 0.83), and 2.25 kPa to distinguish normal cervix from CC (AUC: 0.88), respectively. There were no significant difference in G″, DR and ADC values between any subgroups except for comparison of healthy participants and CC patients (P = 0.001, P = 0.004, P < 0.001, respectively).

DATA CONCLUSION

3D MRE-assessed TS shows promise as a potential biomarker to preoperatively assess tumor grade and subtype of CC.

Enhancing Preoperative Assessment of Endometrial Cancer: The Role of Diffusion-Weighted Magnetic Resonance Imaging in Evaluating Myometrial Invasion

BACKGROUND

Endometrial cancer (EC) is the most common gynecological malignancy. Accurate preoperative staging is essential for guiding treatment. The depth of myometrial invasion is a key prognostic factor. This prospective study aimed to evaluate the added benefit of diffusion-weighted imaging (DWI) compared to T2-weighted imaging (T2WI) and dynamic contrast-enhanced MRI (DCE-MRI) for the preoperative assessment of myometrial invasion in EC.

AIM AND OBJECTIVES

The aim of this prospective study was to evaluate the added benefit of DWI in the preoperative assessment of myometrial invasion in EC, in comparison with T2WI and DCE-MRI. The objectives were to assess the imaging characteristics of endometrial carcinoma on T2WI, DCE, and DW MR, to assess the depth of myometrial invasion and overall stage in EC patients, to compare the diagnostic performance of DCE-MRI with that of DW-MRI combined with T2WI, to describe how MR imaging findings can be combined with tumor histologic features and grading to guide treatment planning, and to evaluate the pitfalls and limitations of DCE and DW MR in the assessment of EC.

MATERIALS AND METHODS

Thirty-one patients with histologically confirmed EC underwent preoperative pelvic MRI on a 1.5T scanner. T2WI, DWI (b-values 0, 1000 s/mm2), and DCE-MRI were performed. Two radiologists independently assessed myometrial invasion on T2WI, T2WI + DWI, and T2WI + DCE-MRI. Histopathology after hysterectomy was the reference standard. Diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each MRI protocol, with separate analyses for superficial (<50%) and deep (≥50%) myometrial invasions.

RESULTS

The accuracy for assessing superficial invasion was 61.3% for T2WI, 87.1% for T2WI + DWI, and 87.1% for T2WI + DCE-MRI. For deep invasion, accuracy was 64.5% for T2WI, 90.3% for T2WI + DWI, and 90.3% for T2WI + DCE-MRI. Sensitivity, specificity, PPV, and NPV for T2WI + DWI and T2WI + DCE-MRI were high and comparable (88.9-91.7%) for both superficial and deep invasions. T2WI had markedly lower sensitivity and specificity. The differences between T2WI and the functional MRI protocols were statistically significant (p < 0.01).

CONCLUSION

DWI and DCE-MRI significantly improve the diagnostic performance of MRI for the preoperative assessment of myometrial invasion depth in EC compared to T2WI alone. DWI + T2WI and DCE-MRI + T2WI demonstrate comparable high accuracy. DWI may be preferable since it is faster and avoids contrast administration.

The value of MRI in quantification of parametrial invasion and association with prognosis in locally advanced cervical cancer: the "PLACE" study

OBJECTIVE

This retrospective observational study aims to evaluate the association between the extent of parametrial invasion (PMI) and disease-free survival (DFS) and cancer-specific survival (CSS) in patients with locally advanced cervical cancer (LACC).

MATERIALS AND METHODS

This study included patients with LACC showing parametrial invasion at Magnetic Resonance Imaging (MRI). They were treated with neoadjuvant chemo-radiotherapy (CT/RT) before undergoing radical hysterectomy. The staging MRIs were reviewed retrospectively. Measurements of maximum PMI (PMImax) and parametrial length were taken bilaterally. After that, PMIratio was calculated by dividing PMImax by parametrial length. Analysis was conducted on homogeneous subsets of patients, grouped based on their pathological lymph nodal evaluation (N- and N+). Correlations between PMImax and PMIratio with DFS and CSS were evaluated in both the N- and N+ groups, employing univariable Cox regression analysis.

RESULTS

Out of 221 patients, 126 (57%) had non-metastatic lymph nodes (N-), while 95 (43%) had metastatic lymph nodes (N+). The median observation period for all these patients was 73 months (95% confidence interval [CI]: 66-77). The 5-year DFS and CSS probability rates were 75% and 85.7%, respectively, for the N- group and 54.3% and 73.6%, respectively, for the N+ group. A higher PMImax (hazard ratio [HR] = 1.09) and PMIratio (HR = 1.04) correlated with worse overall survival in patients in the N- group (p = 0.025 and p = 0.042). These parameters did not show a significant statistical association in the N+ group.

CONCLUSIONS

The degree of PMI evaluated on MRI affects outcome in N- patients with LACC.

CLINICAL RELEVANCE STATEMENT

The degree of MRI parametrial invasion affects disease-free survival and cancer-specific survival in patients with the International Federation of Gynecology and Obstetrics (FIGO) stage IIB cervical cancer. This MRI finding can be easily incorporated into routine clinical practice.

KEY POINTS

• Visual assessment of parametrial invasion on MRI was not significantly associated with prognosis in locally advanced cervical cancer (LACC). • A greater degree of parametrial invasion is associated with poorer disease-free survival and cancer-specific survival in patients with LACC without metastatic lymph node involvement. • The degree of parametrial invasion at MRI has no correlation with prognosis in LACC with metastatic lymph nodes.

Multiparametric MRI-based radiomics nomogram for identifying cervix-corpus junction cervical adenocarcinoma from endometrioid adenocarcinoma

OBJECTIVE

To developed a magnetic resonance imaging (MRI) radiomics nomogram to identify adenocarcinoma at the cervix-corpus junction originating from the endometrium or cervix in order to better guide clinical treatment.

METHODS

Between February 2011 and September 2021, the clinicopathological data and MRI in 143 patients with histopathologically confirmed cervical adenocarcinoma (CAC, n = 86) and endometrioid adenocarcinoma (EAC, n = 57) were retrospectively analyzed at the cervix-corpus junction. Radiomics features were extracted from fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) maps, and delayed phase contrast-enhanced T1-weighted imaging (CE-T1WI) sequences. A radiomics nomogram was developed integrating radscore with independent clinical risk factors. The area under the curve (AUC) was used to evaluate the diagnostic efficacy of the radscore, nomogram and two different experienced radiologists in differentiating CAC from EAC at the cervix-corpus junction, and Delong test was applied to compare the differences of their diagnostic performance.

RESULTS

In the training cohort, the AUC was 0.93 for radscore; 0.97 for radiomics nomograms; 0.85 and 0.86 for radiologists 1 and 2, respectively. Delong test showed that the differential efficacy of nomogram was significant better than those of radiologists in the training cohort (both P < 0.05).

CONCLUSIONS

The nomogram based on radscore and clinical risk factors could better differentiate CAC from EAC at the cervix-corpus junction than radiologists, and preoperatively and non-invasively identify the origin of adenocarcinoma at the cervix-corpus junction, which facilitates clinicians to make individualized treatment decision.

Application of PET/MRI in Gynecologic Malignancies

The diagnosis, treatment, and management of gynecologic malignancies benefit from both positron emission tomography/computed tomography (PET/CT) and MRI. PET/CT provides important information on the local extent of disease as well as diffuse metastatic involvement. MRI offers soft tissue delineation and loco-regional disease involvement. The combination of these two technologies is key in diagnosis, treatment planning, and evaluating treatment response in gynecological malignancies. This review aims to assess the performance of PET/MRI in gynecologic cancer patients and outlines the technical challenges and clinical advantages of PET/MR systems when specifically applied to gynecologic malignancies.

Clinical and multiparametric MRI features for differentiating uterine carcinosarcoma from endometrioid adenocarcinoma

INTRODUCTION

The purpose of our study was to differentiate uterine carcinosarcoma (UCS) from endometrioid adenocarcinoma (EAC) by the multiparametric magnetic resonance imaging (MRI) features.

METHODS

We retrospectively evaluated clinical and MRI findings in 17 patients with UCS and 34 patients with EAC proven by histologically. The following clinical and pathological features were evaluated: post- or pre-menopausal, clinical presentation, invasion depth, FIGO stage, lymphaticmetastasis. The following MRI features were evaluated: tumor dimension, cystic degeneration or necrosis, hemorrhage, signal intensity (SI) on T2-weighted images (T2WI), relative SI of lesion to myometrium on T2WI, T1WI, DWI, ADCmax, ADCmin, ADCmean (RSI-T2, RSI-T1, RSI-DWI, RSI-ADCmax, RSI-ADCmin, RSI-ADCmean), ADCmax, ADCmin, ADCmean, the maximum, minimum and mean relative enhancement (RE) of lesion to myometrium on the arterial and venous phases (REAmax, REAmin, REAmean, REVmax, REVmin, REVmean). Receiver operating characteristic (ROC) analysis and the area under the curve (AUC) were used to evaluate prediction ability.

