What Is the Role of Imaging at Primary Diagnostic Work-Up in Uterine Cervical Cancer?

Nomogram based on MRI and clinical features to predict progression-free survival in patients with stage IIIC1r cervical squamous cell carcinoma: A two-center study

PURPOSE

To develop a nomogram based on MRI and clinical features to predict progression-free survival (PFS) of 2018 FIGO stage ⅢC1r cervical squamous cell carcinoma (CSCC).

METHODS

144 consecutive patients with stage ⅢC1r CSCC from two independent institutions were stratified into training cohort (from Institution 1, n=100) and independent validation cohort (from Institution 2, n=44). Univariate and multivariate Cox regression analyses of MRI and clinical features before treatment were performed to determine independent risk factors for PFS in training cohort. Nomogram was developed based on them. Concordance index (C-index), calibration curves, and receiver operating characteristic (ROC) analyses were performed to assess and validate the nomogram.

RESULTS

In training cohort, 2009 FIGO stage, maximum length of the primary tumor, short diameter and roundness index of the maximum metastatic lymph node were independent risk factors of PFS in patients with stage IIIC1r CSCC (all P-values < 0.05). Nomogram based on them to predict 1- and 3-year PFS achieved C-indexes of 0.835 (95% confidence interval (CI): 0.809-0.862) and 0.789 (95%CI: 0.683-0.895) in the training and validation cohorts, respectively. Areas under ROC curves for the nomogram to predict 1- and 3-year PFS were 0.891 (95%CI: 0.829-0.954), 0.921 (95%CI: 0.861-0.981) in training cohort, and 0.902 (95%CI: 0.803-0.999), 0.885 (95%CI: 0.778-0.992) in validation cohort, respectively. Calibration curves indicated the nomogram predictions were in good agreement with actual observations.

CONCLUSIONS

The nomogram based on MRI and clinical features has high accuracy and stability in predicting PFS of patients with stage IIIC1r CSCC.

Role of ultrasound in detection of lymph-node metastasis in gynecological cancer: systematic review and meta-analysis

OBJECTIVE

To assess the diagnostic performance of transvaginal sonography (TVS) for the preoperative evaluation of lymph-node metastasis in gynecological cancer.

METHODS

This was a systematic review and meta-analysis of studies published between January 1990 and May 2023 evaluating the role of ultrasound in detecting pelvic lymph-node metastasis (index test) in gynecological cancer, using histopathological analysis as the reference standard. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity, specificity and diagnostic odds ratio were estimated.

RESULTS

The literature search identified 2638 citations. Eight studies reporting on a total of 967 women were included. The mean prevalence of pelvic lymph-node metastasis was 24.2% (range, 14.0-65.6%). The risk of bias was low for most domains assessed. Pooled sensitivity, specificity and diagnostic odds ratio of TVS were 41% (95% CI, 26-58%), 98% (95% CI, 93-99%) and 32 (95% CI, 14-72), respectively. High heterogeneity was found between studies for both sensitivity and specificity.

CONCLUSION

TVS showed a high pooled specificity for the detection of pelvic lymph-node metastasis in gynecological cancer, but pooled sensitivity was low. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Case report: A case report of co-morbidity of cervical intraepithelial neoplasia III and urethral cancer associated with HPV16

In this report, we present a case of a woman with concurrent cervical intraepithelial neoplasia grade III (CIN III) and urethral cancer, both associated with HPV16 infection. This unique case was initially brought to attention due to postmenopausal vaginal bleeding, despite the absence of urological symptoms and negative tumor markers. An unexpected discovery of pelvic lymph node metastasis during a hysterectomy intended for CIN III highlighted the rare coexistence of these conditions, with urethral cancer also linked to HPV-16 within the urethral lesion. This case emphasizes the diagnostic challenges faced by HPV-related cervical lesions and the critical need for increased vigilance, even when urological symptoms are not apparent. The findings underline the potential complexity of HPV-associated lesions and advocate for comprehensive screening strategies to ensure the timely detection and management of such intricate cases.

Clinical Tools for Optimizing Therapeutic Decision-Making in Prostate Cancer: A Five-Year Retrospective Analysis

The effective staging of prostate cancer is essential for optimizing treatment and predicting outcomes. This study assessed the correlation between detailed preoperative diagnostic scores and postoperative outcomes to evaluate the accuracy of cancer restaging and its impact on treatment decisions and prognosis after prostatectomy. This retrospective study analyzed 133 prostate cancer patients who underwent prostatectomies at "Pius Brinzeu" Clinical Emergency Hospital in Timisoara over five years. Preoperative Gleason scores increased significantly across risk categories, from an average of 6.21 in low-risk patients to 7.57 in high-risk patients. This trend continued postoperatively, with scores rising from 7.04 to 8.33, respectively. The average increase in Gleason scores from preoperative to postoperative assessments was most pronounced in high-risk patients, at 0.76. Significant changes in clinical staging included increases in NCCN risk, where high-risk patients showed a 30% increase, and ISUP grade, with a 26.7% increase in the high-risk category. Notably, nodal status changes were also significant in high-risk patients, showing a 23.3% increase. The incidence of MRI-detected adenopathy was notably higher in the high-risk group (50%). Furthermore, there were significant correlations between the preoperative CAPRA score and postoperative ISUP grade (r = 0.261) and the preoperative PIRADS score and postoperative ISUP grade (r = 0.306). Similar observations were made between the preoperative and postoperative Gleason scores (r = 0.286) and the number of positive fragments (r = 0.227) with the postoperative ISUP grading. Furthermore, the preoperative CAPRA score was significantly correlated (r = 0.261) with the postoperative ISUP grading. Preoperative MRI findings, which included assessments of adenopathy and seminal vesicle invasion, were also significantly correlated (r = 0.218) with the postoperative pathological findings. Additionally, a significant correlation was found between the preoperative PIRADS score and postoperative ISUP grade (r = 0.306). In forecasting the aggressiveness and staging of prostate cancer following surgery, preoperative PSA levels showed an AUC of 0.631; the preoperative Gleason score had an AUC adjusted to 0.582, and the number of positive biopsy fragments indicated an AUC of 0.566. These results highlight the necessity of accurate and comprehensive preoperative assessments to better predict disease progression and refine treatment strategies.

Application value of artificial intelligence algorithm-based magnetic resonance multi-sequence imaging in staging diagnosis of cervical cancer

The aim of this research is to explore the application value of Deep residual network model (DRN) for deep learning-based multi-sequence magnetic resonance imaging (MRI) in the staging diagnosis of cervical cancer (CC). This research included 90 patients diagnosed with CC between August 2019 and May 2021 at the hospital. After undergoing MRI examination, the clinical staging and surgical pathological staging of patients were conducted. The research then evaluated the results of clinical staging and MRI staging to assess their diagnostic accuracy and correlation. In the staging diagnosis of CC, the feature enhancement layer was added to the DRN model, and the MRI imaging features of CC were used to enhance the image information. The precision, specificity, and sensitivity of the constructed model were analyzed, and then the accuracy of clinical diagnosis staging and MRI staging were compared. As the model constructed DRN in this research was compared with convolutional neural network (CNN) and the classic deep neural network visual geometry group (VGG), the precision was 67.7, 84.9, and 93.6%, respectively. The sensitivity was 70.4, 82.5, and 91.2%, while the specificity was 68.5, 83.8, and 92.2%, respectively. The precision, sensitivity, and specificity of the model were remarkably higher than those of CNN and VGG models (P < 0.05). As the clinical staging and MRI staging of CC were compared, the diagnostic accuracy of MRI was 100%, while that of clinical diagnosis was 83.7%, showing a significant difference between them (P < 0.05). Multi-sequence MRI under intelligent algorithm had a high diagnostic rate for CC staging, deserving a good clinical application value.

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.

Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer

Cervical cancer (CC) is a major global health problem with 570,000 new cases and 266,000 deaths annually. Prognosis is poor for advanced stage disease, and few effective treatments exist. Preoperative diagnostic imaging is common in high-income countries and MRI measured tumor size routinely guides treatment allocation of cervical cancer patients. Recently, the role of MRI radiomics has been recognized. However, its potential to independently predict survival and treatment response requires further clarification. This retrospective cohort study demonstrates how non-invasive, preoperative, MRI radiomic profiling may improve prognostication and tailoring of treatments and follow-ups for cervical cancer patients. By unsupervised clustering based on 293 radiomic features from 132 patients, we identify three distinct clusters comprising patients with significantly different risk profiles, also when adjusting for FIGO stage and age. By linking their radiomic profiles to genomic alterations, we identify putative treatment targets for the different patient clusters (e.g., immunotherapy, CDK4/6 and YAP-TEAD inhibitors and p53 pathway targeting treatments).