RESULTS

The mean age of UCS was higher than EAC. UCS occurred more often in the postmenopausal patients. UCS and EAC did not significantly differ in depth of myometrial invasion, FIGO stage and lymphatic metastasis. The anterior-posterior and transverse dimensions were significantly larger in UCS than EAC. Cystic degeneration or necrosis and hemorrhage were more likely occurred in UCS. The SI of tumor on T2WI was more heterogeneous in UCS. The RSI-T2, ADCmax, ADCmean, RSI-ADCmax and RSI-ADCmean of UCS were significantly higher than EAC. The REAmax, REAmin, REAmean, REVmax, REVmin and REVmean of UCS were all higher than EAC. The AUCs were 0.72, 0.71, 0.86, 0.96, 0.89, 0.84, 0.73, 0.97, 0.88, 0.94, 0.91, 0.69 and 0.80 for the anterior-posterior dimension, transverse dimension, RSI-T2, ADCmax, ADCmean, RSI-ADCmax, RSI-ADCmean, REAmax, REAmin, REAmean, REVmax, REVmin and REVmean, respectively. The AUC was 0.997 of the combined of ADCmax, REAmax and REVmax. Our study showed that ADCmax threshold value of 789.05 (10-3mm2/s) can differentiate UCS from EAC with 100% sensitivity, 76.5% specificity, and 0.76 AUC, REAmax threshold value of 0.45 can differentiate UCS from EAC with 88.2% sensitivity, 100% specificity, and 0.88 AUC.

CONCLUSION

Multiparametric MRI features may be utilized as a biomarker to distinguish UCS from EAC.

Intratumoral and peritumoral MRI radiomics nomogram for predicting parametrial invasion in patients with early-stage cervical adenocarcinoma and adenosquamous carcinoma

OBJECTIVE

To develop a comprehensive nomogram based on MRI intra- and peritumoral radiomics signatures and independent risk factors for predicting parametrial invasion (PMI) in patients with early-stage cervical adenocarcinoma (AC) and adenosquamous carcinoma (ASC).

METHODS

A total of 460 patients with IB to IIB cervical AC and ASC who underwent preoperative MRI examination and radical trachelectomy/hysterectomy were retrospectively enrolled and divided into primary, internal validation, and external validation cohorts. The original (Ori) and wavelet (Wav)-transform features were extracted from the volumetric region of interest of the tumour (ROI-T) and 3mm- and 5mm-peritumoral rings (ROI-3 and ROI-5), respectively. Then the Ori and Ori-Wav feature-based radiomics signatures from the tumour (RST) and 3 mm- and 5 mm-peritumoral regions (RS3 and RS5) were independently built and their diagnostic performances were compared to select the optimal ones. Finally, the nomogram was developed by integrating optimal intra- and peritumoral signatures and clinical independent risk factors based on multivariable logistic regression analysis.

RESULTS

FIGO stage, disruption of the cervical stromal ring on MRI (DCSRMR), parametrial invasion on MRI (PMIMR), and serum CA-125 were identified as independent risk factors. The nomogram constructed by integrating independent risk factors, Ori-Wav feature-based RST, and RS5 yielded AUCs of 0.874 (0.810-0.922), 0.885 (0.834-0.924), and 0.966 (0.887-0.995) for predicting PMI in the primary, internal and external validation cohorts, respectively. Furthermore, the nomogram was superior to radiomics signatures and clinical model for predicting PMI in three cohorts.

CONCLUSION

The nomogram can preoperatively, accurately, and noninvasively predict PMI in patients with early-stage cervical AC and ASC.

CLINICAL RELEVANCE STATEMENT

The nomogram can preoperatively, accurately, and noninvasively predict PMI and facilitate precise treatment decisions regarding chemoradiotherapy or radical hysterectomy in patients with early-stage cervical AC and ASC.

KEY POINTS

The accurate preoperative prediction of PMI in early-stage cervical AC and ASC can facilitate precise treatment decisions regarding chemoradiotherapy or radical hysterectomy. The nomogram integrating independent risk factors, Ori-Wav feature-based RST, and RS5 can preoperatively, accurately, and noninvasively predict PMI in early-stage cervical AC and ASC. The nomogram was superior to radiomics signatures and clinical model for predicting PMI in early-stage cervical AC and ASC.

Preoperative Imaging Evaluation of Endometrial Cancer in FIGO 2023

The staging of endometrial cancer is based on the International Federation of Gynecology and Obstetrics (FIGO) staging system according to the examination of surgical specimens, and has revised in 2023, 14 years after its last revision in 2009. Molecular and histological classification has incorporated to new FIGO system reflecting the biological behavior and prognosis of endometrial cancer. Nonetheless, the basic role of imaging modalities including ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography, as a preoperative assessment of the tumor extension and also the evaluation points in CT and MRI imaging are not changed, other than several point of local tumor extension. In the field of radiology, it has also undergone remarkable advancement through the rapid progress of computational technology. The application of deep learning reconstruction techniques contributes the benefits of shorter acquisition time or higher quality. Radiomics, which extract various quantitative features from the images, is also expected to have the potential for the quantitative prediction of risk factors such as histological types and lymphovascular space invasion, which is newly included in the new FIGO system. This article reviews the preoperative imaging diagnosis in new FIGO system and recent advances in imaging analysis and their clinical contributions in endometrial cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 3.

Role of tumor volume in endometrial cancer: An imaging analysis and prognosis significance

OBJECTIVE

To evaluate the prognostic value of tumor volume on preoperative MRI in endometrial cancer (EC) patients and its association with adverse prognostic factors and survival.

METHODS

A retrospective observational study with 127 consecutive patients with endometrioid EC was carried out between 2016 and 2021 at Juan Ramón Jiménez University Hospital, Huelva (Spain). All patients underwent preoperative magnetic resonance imaging (MRI) for local staging. The tumor volume was analyzed on MRI by two different methods: by measuring the three maximum diameters of the tumor according to an ellipse formula and by manual region of interest in different sections; the ratio between tumor volume and uterus volume was also calculated as a third tool. The relationships between volume, prognostic factors, and survival were analyzed.

RESULTS

A total of 127 patients with endometroid EC underwent preoperative MRI and were included in the study. Tumor volume was significantly higher for deep myometrial invasion, cervical stromal involvement, infiltrated serosa, lymph node metastases, high-grade EC, and lymphovascular space involvement, advanced FIGO stage, and High Recurrence Risk Group (P < 0.001). ROC curves showed that tumor volume greater than 25 cm3 predicts lymph node metastases. Volume index greater than 17 cm3 was associated with reduced disease-free survival (P < 0.001) and overall survival (P < 0.003). Multivariate analysis showed that the greatest tumor volume had an independent impact on recurrence (odds ratio [OR]1.019, 95% confidence interval [CI] 1.005-1.032) and survival (OR 1.027, 95% CI 1.009-1.046).

CONCLUSIONS

This study shows an important correlation between tumor volume on MRI and poor prognostic factors. Preoperative tumor volume on MRI is a valuable biomarker to be considered for management of EC.

US, MRI, CT Performance and Interpretation of Uterine Masses

Uterine masses are commonly encountered as incidental findings during cross-sectional imaging or when individuals present with symptoms such as pain and bleeding. The World Health Organization categorizes tumors of the uterine corpus into 5 distinct groups: endometrial epithelial tumors and their precursors, tumor-like growths, mesenchymal uterine tumors, tumors with a combination of epithelial and mesenchymal elements, and various other types of tumors. The primary imaging method for assessing uterine abnormalities is transvaginal ultrasound. However, magnetic resonance imaging (MRI) can be employed to enhance the visualization of soft tissues, enabling a more detailed characterization of uterine masses. This article aims to outline the imaging features of both benign and malignant uterine masses using ultrasound, MRI, and computed tomography.

The value of multiparametric MRI combined with clinical prognostic parameters in predicting the 5-year survival of stage IIIC1 cervical squamous cell carcinoma

OBJECTIVES

To explore the value of multiparametric magnetic resonance imaging（MRI）in predicting the 5-year progression-free survival (PFS) and overall survival (OS) of cervical squamous cell carcinoma (CSCC) in 2018 FIGO stage IIIC1.

METHODS

This retrospective study collected156 patients with CSCC from Dec. 2014 to Jul. 2018. Sixty-one patients underwent radical hysterectomy (RH), and 95 patients underwent concurrent chemoradiotherapy (CCRT). Clinical and MR parameters of primary tumours were analysed. A 1:1 ratio propensity score matching (PSM) was performed for the RH group and CCRT group according to T stage. The Cox proportional hazard model was used to evaluate the associations between imaging or clinical variables and PFS and OS.

RESULTS

The 5-year PFS and OS rates were 72.6% and 78.3%, respectively. The analysis results show that the treatment method, ADCmin < 0.604 × 10-3 mm2/s, and Ktrans < 0.699 min-1 correlated with worse PFS, while SCC-Ag > 6.7 ng/L, ADCmin < 0.604 × 10-3 mm2/s, and Ktrans < 0.699 min-1 correlated with worse OS. After PSM, we confirmed that the treatment methods did not affect the long-term survival of patients with stage IIIC1 disease, and a low Ktrans value was an independent poor prognostic factor.