Cervical extracellular matrix hydrogel optimizes tumor heterogeneity of cervical squamous cell carcinoma organoids

Cervical cancer, primarily squamous cell carcinoma, is the most prevalent gynecologic malignancy. Organoids can mimic tumor development in vitro, but current Matrigel inaccurately replicates the tissue-specific microenvironment. This limitation compromises the accurate representation of tumor heterogeneity. We collected para-cancerous cervical tissues from patients diagnosed with cervical squamous cell carcinoma (CSCC) and prepared uterine cervix extracellular matrix (UCEM) hydrogels. Proteomic analysis of UCEM identified several tissue-specific signaling pathways including human papillomavirus, phosphatidylinositol 3-kinase-AKT, and extracellular matrix receptor. Secreted proteins like FLNA, MYH9, HSPA8, and EEF1A1 were present, indicating UCEM successfully maintained cervical proteins. UCEM provided a tailored microenvironment for CSCC organoids, enabling formation and growth while preserving tumorigenic potential. RNA sequencing showed UCEM-organoids exhibited greater similarity to native CSCC and reflected tumor heterogeneity by exhibiting CSCC-associated signaling pathways including virus protein-cytokine, nuclear factor κB, tumor necrosis factor, and oncogenes EGR1, FPR1, and IFI6. Moreover, UCEM-organoids developed chemotherapy resistance. Our research provides insights into advanced organoid technology through native matrix hydrogels.

Staging by imaging in gynecologic cancer and the role of ultrasound: an update of European joint consensus statements

In recent years the role of diagnostic imaging by pelvic ultrasound in the diagnosis and staging of gynecological cancers has been growing exponentially. Evidence from recent prospective multicenter studies has demonstrated high accuracy for pre-operative locoregional ultrasound staging in gynecological cancers. Therefore, in many leading gynecologic oncology units, ultrasound is implemented next to pelvic MRI as the first-line imaging modality for gynecological cancer. The work herein is a consensus statement on the role of pre-operative imaging by ultrasound and other imaging modalities in gynecological cancer, following European Society guidelines.

The Role of Imaging in Cervical Cancer Staging: ESGO/ESTRO/ESP Guidelines (Update 2023)

Following the European Society of Gynaecological Oncology (ESGO), the European Society for Radiotherapy and Oncology (ESTRO), and the European Society of Pathology (ESP) joint guidelines (2018) for the management of patients with cervical cancer, treatment decisions should be guided by modern imaging techniques. After five years (2023), an update of the ESGO-ESTRO-ESP recommendations was performed, further confirming this statement. Transvaginal/transrectal ultrasound (TRS/TVS) or pelvic magnetic resonance (MRI) enables tumor delineation and precise assessment of its local extent, including the evaluation of the depth of infiltration in the bladder- or rectal wall. Additionally, both techniques have very high specificity to confirm the presence of metastatic pelvic lymph nodes but fail to exclude them due to insufficient sensitivity to detect small-volume metastases, as in any other currently available imaging modality. In early-stage disease (T1a to T2a1, except T1b3) with negative lymph nodes on TVS/TRS or MRI, surgicopathological staging should be performed. In all other situations, contrast-enhanced computed tomography (CECT) or 18F-fluorodeoxyglucose positron emission tomography combined with CT (PET-CT) is recommended to assess extrapelvic spread. This paper aims to review the evidence supporting the implementation of diagnostic imaging with a focus on ultrasound at primary diagnostic workup of cervical cancer.

Radiomics analysis based on multiparametric magnetic resonance imaging for differentiating early stage of cervical cancer

Objective

To investigate the performance of multiparametric magnetic resonance imaging (MRI)-based radiomics models in differentiating early stage of cervical cancer (Stage I-IIa vs. IIb-IV).