CONCLUSION

Functional MRI parameters and SCC-Ag have potential predictive value for the 5-year survival of 2018 FIGOIIIC1 CSCC. There were no significant differences in survival between CCRT and RH + adjuvant therapy for IIIC1 stage CSCC if the T stage was earlier.

Contrast-Enhanced MRI in Women with Endometrial Cancer: Dynamic Versus Single-Phase Acquisitions

Background

The 2019 European Society of Urogenital Radiology (ESUR) guidelines for endometrial cancer recommend performing either dynamic contrast-enhanced magnetic resonance imaging (CE MRI) or single-phase CE MRI. However, no study has directly compared these options. Therefore, this study compared dynamic versus single-phase CE MRI for the evaluation of myometrial invasion in women with endometrial cancer.

Methods

This retrospective, single-institution comparative study was conducted among women with surgically proven endometrial cancer, including 30 consecutive women with single-phase CE MRI and 30 age- and pathologic stage-matched women with dynamic CE MRI. Three readers independently compared dynamic and single-phase CE MRI in terms of the tumor-myometrium signal intensity (SI) difference ratio, depth of myometrial invasion, image quality, and image number. Pathologic findings served as a reference standard for the depth of myometrial invasion.

Results

The estimated mean SI difference ratios of dynamic CE MRI and single-phase CE MRI fell within an equivalence margin of 0.05 (90% confidence intervals [CIs] = [-0.0497 to -0.0165], [-0.0226 to -0.0403], and [-0.0429 to -0.0433], respectively, for readers A, B, and C). The area under the receiver operating characteristic curve for the detection of deep myometrial invasion was not significantly different between the acquisitions (P = .3315, P = .3345, and P = .8593, respectively). Single-phase CE MRI showed significantly better image quality than dynamic CE MRI (P = .0143, P = .0042, and P = .0066, respectively), while the median number of images for dynamic CE MRI was 2.4 times higher than that for single-phase CE MRI.

Conclusion

Single-phase acquisition may be a better option for CE MRI in women with endometrial cancer than dynamic acquisition.

Patient survival prediction in locally advanced cervical squamous cell carcinoma using MRI-based radiomics: retrospective cohort study

Cervical cancer is a major health concern for women, ranking as the fourth most common cancer and a significant cause of cancer-related deaths worldwide. To enhance prognostic predictions for locally advanced cervical squamous cell carcinoma, we conducted a study utilizing radiomics features extracted from pretreatment magnetic resonance images. The goal was to predict patient survival and compare the predictive value of these features with clinical traits and the 2018 International Federation of Obstetrics and Gynecology (FIGO) staging system. In our retrospective cohort study, we included 500 patients with confirmed cervical squamous cell carcinoma ranging from FIGO stages IIB to IVA under the 2018 staging system. All patients underwent pelvic MRI with diffusion-weighted imaging before receiving definitive curative concurrent chemoradiotherapy. The results showed that the combination model, incorporating radiomics scores and clinical traits, demonstrated superior predictive accuracy compared to the widely used 2018 FIGO staging system for both progression-free and overall survival. Age was identified as a significant factor influencing survival outcomes. Additionally, primary tumour invasion stage, tumour maximal diameter, and the location of lymph node metastasis were found to be important predictors of progression-free survival, while primary tumour invasion stage and lymph node metastasis position individually affected overall survival. During the follow-up period, a portion of patients experienced disease-related deaths or tumour progression/recurrence in both sets. The radiomics-score significantly enhanced prediction ability, providing valuable insights for guiding personalized therapy approaches and stratifying patients into low-risk and high-risk categories for progression-free and overall survival. In conclusion, our study demonstrated the potential of radiomics features as a valuable addition to existing clinical tools like the FIGO staging system, offering promising advancements in managing locally advanced cervical squamous cell carcinoma.

Staging of Cervical Cancer: A Practical Approach Using MRI and FDG PET

This review provides a practical approach to the imaging evaluation of patients with cervical cancer (CC), from initial diagnosis to restaging of recurrence, focusing on MRI and FDG PET. The primary updates to the International Federation of Gynecology and Obstetrics (FIGO) CC staging system, as well as these updates' relevance to clinical management, are discussed. The recent literature investigating the role of MRI and FDG PET in CC staging and image-guided brachytherapy is summarized. The utility of MRI and FDG PET in response assessment and posttreatment surveillance is described. Important findings on MRI and FDG PET that interpreting radiologists should recognize and report are illustrated. The essential elements of structured reports during various phases of CC management are outlined. Special considerations, including the role of imaging in patients desiring fertility-sparing management, differentiation of CC and endometrial cancer, and unusual CC histologies, are also described. Finally, future research directions including PET/MRI, novel PET tracers, and artificial intelligence applications are highlighted.

[68Ga]Ga-FAPI-04 PET/CT in the evaluation of epithelial ovarian cancer: comparison with [18F]F-FDG PET/CT

PURPOSE

To compare the efficacy of [68Ga]Ga-FAPI-04 PET/CT in primary or recurrent tumors and metastatic lesions of epithelial ovarian cancer (EOC) with that of fluorine-18 fluorodeoxyglucose ([18F]F-FDG) PET/CT.

METHODS

Forty-nine patients (median age, 57 years; IQR, 51-66 years) with histologically proven primary or relapsed EOC were enrolled. Participants underwent [18F]F-FDG and [68Ga]Ga-FAPI-04 PET/CT. The detection rate, diagnostic accuracy, semiquantitative parameters, tumor staging, and clinical management of the tracers were compared. The diagnostic performance of [18F]F-FDG and [68Ga]Ga-FAPI-04 PET/CT was evaluated and compared using surgical pathology. Differences between methods regarding the peritoneal cancer index (PCI) using preoperative imaging, surgical PCI, and tumor markers (CA125, HE4) were also assessed regarding peritoneal metastases.

RESULTS

Among the 49 patients, 28 had primary EOC; 21 had relapsed EOC. [68Ga]Ga-FAPI-04 PET/CT outperformed [18F]F-FDG PET/CT in detecting peritoneal metastases (96.8% vs. 83.0%; p < 0.001), retroperitoneal (99.5% vs. 91.4%; p < 0.001), and supradiaphragmatic lymph node metastases (100% vs. 80.4%; p < 0.001). Compared with [18F]F-FDG, [68Ga]Ga-FAPI-04 showed higher SUVmax for peritoneal metastases (17.31 vs. 13.68; p = 0.026) and retroperitoneal (8.72 vs. 6.56; p < 0.001) and supradiaphragmatic lymph node metastases (6.39 vs. 4.20; p < 0.001). Moreover, [68Ga]Ga-FAPI-04 PET/CT showed higher sensitivity compared with [18F]F-FDG PET/CT for detecting metastatic lymph nodes (80.6% vs. 61.3%; p = 0.031) and peritoneal metastases (97.5% vs. 75.9%; p < 0.001), using surgical pathology as the gold standard. Compared with [18F]F-FDG PET/CT, [68Ga]Ga-FAPI-04 PET/CT led to an upgrade in 14.3% and 33.3% of treatment-naive and relapse participants, resulting in management changes in 10.7% and 19.0% of the patients, respectively. The median PCIFAPI scores were significantly higher than PCIFDG (15 vs. 11; p < 0.001) and positively correlated with CA125 and HE4 levels and surgical PCI.

CONCLUSION

[68Ga]Ga-FAPI-04 PET/CT achieved higher sensitivity than [18F]F-FDG PET/CT in the detection and diagnosis of lymph node and peritoneal metastases, suggesting advantages regarding the preoperative staging of patients with EOC and, thereby, improving treatment decision-making.

TRIAL REGISTRATION

NCT05034146. Registered February 23, 2021.

Advances in Research, Diagnosis, and Treatment of Neuroendocrine Cervical Carcinoma: A Review

Neuroendocrine neoplasms (NENs) were classified separately in the 5th edition (2020) of the World Health Organization (WHO) classification of female genital malignancies. Cervical neuroendocrine carcinoma (NEC) is distinguished by its low incidence, high invasiveness, early local dissemination, and distant metastases. The purpose of this review is to outline the achievements in pathology, diagnostics, gene sequencing, and multi-modality treatment of cervical NEC.

An Update on the Role of MRI in Treatment Stratification of Patients with Cervical Cancer

Cervical cancer is the fourth most common cancer in women worldwide and the most common gynaecological malignancy. The FIGO staging system is the most commonly utilised classification system for cervical cancer worldwide. Prior to the most recent update in the FIGO staging in 2018, the staging was dependent upon clinical assessment alone. Concordance between the surgical and clinical FIGO staging decreases rapidly as the tumour becomes more advanced. MRI now plays a central role in patients diagnosed with cervical cancer and enables accurate staging, which is essential to determining the most appropriate treatment. MRI is the best imaging option for the assessment of tumour size, location, and parametrial and sidewall invasion. Notably, the presence of parametrial invasion precludes surgical options, and the patient will be triaged to chemoradiotherapy. As imaging is intrinsic to the new 2018 FIGO staging system, nodal metastases have been included within the classification as stage IIIC disease. The presence of lymph node metastases within the pelvis or abdomen is associated with a poorer prognosis, which previously could not be included in the staging classification as these could not be reliably detected on clinical examination. MRI findings corresponding to the 2018 revised FIGO staging of cervical cancers and their impact on treatment selection will be described.