Methods

One hundred patients with cervical cancer who underwent preoperative MRI between June 2020 and March 2022 were retrospectively enrolled. Training (n = 70) and testing cohorts (n = 30) were assigned by stratified random sampling. The clinical and pathological features, including age, histological subtypes, tumor grades, and node status, were compared between the two cohorts by t-test or chi-square test. Radiomics features were extracted from each volume of interest (VOI) on T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) maps. The data balance of the training cohort was resampled by synthesizing minority oversampling techniques. Subsequently, the adiomics signatures were constructed by the least absolute shrinkage and selection operator algorithm and minimum-redundancy maximum-relevance with 10-fold cross-validation. Logistic regression was applied to predict the cervical cancer stages (low [I-IIa]) and (high [IIb-IV] FIGO stages). The receiver operating characteristic curve (area under the curve [AUC]) and decision curve analysis were used to assess the performance of the radiomics model.

Results

The characteristics of age, histological subtypes, tumor grades, and node status were not significantly different between the low [I-IIa] and high [IIb-IV] FIGO stages (p > 0.05 for both the training and test cohorts). Three models based on T2WI, ADC maps, and the combined were developed based on six radiomics features from T2WI and three radiomics features from ADC maps, with AUCs of 0.855 (95% confidence interval [CI], 0.777-0.934) and 0.823 (95% CI, 0.727-0.919), 0.861 (95% CI, 0.785-0.936) and 0.81 (95% CI, 0.701-0.918), 0.934 (95% CI, 0.884-0.984) and 0.902 (95% CI, 0.832-0.972) in the training and test cohorts.

Conclusion

The radiomics models combined T2W and ADC maps had good predictive performance in differentiating the early stage from locally advanced cervical cancer.

Expanding Access to Computed Tomographic Staging and Three-Dimensional Intensity Modulated Radiotherapy for Cervical Cancer in Ghana

PURPOSE

To build capacity for improved treatment of locally advanced cervical cancer in Ghana, including computed tomography (CT) staging and intensity modulated radiotherapy (IMRT).

MATERIALS AND METHODS

Patients with histologically confirmed cervical cancer were prospectively staged with abdominopelvic CT and ultrasound and offered the opportunity to have IMRT instead of conventional two-dimensional radiotherapy. The development of an efficient, high-quality, and safe IMRT program was facilitated by investment in new technology and comprehensive training of the interdisciplinary radiotherapy team in collaboration with a North American center of excellence.

RESULTS

Of 215 patients with cervical cancer referred in 2022, 66% were able to afford CT scans and 26% were able to afford IMRT. Lymph node metastases were identified in 52% of patients by CT but in only 2% of patients by ultrasound. The use of CT resulted in 63% of patients being upstaged and changed treatment intent or radiation treatment volumes in 67% of patients. Patients who had IMRT experienced fewer acute side effects and were more likely to complete treatment as planned.

CONCLUSION

It is feasible to provide state-of the-art cancer treatment with CT staging and IMRT to patients with cervical cancer in low-resource settings and achieve meaningful improvements in outcomes. It requires a broad commitment by program leadership to invest in technology and staff training. Major challenges include balancing improved clinical care with reduced patient throughput when radiation treatment capacity is constrained, and with the additional cost in the absence of universal health coverage.

Enhancing the Accuracy of Lymph-Node-Metastasis Prediction in Gynecologic Malignancies Using Multimodal Federated Learning: Integrating CT, MRI, and PET/CT

Gynecological malignancies, particularly lymph node metastasis, have presented a diagnostic challenge, even with traditional imaging techniques such as CT, MRI, and PET/CT. This study was conceived to explore and, subsequently, to bridge this diagnostic gap through a more holistic and innovative approach. By developing a comprehensive framework that integrates both non-image data and detailed MRI image analyses, this study harnessed the capabilities of a multimodal federated-learning model. Employing a composite neural network within a federated-learning environment, this study adeptly merged diverse data sources to enhance prediction accuracy. This was further complemented by a sophisticated deep convolutional neural network with an enhanced U-NET architecture for meticulous MRI image processing. Traditional imaging yielded sensitivities ranging from 32.63% to 57.69%. In contrast, the federated-learning model, without incorporating image data, achieved an impressive sensitivity of approximately 0.9231, which soared to 0.9412 with the integration of MRI data. Such advancements underscore the significant potential of this approach, suggesting that federated learning, especially when combined with MRI assessment data, can revolutionize lymph-node-metastasis detection in gynecological malignancies. This paves the way for more precise patient care, potentially transforming the current diagnostic paradigm and resulting in improved patient outcomes.

Preoperative prediction of cervical cancer survival using a high-resolution MRI-based radiomics nomogram

BACKGROUND

Cervical cancer patients receiving radiotherapy and chemotherapy require accurate survival prediction methods. The objective of this study was to develop a prognostic analysis model based on a radiomics score to predict overall survival (OS) in cervical cancer patients.

METHODS

Predictive models were developed using data from 62 cervical cancer patients who underwent radical hysterectomy between June 2020 and June 2021. Radiological features were extracted from T2-weighted (T2W), T1-weighted (T1W), and diffusion-weighted (DW) magnetic resonance images prior to treatment. We obtained the radiomics score (rad-score) using least absolute shrinkage and selection operator (LASSO) regression and Cox's proportional hazard model. We divided the patients into low- and high-risk groups according to the critical rad-score value, and generated a nomogram incorporating radiological features. We evaluated the model's prediction performance using area under the receiver operating characteristic (ROC) curve (AUC) and classified the participants into high- and low-risk groups based on radiological characteristics.

RESULTS

The 62 patients were divided into high-risk (n = 43) and low-risk (n = 19) groups based on the rad-score. Four feature parameters were selected via dimensionality reduction, and the scores were calculated after modeling. The AUC values of ROC curves for prediction of 3- and 5-year OS using the model were 0.84 and 0.93, respectively.

CONCLUSION

Our nomogram incorporating a combination of radiological features demonstrated good performance in predicting cervical cancer OS. This study highlights the potential of radiomics analysis in improving survival prediction for cervical cancer patients. However, further studies on a larger scale and external validation cohorts are necessary to validate its potential clinical utility.

Identification of lymph node metastasis in pre-operation cervical cancer patients by weakly supervised deep learning from histopathological whole-slide biopsy images

BACKGROUND

Lymph node metastasis (LNM) significantly impacts the prognosis of individuals diagnosed with cervical cancer, as it is closely linked to disease recurrence and mortality, thereby impacting therapeutic schedule choices for patients. However, accurately predicting LNM prior to treatment remains challenging. Consequently, this study seeks to utilize digital pathological features extracted from histopathological slides of primary cervical cancer patients to preoperatively predict the presence of LNM.

METHODS

A deep learning (DL) model was trained using the Vision transformer (ViT) and recurrent neural network (RNN) frameworks to predict LNM. This prediction was based on the analysis of 554 histopathological whole-slide images (WSIs) obtained from Qilu Hospital of Shandong University. To validate the model's performance, an external test was conducted using 336 WSIs from four other hospitals. Additionally, the efficiency of the DL model was evaluated using 190 cervical biopsies WSIs in a prospective set.

RESULTS

In the internal test set, our DL model achieved an area under the curve (AUC) of 0.919, with sensitivity and specificity values of 0.923 and 0.905, respectively, and an accuracy (ACC) of 0.909. The performance of the DL model remained strong in the external test set. In the prospective cohort, the AUC was 0.91, and the ACC was 0.895. Additionally, the DL model exhibited higher accuracy compared to imaging examination in the evaluation of LNM. By utilizing the transformer visualization method, we generated a heatmap that illustrates the local pathological features in primary lesions relevant to LNM.

CONCLUSION

DL-based image analysis has demonstrated efficiency in predicting LNM in early operable cervical cancer through the utilization of biopsies WSI. This approach has the potential to enhance therapeutic decision-making for patients diagnosed with cervical cancer.

Visceral fat percentage for prediction of outcome in uterine cervical cancer

OBJECTIVE

The prognostic role of adiposity in uterine cervical cancer (CC) is largely unknown. Abdominal fat distribution may better reflect obesity than body mass index. This study aims to describe computed tomography (CT)-assessed abdominal fat distribution in relation to clinicopathologic characteristics, survival, and tumor gene expression in CC.

METHODS

The study included 316 CC patients diagnosed during 2004-2017 who had pre-treatment abdominal CT. CT-based 3D segmentation of total-, subcutaneous- and visceral abdominal fat volumes (TAV, SAV and VAV) allowed for calculation of visceral fat percentage (VAV% = VAV/TAV). Liver density (LD) and waist circumference (at L3/L4-level) were also measured. Associations between CT-derived adiposity markers, clinicopathologic characteristics and disease-specific survival (DSS) were explored. Gene set enrichment of primary tumors were examined in relation to fat distribution in a subset of 108 CC patients.