Values of tumor volume on magnetic resonance imaging for a surgical approach to endometrial cancer

OBJECTIVE

To analyze the relationship between tumor volume in Endometrial Cancer (EC) on Magnetic Resonance Imaging (MRI) and lymph node metastasis to establish which patients benefit from omitting the lymphadenectomy.

METHODS

A retrospective observational study with 194 patients with EC identified between 2016 and 2021 at the Juan Ramón Jiménez University Hospital, Huelva (Spain) was carried out. Preoperative MRI of 127 patients was assessed. The tumor volume was analyzed on MRI by the ellipsoid formula and another alternative method with a manual ROI in different sections. Risk factors for node metastases were analyzed to understand its relationship and to identify an optimum criterion for the tailored surgery.

RESULTS

Univariate analysis showed risk factors for lymph node metastases were histological grade (p = 0.001), tumor with a volume greater than >25 cm3 (p < 0.001), lymphovascular space invaded (p = 0.007), and preoperative Ca 125 serum >28 (p < 0.001). Multivariate analysis indicated that tumor volume index >25 cm3 was an independent risk factor for lymph node metastases. The patients without significant proposed risk factors (volume index >25 cm3  [OR = 0.64], Ca 125 > 28 [OR = 0.32], and high histological grade [OR = 2.6]) did not present lymph node metastases, independent of myometrial invasion.

CONCLUSIONS

Lymphadenectomy can be omitted in patients with Endometrioid carcinoma that do not have any of the following risk factors: high-grade tumor, elevated Ca 125 (>28), and tumor volume on MRI greater than 25 cm3 . Tumor volume might predict the state of lymph nodes in EC and it could give information regarding surgical management.

Which factors predict parametrial involvement in stage IB cervical cancer? A Chinese multicentre study

OBJECTIVE

To explore the clinicopathological risk factors influencing parametrial involvement (PI) in stage IB cervical cancer patients and compare the oncological outcomes between Q-M type B radical hysterectomy (RH) group and Q-M type C RH group.

METHODS

Univariate and multivariate analyses were performed to explore the clinicopathological factors related to PI. Overall survival (OS) and disease-free survival (DFS) in patients with stage IB cervical cancer who underwent Q-M type B or Q-M type C RH under different circumstances of PI were also compared before and after propensity score matching (1:1 matching).

RESULTS

A total of 6358 patients were enrolled in this study. Depth of stromal invasion>1/2 (HR: 3.139, 95% CI: 1.550-6.360; P = 0.001), vaginal margin (+) (HR: 4.271, 95% CI: 1.368-13.156; P = 0.011), lymphovascular space invasion (LVSI) (+) (HR: 2.238, 95% CI: 1.353-3.701; P = 0.002) and lymph node metastases (HR: 5.173, 95% CI: 3.091-8.658; P < 0.001) were associated with PI. Among the 6273 patients with negative PI, those in the Q-M type B RH group had a higher 5-year OS and DFS than those in the Q-M type C RH group before and after 1:1 matching. Among the 85 patients with positive PI, Q-M type C RH showed no survival benefits before and after 1:1 matching.

CONCLUSION

Stage IB cervical cancer patients with no lymph node metastasis, LVSI(-) and depth of stromal invasion ≤1/2 may be considered for Q-M type B radical hysterectomy.

MR Imaging of Gynecologic Tumors: Pearls, Pitfalls, and Tumor Mimics

MR imaging is the modality of choice for the pre-treatment evaluation of patients with gynecologic malignancies, given its excellent soft tissue contrast and multi-planar capability. However, it is not without pitfalls. Challenges can be encountered in the assessment of the infiltration of myometrium, vagina, cervical stroma, and parametria, which are crucial prognostic factors for endometrial and cervical cancers. Other challenges can be encountered in the distinction between solid and non-solid tissue and in the identification of peritoneal carcinomatosis for the sonographically indeterminate adnexal mass.

Quantitative dynamic contrast-enhanced parameters and intravoxel incoherent motion facilitate the prediction of TP53 status and risk stratification of early-stage endometrial carcinoma

BACKGROUND

The aim of the study was to investigate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and intravoxel incoherent motion (IVIM) in differentiating TP53-mutant from wild type, low-risk from non-low-risk early-stage endometrial carcinoma (EC).

PATIENTS AND METHODS

A total of 74 EC patients underwent pelvic MRI. Parameters volume transfer constant (K^trans), rate transfer constant (K_ep), the volume of extravascular extracellular space per unit volume of tissue (V_e), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and microvascular volume fraction (f) were compared. The combination of parameters was investigated by logistic regression and evaluated by bootstrap (1000 samples), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

RESULTS

In the TP53-mutant group, K^trans and K_ep were higher and D was lower than in the TP53-wild group; K^trans, V_e, f, and D were lower in the non-low-risk group than in the low-risk group (all P < 0.05). In the identification of TP53-mutant and TP53-wild early-stage EC, K^trans and D were independent predictors, and the combination of them had an optimal diagnostic efficacy (AUC, 0.867; sensitivity, 92.00%; specificity, 80.95%), which was significantly better than D (Z = 2.169, P = 0.030) and K^trans (Z = 2.572, P = 0.010). In the identification of low-risk and non-low-risk early-stage EC, K^trans, V_e, and f were independent predictors, and the combination of them had an optimal diagnostic efficacy (AUC, 0.947; sensitivity, 83.33%; specificity, 93.18%), which was significantly better than D (Z = 3.113, P = 0.002), f (Z = 4.317, P < 0.001), K^trans (Z = 2.713, P = 0.007), and V_e (Z = 3.175, P = 0.002). The calibration curves showed that the above two combinations of independent predictors, both have good consistency, and DCA showed that these combinations were reliable clinical prediction tools.

CONCLUSIONS

Both DCE-MRI and IVIM facilitate the prediction of TP53 status and risk stratification in early-stage EC. Compare with each single parameter, the combination of independent predictors provided better predictive power and may serve as a superior imaging marker.

Imaging of pediatric ovarian tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee White Paper

Ovarian tumors in children are uncommon. Like those arising in the adult population, they may be broadly divided into germ cell, sex cord, and surface epithelium subtypes; however, germ cell tumors comprise the majority of lesions in children, whereas tumors of surface epithelial origin predominate in adults. Diagnostic workup, including the use of imaging, requires an approach that often differs from that required in an adult. This paper offers consensus recommendations for imaging of pediatric patients with a known or suspected primary ovarian malignancy at diagnosis and during follow-up.

Smooth Muscle Tumors of the Uterus at MRI: Focus on Leiomyomas and FIGO Classification

Leiomyomas are smooth muscle tumors of the uterus and are the most common uterine neoplasm. Although leiomyomas are usually asymptomatic, they can manifest with symptoms such as pain or uterine bleeding. Leiomyomas are classified on the basis of their anatomic location and morphology. Localization of leiomyomas relative to the endometrium, myometrium, and uterine serosa with use of the International Federation of Gynecology and Obstetrics (FIGO) classification system is helpful for guiding management in symptomatic patients. The FIGO system is a practical and universally accepted approach for classifying leiomyomas to guide radiologists and clinicians in deciding management. The MRI appearance of conventional leiomyomas is related to their tissue contents of smooth muscle and fibrous tissue and is well established. The MRI features of some leiomyoma subtypes and forms of degeneration also have been described. Other smooth muscle tumors of the uterus recognized in the 2020 World Health Organization classification system include intravenous leiomyomatosis, smooth muscle tumors of uncertain malignant potential, and metastasizing leiomyoma. At the far end of the spectrum are leiomyosarcomas, which are frankly malignant and therefore must be managed accordingly. Although MRI features that suggest a diagnosis of leiomyosarcoma have been proposed, these features overlap with those of some leiomyoma subtypes and degeneration. ^© RSNA, 2023 See the invited commentary by Fennessy and Gargiulo in this issue. Online supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article. Quiz questions for this article are available through the Online Learning Center.

3D multifrequency magnetic resonance elastography in distinguishing endometrial and cervical adenocarcinoma

OBJECTIVES

To prospectively evaluate the value of tomoelastography in determining the underlying origins of uterine adenocarcinoma.

METHODS

This prospective work was approved by our institutional review board, and all patients provided informed consent. 64 patients with histopathologically confirmed adenocarcinomas originated either from the cervix (CAC: cervical adenocarcinoma) or endometrium (EAC: endometrial adenocarcinoma) underwent MRI and tomoelastography examination on a 3.0 T MR scanner. To biomechanically characterize the adenocarcinoma, two MRE-derived parameters maps were provided in the tomoelastography, namely shear wave speed (c, m/s) and loss angle (φ, radian), which represented the stiffness and fluidity, respectively. The MRE-derived parameters were compared by using a two-tailed independent-sample t-test or Mann-Whitney U test. Five morphologic features were also analyzed by using the χ2 test. Logistic regression analysis was used to develop diagnosis models. Delong test was used to compare the receiver operating characteristic curves whith different diagnostic models and evaluate the diagnostic efficiency.