RESULTS

High TAV, VAV and VAV% and low LD were associated with higher age (≥44 yrs.; p ≤ 0.017) and high International Federation of Gynecology and Obstetrics (FIGO) (2018) stage (p ≤ 0.01). High VAV% was the only CT-marker predicting high-grade histology (p = 0.028), large tumor size (p = 0.016) and poor DSS (HR 1.07, p < 0.001). Patients with high VAV% had CC tumors that exhibited increased inflammatory signaling (false discovery rate [FDR] < 5%).

CONCLUSIONS

High VAV% is associated with high-risk clinical features and predicts reduced DSS in CC patients. Furthermore, patients with high VAV% had upregulated inflammatory tumor signaling, suggesting that the metabolic environment induced by visceral adiposity contributes to tumor progression in CC.

Imaging evaluation of para-aortic lymph nodes in cervical cancer

BACKGROUND

In recent years, much literature has reported the diagnostic value of computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET)-CT in para-aortic lymph node metastasis of cervical cancer.

PURPOSE

To compare and analyze the para-aortic lymph node presentations found in cervical cancer on different images in order to determine the best precise imaging method for identifying metastatic lymph nodes.

MATERIAL AND METHODS

PubMed, Web of Science, MEDLINE, and other databases were searched for the non-invasive detection of metastatic lymph nodes for a comprehensive comparison.

RESULTS

Positive lymph nodes on CT are significantly related to the following factors: short axis ≥10 mm; and round or central necrosis. Positive lymph nodes on MRI are significantly related to the following factors: short axis ≥8 mm; inhomogeneous signal intensity; morphology: round, irregular edge, extracapsular invasion, central necrosis, loss of lymph node structure, burrs, or lobes; and ADC value decreases, combined with local actuality. On PET-CT examination, when the short axis of the lymph node is >5 mm, the SUV is >2.5, or the FDG uptake is greater than that of the surrounding tissue, it is a metastatic lymph node.

CONCLUSION

In conclusion, different imaging techniques show metastatic lymph nodes in different ways. Combining the patient's medical history with the symptoms of the aforementioned lymph nodes, together with one or more imaging techniques, is important to diagnose para-aortic lymph nodes in cervical cancer.

Value of loop electrosurgical excision procedure conization and imaging for the diagnosis of papillary squamous cell carcinoma of the cervix

Background

Loop electrosurgical excision procedure (LEEP) conization and hysterectomy are performed for some patients with papillary squamous cell carcinoma (PSCC), whereas only hysterectomy is performed for others. We aimed to determine the optimal management for PSCC.

Methods

Patients diagnosed with PSCC by colposcopy-directed biopsy between June 2008 and January 2020 who underwent LEEP conization and hysterectomy or only hysterectomy at our hospital were enrolled. Results of cervical cytology, high-risk human papillomavirus testing, transvaginal sonography, pelvic magnetic resonance imaging, LEEP, hysterectomy, and pathology testing of colposcopy-directed biopsy samples were analyzed.

Results

A total of 379 women were diagnosed with PSCC by colposcopy-directed biopsy; 174 underwent LEEP before hysterectomy and 205 underwent only hysterectomy. Patients underwent and did not undergo LEEP were aged 47 ± 11 years and 52 ± 11 years, respectively. Among women who underwent LEEP, the agreement between LEEP and hysterectomy pathology was 85.1%. For women who underwent only hysterectomy, the agreement between preoperative clinical staging and pathological staging after hysterectomy was 82.4%. For patients with preoperative imaging indicative of malignancy, the accuracy of LEEP for diagnosing and staging PSCC was 88.5%, whereas for the hysterectomy-only group, it was 86.2%. For patients without malignancy detected with imaging, the accuracy of LEEP for diagnosing and staging PSCC was 81.6%; however, for those who did not undergo LEEP, it was 70.0%.

Conclusion

For women diagnosed with PSCC by colposcopy-directed biopsy, LEEP conization is necessary for an accurate diagnosis when imaging does not indicate cancer; however, LEEP is not necessary when imaging indicates cancer.