RESULTS

CAC were significantly stiffer and behaved more fluid like than EAC (c: 2.58 ± 0.62 m/s vs.2.17 ± 0.72 m/s, p = 0.029, φ, 0.97 ± 0.19 rad vs.0.73 ± 0.26 rad, p < 0.0001). The diagnostic performance for distinguishing CAC from EAC was similar for c (AUC = 0.71) and for φ (AUC = 0.75). For distinguishing CAC from EAC, the AUC of tumor location was the higher than c and φ (AUC = 0.80). A cmobined model consisting of tumor location, c, and φ achieved the best diagnostic performance, with an AUC of 0.88 (77.27% sensitivity and 85.71% specificity).

CONCLUSIONS

CAC and EAC displayed their unique biomechanical features. 3D multifrequency MRE provided added value to the conventional morphologic features in distinguishing the two types of diseases.

Diagnostic accuracy of MRI for evaluating myometrial invasion in endometrial cancer: a comparison of MUSE-DWI, rFOV-DWI, and DCE-MRI

OBJECTIVES

To compare the image quality of high-resolution diffusion-weighted imaging (DWI) using multiplexed sensitivity encoding (MUSE) versus reduced field-of-view (rFOV) techniques in endometrial cancer (EC) and to compare the diagnostic performance of these techniques with that of dynamic contrast-enhanced (DCE) MRI for assessing myometrial invasion of EC.

METHODS

MUSE-DWI and rFOV-DWI were obtained preoperatively in 58 women with EC. Three radiologists assessed the image quality of MUSE-DWI and rFOV-DWI. For 55 women who underwent DCE-MRI, the same radiologists assessed the superficial and deep myometrial invasion using MUSE-DWI, rFOV-DWI, and DCE-MRI. Qualitative scores were compared using the Wilcoxon signed-rank test. Receiver operating characteristic analysis was performed to compare the diagnostic performance.

RESULTS

Artifacts, sharpness, lesion conspicuity, and overall quality were significantly better with MUSE-DWI than with rFOV-DWI (p < 0.05). The area under the curve (AUC) of MUSE-DWI, rFOV-DWI, and DCE-MRI for the assessment of myometrial invasion were not significantly different except for significantly higher AUC of MUSE-DWI than that of DCE-MRI for superficial myometrial invasion (0.76 for MUSE-DWI and 0.64 for DCE-MRI, p = 0.049) and for deep myometrial invasion (0.92 for MUSE-DWI and 0.80 for DCE-MRI, p = 0.022) in one observer, and that of rFOV-DWI for deep myometrial invasion in another observer (0.96 for MUSE-DWI and 0.89 for rFOV-MRI, p = 0.048).

CONCLUSION

MUSE-DWI exhibits better image quality than rFOV-DWI. MUSE-DWI and rFOV-DWI shows almost equivalent diagnostic performance compared to DCE-MRI for assessing superficial and deep myometrial invasion in EC although MUSE-DWI may be helpful for some radiologists.

Predicting histopathology markers of endometrial carcinoma with a quantitative image analysis approach based on spherical harmonics in multiparametric MRI

PURPOSE

Identifying optimal machine learning pipelines for computer-aided diagnosis is key for the development of robust, reproducible, and clinically relevant imaging biomarkers for endometrial carcinoma. The purpose of this study was to introduce the mathematical development of image descriptors computed from spherical harmonics (SPHARM) decompositions as well as the associated machine learning pipeline, and to evaluate their performance in predicting deep myometrial invasion (MI) and histopathological high-grade in preoperative multiparametric magnetic resonance imaging (MRI).

PATIENTS AND METHODS

This retrospective study included 128 women with histopathology-confirmed endometrial carcinomas who underwent 1.5-T MRI before hysterectomy between January 2011 and July 2015. SPHARM descriptors of each tumor were computed on multiparametric MRI images (T2-weighted, diffusion-weighted, dynamic contrast-enhanced-MRI and apparent diffusion coefficient maps). Tensor-based logistic regression was used to classify two-dimensional SPHARM rotationally-invariant descriptors. Head-to-head comparisons with radiomics analyses were performed with DeLong tests with Bonferroni-Holm correction to compare diagnostic performances.

RESULTS

With all MRI contrasts, SPHARM analysis resulted in area under the curve, sensitivity, specificity, and balanced accuracy values of 0.94 (95% confidence interval [CI]: 0.85, 1.00), 100% (95% CI: 100, 100), 74% (95% CI: 51, 92), 87% (95% CI: 78, 98), respectively, for predicting deep MI. For predicting high-grade tumor histology, the corresponding values for the same diagnostic metrics were 0.81 (95% CI: 0.64, 0.90), 93% (95% CI: 67, 100), 63% (95% CI: 45, 79) and 78% (95% CI: 64, 86). The corresponding values achieved via radiomics were 0.92 (95% CI: 0.82, 0.95), 82% (95% CI: 65, 93), 80% (95% CI: 51, 94), 81% (95% CI: 70, 91) for deep MI and 0.72 (95% CI: 0.58, 0.83), 93% (95% CI: 65, 100), 55% (95% CI: 41, 69), 74% (95% CI: 52, 88) for high-grade histology. The diagnostic performance of the SPHARM analysis was not significantly different (P = 0.62) from that of radiomics for predicting deep MI but was significantly higher (P = 0.044) for predicting high-grade histology.

CONCLUSION

The proposed SPHARM analysis yields similar or higher diagnostic performance than radiomics in identifying deep MI and high-grade status in histology-proven endometrial carcinoma.

Imaging Recommendations for Diagnosis, Staging, and Management of Uterine Cancer

Uterine cancers are classified into cancers of the corpus uteri (uterine carcinomas and carcinosarcoma) and corpus uteri (sarcomas) by the AJCC staging system (eighth edition). Endometrial carcinoma is the most common amongst these with prolonged estrogen exposure being a well-known risk factor. The FIGO staging system for endometrial carcinoma is primarily surgical and includes total hysterectomy, bilateral salpingo-oophorectomy, and lymphadenectomy. Imaging is useful in the preoperative evaluation of tumor stage, especially assessment of myometrial invasion and cervical stromal extension. Dynamic contrast enhanced MRI with DWI has a high staging accuracy and is the preferred imaging modality for primary evaluation with contrast-enhanced CT abdomen being indicated for recurrent disease. PET/CT is considered superior in evaluation of lymph nodes and extra pelvic metastases.

Assessment of Salvage Surgery in Persistent Cervical Cancer after Definitive Radiochemotherapy: A Systematic Review

Background and Objectives: The standard treatment approach in locally advanced cervical cancer (LACC) is exclusive concurrent chemoradiation therapy (RTCT). The risk of local residual disease after six months from RTCT is about 20-30%. It is directly related to relapse risk and poor survival, such as in patients with recurrent cervical cancer. This systematic review aims to describe studies investigating salvage surgery's role in persistent/recurrent disease in LACC patients who underwent definitive RTCT. Materials and Methods: Studies were eligible for inclusion when patients had LACC with radiologically suspected or histologically confirmed residual disease after definitive RTCT, diagnosed with post-treatment radiological workup or biopsy. Information on complications after salvage surgery and survival outcomes had to be reported. The methodological quality of the articles was independently assessed by two researchers with the Newcastle-Ottawa scale. Following the recommendations in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we systematically searched the PubMed, Scopus, Cochrane, Medline, and Medscape databases in May 2022. We applied no language or geographical restrictions but considered only English studies. We included studies containing data about postoperative complications and survival outcomes. Results: Eleven studies fulfilled the inclusion criteria and all were retrospective observational studies. A total of 601 patients were analyzed concerning the salvage surgery in LACC patients for persistent/recurrent disease after RTCT treatment. Overall, 369 (61.4%) and 232 (38.6%) patients underwent a salvage hysterectomy (extrafascial or radical) and pelvic exenteration (anterior, posterior, or total), respectively. Four hundred and thirty-nine (73%) patients had histologically confirmed the residual disease in the salvage surgical specimen, and 109 patients had positive margins (overall range 0-43% of the patients). The risk of severe (grade ≥ 3) postoperative complications after salvage surgery is 29.8% (range 5-57.5%). After a median follow-up of 38 months, the overall RR was about 32% with an overall death rate of 40% after hysterectomy or pelvic exenteration with or without lymphadenectomy. Conclusions: There is heterogeneity between the studies both in their design and results, therefore the effect of salvage surgery on survival and recurrence cannot be adequately estimated. Future homogeneous studies with an appropriately selected population are needed to analyze the safety and efficacy of salvage hysterectomy or pelvic exenteration in patients with residual tumors after definitive RTCT.

Utility of Whole Body 18F-FDG PET/CT in Comparison to Pelvic MRI in Evaluation of Local Staging of Early-Stage Carcinoma Cervix

OBJECTIVE

This prospective comparative study aimed to investigate the applied value of whole body 2-deoxy-2[fluorine-18]fluoro- D-glucose positron emission tomography integrated with computed tomography (¹⁸F-FDG PET/CT) in comparison to pelvic magnetic resonance imaging (MRI) in early cervical cancer patients.

MATERIAL AND METHODS

A prospective study was performed on 47 clinically early-stage cervical cancer patients evaluated with positron emission tomography/computed tomography (PET/CT) and MRI before surgery. The final postoperative histopathology report served as the reference standard. Both PET/CT and MRI images were analyzed and correlated with histopathologic findings concerning parametrial and lymph node involvement.

RESULTS

Sensitivity, specificity, and negative predictive value (NPV) of PET/CT were 33.3%, 81.8%, and 94.7%, respectively, for parametrium assessment. And the corresponding values of pelvic MRI were 33.3%, 63.6%, and 93.3%, respectively (PET/CT versus MRI, p > 0.05). The positive predictive value (PPV) of PET/CT (11.1%) was higher than MRI (5.9%) for parametrial assessment (p < 0.05). The sensitivity, specificity, PPV, and NPV of PET/CT were 75%, 83.7%, 30%, and 97.3%, respectively, for lymph node assessment. And the corresponding values of MRI were 75%, 81.3%, 27.3%, and 97.2%, respectively (PET/CT versus MRI, p > 0.05). There was no significant difference between MRI and PET/CT concerning stage migration (p = 0.4276).

CONCLUSION

The PET/CT had no additional utility (compared to MRI) in the evaluation of local staging of clinically early cervical carcinoma patients.

Development of an improved diagnostic nomogram for preoperative prediction of small cell neuroendocrine cancer of the cervix

OBJECTIVES

Accurate preoperative diagnosis of small cell neuroendocrine cancer of the cervix (SCNECC) is crucial for establishing the best treatment plan. This study aimed to develop an improved, non-invasive method for the preoperative diagnosis of SCNECC by integrating clinical, MR morphological, and apparent diffusion coefficient (ADC) information.

METHODS

A total of 105 pathologically confirmed cervical cancer patients (35 SCNECC, 70 non-SCNECC) from multiple centres with complete clinical and MR records were included. Whole lesion histogram analysis of the ADC was performed. Multivariate logistic regression analysis was used to develop diagnostic models based on clinical, morphological, and histogram data. The predictive performance in terms of discrimination, calibration, and clinical usefulness of the different models was assessed. A nomogram for preoperatively discriminating SCNECC was developed from the combined model.

RESULTS

In preoperative SCNECC diagnosis, the combined model, which had a diagnostic AUC (area under the curve) of 0.937 (95% CI: 0.887-0.987), outperformed the clinical-morphological model, which had an AUC of 0.869 (CI: 0.788-0.949), and the histogram model, which had an AUC of 0.872 (CI: 0.792-0.951). The calibration curve and decision curve analyses suggest that the combined model achieved good fitting and clinical utility.

CONCLUSIONS

Non-invasive preoperative diagnosis of SCNECC can be achieved with high accuracy by integrating clinical, MR morphological, and ADC histogram features. The nomogram derived from the combined model can provide an easy-to-use clinical preoperative diagnostic tool for SCNECC.

ADVANCES IN KNOWLEDGE

It is clear that the therapeutic strategies for SCNECC are different from those for other pathological types of cervical cancer according to V 1.2021 of the NCCN clinical practice guidelines in oncology for cervical cancer. This research developed an improved, non-invasive method for the preoperative diagnosis of SCNECC by integrating clinical, MR morphological, and apparent diffusion coefficient (ADC) information.

Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases

Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-based diagnosis in patients with uterine sarcomas. Fifteen sequences of MRI for patients (uterine sarcoma group: n = 63; uterine leiomyoma: n = 200) were used to train the models. Six radiologists (three specialists, three practitioners) interpreted the same images for validation. The most important individual sequences for diagnosis were axial T2-weighted imaging (T2WI), sagittal T2WI, and diffusion-weighted imaging. These sequences also represented the most accurate combination (accuracy: 91.3%), achieving diagnostic ability comparable to that of specialists (accuracy: 88.3%) and superior to that of practitioners (accuracy: 80.1%). Moreover, radiologists' diagnostic accuracy improved when provided with DNN results (specialists: 89.6%; practitioners: 92.3%). Our DNN models are valuable to improve diagnostic accuracy, especially in filling the gap of clinical skills between interpreters. This method can be a universal model for the use of deep learning in the diagnostic imaging of rare tumors.

Utilization of functional MRI in the diagnosis and management of cervical cancer

INTRODUCTION

Imaging is integral part of cervical cancer management. Currently, MRI is used for staging, follow up and image guided adaptive brachytherapy. The ongoing IQ-EMBRACE sub-study is evaluating the use of MRI for functional imaging to aid in the assessment of hypoxia, metabolism, hemodynamics and tissue structure. This study reviews the current and potential future utilization of functional MRI imaging in diagnosis and management of cervical cancer.

METHODS

We searched PubMed for articles characterizing the uses of functional MRI (fMRI) for cervical cancer. The current literature regarding these techniques in diagnosis and outcomes for cervical cancer were then reviewed.

RESULTS

The most used fMRI techniques identified for use in cervical cancer include diffusion weighted imaging (DWI) and dynamic contrast enhancement (DCE). DCE-MRI indirectly reflects tumor perfusion and hypoxia. This has been utilized to either characterize a functional risk volume of tumor with low perfusion or to characterize at-risk tumor voxels by analyzing signal intensity both pre-treatment and during treatment. DCE imaging in these situations has been associated with local control and disease-free survival and may have predictive/prognostic significance, however this has not yet been clinically validated. DWI allows for creation of ADC maps, that assists with diagnosis of local malignancy or nodal disease with high sensitivity and specificity. DWI findings have also been correlated with local control and overall survival in patients with an incomplete response after definitive chemoradiotherapy and thus may assist with post-treatment follow up. Other imaging techniques used in some instances are MR-spectroscopy and perfusion weighted imaging. T2-weighted imaging remains the standard technique used for diagnosis and radiation treatment planning. In many instances, it is unclear what additional information functional-MRI techniques provide compared to standard MRI imaging.

CONCLUSIONS

Functional MRI provides potential for improved diagnosis, prediction of treatment response and prognostication in cervical cancer. Specific sequences such as DCE, DWI and ADC need to be validated in a large prospective setting prior to widespread use. The ongoing IQ-EMBRACE study will provide important clinical information regarding these imaging modalities.

Endometrial Cancer in Reproductive Age: Fertility-Sparing Approach and Reproductive Outcomes

Endometrial cancer is the most common gynecologic malignancy in developed countries and approximately 7% of the women with endometrial cancer are below the age of 45. Management of endometrial cancer in young women who desire to maintain fertility presents a unique set of challenges since the standard surgical treatment based on hysterectomy and salpingo-oophorectomy is often not compatible with the patient's goals. A fertility-preserving approach can be considered in selected patients with early stage and low-grade endometrial cancer. An increasing amount of data suggest that oncologic outcomes are not compromised if a conservative approach is utilized with close monitoring until childbearing is completed. If a fertility-preserving approach is not possible, assisted reproductive technologies can assist patients in achieving their fertility goals.

Can MRI Be Used as a Sole Diagnostic Modality in Determining Clinical Stage in Cervical Cancer?

OBJECTIVE

The objective of this study was to compare staging by MRI to clinical staging in patients with cervical cancer and to determine the histological accuracy of staging by MRI and examination under anesthesia (EUA) in early stage disease.

METHODS

This was a retrospective cohort study of patients diagnosed with cervical cancer between 2010 and 2020 at the Radboud University Medical Centre, the Netherlands. Pretreatment stage (FIGO 2009) by MRI was compared with staging by EUA. Diagnostic accuracy in terms of sensitivity, specificity, positive, and negative predictive value was calculated for MRI and EUA in patients undergoing surgery (early stage disease) with histological results as a reference standard.

RESULTS

A total of 358 patients were included in the study and MRI-based stage differed from EUA stage in 30.7%. In 12.3% this meant a discrepancy in treatment assignment between MRI and EUA. Diagnostic accuracy of MRI in terms of sensitivity and specificity for detecting early stage disease was comparable to EUA in surgical patients. Further analyses showed that premenopausal status, early stage disease and a tumor diameter of <2 cm were associated with improved comparability of MRI and EUA (98%).

CONCLUSION

There is still a large discrepancy between MRI and EUA. In patients with suspected early stage disease, diagnostic accuracy of MRI is similar to EUA, especially for premenopausal women with early stage disease and a tumor diameter of <2 cm.

Update on MRI in Evaluation and Treatment of Endometrial Cancer

Endometrial cancer is the second most common gynecologic cancer worldwide and the most common gynecologic cancer in the United States, with an increasing incidence in high-income countries. Although the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer is a surgical staging system, contemporary published evidence-based data and expert opinions recommend MRI for treatment planning as it provides critical diagnostic information on tumor size and depth, extent of myometrial and cervical invasion, extrauterine extent, and lymph node status, all of which are essential in choosing the most appropriate therapy. Multiparametric MRI using a combination of T2-weighted sequences, diffusion-weighted imaging, and multiphase contrast-enhanced imaging is the mainstay for imaging assessment of endometrial cancer. Identification of important prognostic factors at MRI improves both treatment selection and posttreatment follow-up. MRI also plays a crucial role for fertility-preserving strategies and in patients who are not surgical candidates by helping guide therapy and identify procedural complications. This review is a product of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease-Focused Panel and reflects a multidisciplinary international collaborative effort to summarize updated information highlighting the role of MRI for endometrial cancer depiction and delineation, treatment planning, and follow-up. The article includes information regarding dedicated MRI protocols, tips for MRI reporting, imaging pitfalls, and strategies for image quality optimization. The roles of MRI-guided radiation therapy, hybrid PET/MRI, and advanced MRI techniques that are applicable to endometrial cancer imaging are also discussed. Online supplemental material is available for this article. ^©RSNA, 2022.

A Comparison of Dynamic Contrast-Enhanced Magnetic Resonance Imaging and T2-Weighted Imaging in Determining the Depth of Myometrial Invasion in Endometrial Carcinoma—A Retrospective Study

This study aims to compare dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with T2-weighted imaging (T2WI) in defining the depth of myometrial invasion in endometrial carcinoma. This retrospective study included 32 subjects with endometrial carcinoma who underwent 3.0T magnetic resonance imaging (MRI) prior to hysterectomy. DCE-MRI and T2WI were evaluated to determine the depth of myometrial invasion in endometrial carcinoma. A set of data consisting of the sensitivity, specificity, predictive values, and accuracy of DCE-MRI and T2WI were obtained and compared with the histopathological results. Out of the 32 cases included, the histopathological examination revealed that 50% myometrial invasion was found in 11 patients and ≥50% myometrial invasion was found in 21 patients. In the assessment of the tumor invasion, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of T2WI were 45.45%, 90.48 %, 71.43%, 76.0%, and 75.0%, respectively. The corresponding values for DCE-MRI were 81.82%, 76.19%, 64.29%, 88.89 %, and 78.12%, respectively. When T2WI were read together with DCE-MRI, the values were 90.91%, 90.48%, 83.33%, 95.0%, and 90.62%, respectively. Thus, the sensitivity and accuracy of DCE-MRI were greater compared to T2WI in defining the depth of myometrial invasion. However, the merging of T2WI and DCE-MRI increased the specificity and PPV value and improved the sensitivity, NPV and accuracy in detecting myometrial invasion. DCE-MRI was more sensitive but less specific than T2WI in defining the depth of myometrial invasion. In conclusion, combining DCE-MRI and T2WI further improves the diagnostic performance for myometrial invasion in endometrial carcinoma.

Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network

PURPOSE

Contouring clinical target volume (CTV) from medical images is an essential step for radiotherapy (RT) planning. Magnetic resonance imaging (MRI) is used as a standard imaging modality for CTV segmentation in cervical cancer due to its superior soft-tissue contrast. However, the delineation of CTV is challenging as CTV contains microscopic extensions that are not clearly visible even in MR images, resulting in significant contour variability among radiation oncologists depending on their knowledge and experience. In this study, we propose a fully automated deep learning-based method to segment CTV from MR images.

METHODS

Our method begins with the bladder segmentation, from which the CTV position is estimated in the axial view. The superior-inferior CTV span is then detected using an Attention U-Net. A CTV-specific region of interest (ROI) is determined, and three-dimensional (3-D) blocks are extracted from the ROI volume. Finally, a CTV segmentation map is computed using a 3-D U-Net from the extracted 3-D blocks.

RESULTS

We developed and evaluated our method using 213 MRI scans obtained from 125 patients (183 for training, 30 for test). Our method achieved (mean ± SD) Dice similarity coefficient of 0.85 ± 0.03 and the 95th percentile Hausdorff distance of 3.70 ± 0.35 mm on test cases, outperforming other state-of-the-art methods significantly (p-value < 0.05). Our method also produces an uncertainty map along with the CTV segmentation by employing the Monte Carlo dropout technique to draw physician's attention to the regions with high uncertainty, where careful review and manual correction may be needed.

CONCLUSIONS

Experimental results show that the developed method is accurate, fast, and reproducible for contouring CTV from MRI, demonstrating its potential to assist radiation oncologists in alleviating the burden of tedious contouring for RT planning in cervical cancer.

Development and Validation of Multiparametric MRI-based Radiomics Models for Preoperative Risk Stratification of Endometrial Cancer

Background Stratifying high-risk histopathologic features in endometrial carcinoma is important for treatment planning. Radiomics analysis at preoperative MRI holds potential to identify high-risk phenotypes. Purpose To evaluate the performance of multiparametric MRI three-dimensional radiomics-based machine learning models for differentiating low- from high-risk histopathologic markers-deep myometrial invasion (MI), lymphovascular space invasion (LVSI), and high-grade status-and advanced-stage endometrial carcinoma. Materials and Methods This dual-center retrospective study included women with histologically proven endometrial carcinoma who underwent 1.5-T MRI before hysterectomy between January 2011 and July 2015. Exclusion criteria were tumor diameter less than 1 cm, missing MRI sequences or histopathology reports, neoadjuvant therapy, and malignant neoplasms other than endometrial carcinoma. Three-dimensional radiomics features were extracted after tumor segmentation at MRI (T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI). Predictive features were selected in the training set with use of random forest (RF) models for each end point, and trained RF models were applied to the external test set. Five board-certified radiologists conducted MRI-based staging and deep MI assessment in the training set. Areas under the receiver operating characteristic curve (AUCs) were reported with balanced accuracies, and radiologists' readings were compared with radiomics with use of McNemar tests. Results In total, 157 women were included: 94 at the first institution (training set; mean age, 66 years ± 11 [SD]) and 63 at the second institution (test set; 67 years ± 12). RF models dichotomizing deep MI, LVSI, high grade, and International Federation of Gynecology and Obstetrics (FIGO) stage led to AUCs of 0.81 (95% CI: 0.68, 0.88), 0.80 (95% CI: 0.67, 0.93), 0.74 (95% CI: 0.61, 0.86), and 0.84 (95% CI: 0.72, 0.92), respectively, in the test set. In the training set, radiomics provided increased performance compared with radiologists' readings for identifying deep MI (balanced accuracy, 86% vs 79%; P = .03), while no evidence of a difference was observed in performance for advanced FIGO stage (80% vs 78%; P = .27). Conclusion Three-dimensional radiomics can stratify patients by using preoperative MRI according to high-risk histopathologic end points in endometrial carcinoma and provide nonsignificantly different or higher performance than radiologists in identifying advanced stage and deep myometrial invasion, respectively. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Kido and Nishio in this issue.

Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images

BACKGROUND AND PURPOSE

Early Regression Index (ERI_TCP) is an image-based parameter based on tumor control probability modelling, that reported interesting results in predicting pathological complete response (pCR) after pre-operative chemoradiotherapy (CRT) in rectal cancer. This study aims to evaluate this parameter for Locally Advanced Cervical Cancer (LACC), considering not only T2-weighted but also diffusion-weighted (DW) Magnetic Resonance (MR) images, comparing it with other image-based parameters such as tumor volumes and apparent coefficient diffusion (ADC).

MATERIALS AND METHODS

A total of 88 patients affected by LACC (FIGO IB2-IVA) and treated with CRT were enrolled. An MRI protocol consisting in two acquisitions (T2-w and DWI) in two times (before treatment and at mid-therapy) was applied. Gross Tumor Volume (GTV) was delineated and ERI_TCP was calculated for both imaging modalities. Surgery was performed for each patient after nCRT: pCR was considered in case of absence of any residual tumor cells. The predictive performance of ERI_TCP, GTV volumes (calculated on T2-w and DW MR images) and ADC parameters were evaluated in terms of area (AUC) under the Receiver Operating Characteristic (ROC) curve considering pCR and two-years survival parameters as clinical outcomes.

RESULTS

ERI_TCP and GTV volumes calculated on DW MR images (ERI_DWI and V_{mid_DWI}) significantly predict pCR (AUC = 0.77 and 0.75 respectively) with results superior to those observed considering T2-w MR images or ADC parameters. Significance was also reported in the prediction of 2-years local control and disease free-survival.

CONCLUSION

This study identified ERI_TCP and V_mid as good predictor of pCR in case of LACC, especially if calculated considering DWI. Using these indicators, it is possible to early identify not responders and modifying the treatment, accordingly.

Pretreatment Radiologically Enlarged Lymph Nodes as a Significant Prognostic Factor in Clinical Stage IIB Cervical Cancer: Evidence from a Taiwanese Tertiary Care Center in Reaching Consensus

The incidence of lymph node (LN) involvement and its prognostic value based on radiological imaging in stage IIB cervical cancer (CC) remains unclear, and evidence regarding oncological outcomes of patients with stage IIB CC with LN metastases is limited. In this study we retrospectively reviewed the incidence and prognostic significance of pretreatment radiologic LN status in 72 patients with clinical stage IIB CC (FIGO 2009), with or without radiologic evidence of LN enlargement. An enlarged LN was defined as a diameter > 10 mm on CT/MRI. Progression-free survival (PFS) and overall survival (OS) were assessed. Radiologic LN enlargement of >10 mm was observed in 45.8% of patients with stage IIB CC. PFS (p = 0.0088) and OS rates (p = 0.0032) were significantly poorer in the LN group (n = 33) than in the non-LN group (n = 39). Univariate Cox analysis revealed that LN > 10 mm contributed to a higher rate of recurrence and mortality. In conclusion, nearly half of the patients with clinical stage IIB CC had enlarged LNs (>10 mm) identified during pretreatment radiologic evaluation, which negatively impacted prognosis. Our findings highlight the need to incorporate CT- or MRI-based LN assessment before treatment for stage IIB CC.

Evaluation of Amide Proton Transfer-Weighted Imaging for Risk Factors in Stage I Endometrial Cancer: A Comparison With Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging

Background

Endometrial cancer (EC) is one of the most common gynecologic malignancies in clinical practice. This study aimed to compare the value of diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and amide proton transfer-weighted imaging (APTWI) in the assessment of risk stratification factors for stage I EC including histological subtype, grade, stage, and lymphovascular space invasion (LVSI).

Methods

A total of 72 patients with stage I EC underwent pelvic MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), and magnetization transfer ratio asymmetry (MTRasym at 3.5 ppm) were calculated and compared in risk groups with the Mann–Whitney U test or independent samples t-test. Spearman’s rank correlation was applied to depict the correlation of each parameter with risk stratification. The diagnostic efficacy was evaluated with receiver operating characteristic (ROC) curve analysis and compared using the DeLong test. A multivariate logistic regression was conducted to explore the optimal model for risk prediction.

Results

There were significantly greater MTRasym (3.5 ppm) and MK and significantly lower ADC and MD in the non-adenocarcinoma, stage IB, LVSI-positive, high-grade, and non-low-risk groups (all p < 0.05). The MK and MTRasym (3.5 ppm) were moderately positively correlated with risk stratification as assessed by the European Society for Medical Oncology (EMSO) clinical practice guidelines (r = 0.640 and 0.502, respectively), while ADC and MD were mildly negatively correlated with risk stratification (r = −0.358 and −0.438, respectively). MTRasym (3.5 ppm), MD, and MK were identified as independent risk predictors in stage I EC, and optimal predictive performance was obtained with their combinations (AUC = 0.906, sensitivity = 70.97%, specificity = 92.68%). The results of the validation model were consistent with the above results, and the calibration curve showed good accuracy and consistency.

Conclusions

Although similar performance was obtained with each individual parameter of APTWI, DWI, and DKI for the noninvasive assessment of aggressive behavior in stage I EC, the combination of MD, MK, and MTRasym (3.5 ppm) provided improved predictive power for non-low-risk stage I EC and may serve as a superior imaging marker.

Radiomics-based prediction of two-year clinical outcome in locally advanced cervical cancer patients undergoing neoadjuvant chemoradiotherapy

PURPOSE

The aim of this study is to determine if radiomics features extracted from staging magnetic resonance (MR) images could predict 2-year long-term clinical outcome in patients with locally advanced cervical cancer (LACC) after neoadjuvant chemoradiotherapy (NACRT).

MATERIALS AND METHODS

We retrospectively enrolled patients with LACC diagnosis who underwent NACRT followed by radical surgery in two different institutions. Radiomics features were extracted from pre-treatment 1.5 T T2w MR images. The predictive performance of each feature was quantified in terms of Wilcoxon-Mann-Whitney test. Among the significant features, Pearson correlation coefficient (PCC) was calculated to quantify the correlation among the different predictors. A logistic regression model was calculated considering the two most significant features at the univariate analysis showing the lowest PCC value. The predictive performance of the model created was quantified out using the area under the receiver operating characteristic curve (AUC).

RESULTS

A total of 175 patients were retrospectively enrolled (142 for the training cohort and 33 for the validation one). 1896 radiomic feature were extracted, 91 of which showed significance (p < 0.05) at the univariate analysis. The radiomic model showing the highest predictive value combined the features calculated starting from the gray level co-occurrence-based features. This model achieved an AUC of 0.73 in the training set and 0.91 in the validation set.

CONCLUSIONS

The proposed radiomic model showed promising performances in predicting 2-year overall survival before NACRT. Nevertheless, the observed results should be tested in larger studies with consistent external validation cohorts, to confirm their potential clinical use.

Imaging to optimize gynecological radiation oncology

Gynecological cancers have particularly benefited from the increasing use of imaging to guide radiation treatment planning for both external beam radiation and brachytherapy. While the different gynecological cancers have varying use of imaging, certain trends predominate. CT represents an economical choice for evaluating initial disease extent or potential metastasis at follow-up, particularly for endometrial and ovarian cancers. F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT is particularly useful for assessing the initial disease extent and longer term treatment response of squamous predominant cancers, including cervical, vaginal, and vulvar cancers. With its excellent pelvic soft tissue discrimination, MRI provides the greatest assistance in evaluating the local extent of gynecological tumors, including initial evaluation for non-operative endometrial and vulvar cancer, and assessment before, after and during brachytherapy for cervix, locally recurrent endometrial, and primary vaginal cancers. With more limited availability of MRI, ultrasound can also help guide brachytherapy, particularly during procedures. The benefits of using imaging to better spare bone marrow or earlier assessment of treatment response are topics still being explored, in particular for cervical cancer. As imaging along with radiation oncology technologies continue to evolve and develop, such as with MRI-linacs and ultra high dose rate (FLASH) radiation, we may continue to see increasing use of imaging for advancing gynecological radiation oncology.

Preoperative magnetic resonance imaging predicts clinicopathological parameters and stages of endometrial carcinomas

BACKGROUND

We investigated the agreement and accuracy of preoperative magnetic resonance imaging (MRI) with postoperative pathological characteristics and stages of endometrial endometrioid carcinoma (EEC).

METHODS

We recruited 527 women with EEC who underwent staging surgery at a single medical institution. The preoperative MRI, stages, and clinical and pathological parameters, including myometrial invasion (MI), cervical invasion (CI), adnexal metastasis (AM), intra-abdominal metastasis, and pelvic and/or para-aortic nodal metastasis, were recorded and analyzed. The agreement and accuracy between the preoperative MRI findings and these parameters and stages were assessed.

RESULTS

The rate of the preoperative MRI-based clinical stage matching the postoperative surgical stage was 85.2% in International Federation of Gynecology and Obstetrics stage IA, 51.9% in stage IB, 35.5% in stage II, 5.3% in stage IIIA, 33.3% in stage IIIB, 28.6% in stage IIIC1, 64.3% in stage IIIC2, and 93.8% in stage IVB. The consistency between radiologists and pathologists was 80.5% for deep MI, 91.5% for cervical invasion, 92.2% for adnexal metastasis, 98.9% for intra-abdominal metastasis, and 87.5% and 92.2% for pelvic and para-aortic nodal metastases, respectively. The negative predictive value of intra-abdominal metastasis was the highest with 99.8%.

CONCLUSIONS

Preoperative MRI could be an excellent tool for routine preoperative assessment to predict pathological parameters and stages of EEC, especially in excluding intra-abdominal metastatic disease.

The feasibility of reduced field-of-view diffusion-weighted imaging in evaluating bladder invasion of uterine cervical cancer

OBJECTIVES

Uterine cervical cancer with bladder mucosal invasion is classified as FIGO stage IVA with poor prognosis. MRI can rule out the bladder invasion and skipping cystoscopy may be possible; however, high false-positive rate may be problematic. The purpose of this study is to evaluate the diagnostic performance of reduced field-of-view (FOV) diffusion-weighted imaging (DWI) in evaluating bladder mucosal invasion of cervical cancer.

METHODS

3T MRI including T2WI and reduced FOV DWI in 15 women with histologically proven cervical cancer (two stage IIIB, six stage IVA, seven stage IVB) were retrospectively evaluated compared with cystoscopic findings.

RESULTS

Cystoscopy revealed mucosal invasion in 13 of 15 cases. The border between the tumor and the bladder wall was unclear on T2WI and clear on reduced FOV DWI in all 15 cases. The diagnosis of mucosal invasion on reduced FOV DWI had a sensitivity of 100%, specificity of 50%, accuracy of 93%, PPV of 93%, and NPV of 100%.

CONCLUSIONS

Addition of reduced FOV DWI may improve the staging accuracy of MRI for cervical cancer in assessing the bladder mucosal invasion.

ADVANCES IN KNOWLEDGE

Reduced FOV DWI may improve the staging accuracy of cervical cancer in assessing bladder mucosal invasion with high NPV and PPV, which may be helpful for avoiding unnecessary cystoscopy.