Value of non-coding RNAs to assess lymph node status in cervical cancer

Cervical cancer (CC) is the fourth cancer in women and is the leading cause of cancer death in 42 countries. Lymph node metastasis is a determinant prognostic factor, as underlined in the latest FIGO classification. However, assessment of lymph node status remains difficult, despite the progress of imaging such as PET-CT and MRI. In the specific setting of CC, all data underlined the need for new biomarkers easily available to assess lymph node status. Previous studies have underlined the potential value of ncRNA expression in gynecological cancers. In this review, we aimed to evaluate the contribution of ncRNAs in tissue and biofluid samples to determine lymph node status in CC with potential impact on both surgical and adjuvant therapies. In tissue samples, our analysis found that there are arguments to support the role of ncRNAs in physiopathology, differential diagnosis from normal tissue, preinvasive and invasive tumors. In biofluids, despite small studies especially concerning miRNAs expression, promising data opens up new avenue to establish a non-invasive signature for lymph node status as well as a tool to predict response to neo- and adjuvant therapies, thus improving management algorithm of patients with CC.

Association of Sialyl Tn antigen with cervical cancer lymph node status: An NRG oncology/GOG study

OBJECTIVE

Detection of lymph node metastases in cervical cancer patients is important for guiding treatment decisions, however accuracies of current detection methods are limited. We evaluated associations of abnormal glycosylation, represented by Tn and STn antigens on mucin (MUC) proteins, in primary tumor specimens with lymph node metastasis or recurrence of cervical cancer patients.

METHODS

Surgical specimens were prospectively collected from 139 patients with locally-advanced cervical cancer undergoing lymphadenectomy enrolled in a nation-wide clinical trial (NCT00460356). Of these patients, 133 had primary cervix tumor, 67 had pelvic lymph node (PLN) and 28 had para-aortic lymph node (PALN) specimens. Fixed tissue serial sections were immunohistochemically stained for Tn, STn, MUC1 or MUC4. Neuraminidase was used to validate Tn versus STn antibody specificity. Stain scores were compared with clinical characteristics.

RESULTS

Primary tumor STn expression above the median was associated with negative PLN status (p-value: 0.0387; odds ratio 0.439, 95% CI: 0.206 to 0.935). PLN had higher STn compared to primary tumor, while primary tumor had higher MUC1 compared to PALN, and MUC4 compared to PALN or PLN (p = 0.017, p = 0.011, p = 0.016 and p < 0.001, respectively). Tn and STn expression correlated in primary tumor, PALN, and PLN, Tn and MUC1 expression correlated in primary tumors only (Spearman correlation coefficient [r] = 0.301, r = 0.686, r = 0.603 and r = 0.249, respectively).

CONCLUSIONS

STn antigen expression in primary cervical tumors is a candidate biomarker for guiding treatment decisions and for mechanistic involvement in PLN metastases.

Amide Proton Transfer-Weighted Imaging Combined with ZOOMit Diffusion Kurtosis Imaging in Predicting Lymph Node Metastasis of Cervical Cancer

Background: The aim of this study is to investigate the feasibility of amide proton transfer-weighted (APTw) imaging combined with ZOOMit diffusion kurtosis imaging (DKI) in predicting lymph node metastasis (LNM) in cervical cancer (CC). Materials and Methods: Sixty-one participants with pathologically confirmed CC were included in this retrospective study. The APTw MRI and ZOOMit diffusion-weighted imaging (DWI) were acquired. The mean values of APTw and DKI parameters including mean kurtosis (MK) and mean diffusivity (MD) of the primary tumors were calculated. The parameters were compared between the LNM and non-LNM groups using the Student’s t-test or Mann–Whitney U test. Binary logistic regression analysis was performed to determine the association between the LNM status and the risk factors. The diagnostic performance of these quantitative parameters and their combinations for predicting the LNM was assessed with receiver operating characteristic (ROC) curve analysis. Results: Patients were divided into the LNM group (n = 17) and the non-LNM group (n = 44). The LNM group presented significantly higher APTw (3.7 ± 1.1% vs. 2.4 ± 1.0%, p < 0.001), MK (1.065 ± 0.185 vs. 0.909 ± 0.189, p = 0.005) and lower MD (0.989 ± 0.195 × 10−3 mm2/s vs. 1.193 ± 0.337 ×10−3 mm2/s, p = 0.035) than the non-LNM group. APTw was an independent predictor (OR = 3.115, p = 0.039) for evaluating the lymph node status through multivariate analysis. The area under the curve (AUC) of APTw (0.807) was higher than those of MK (AUC, 0.715) and MD (AUC, 0.675) for discriminating LNM from non-LNM, but the differences were not significant (all p > 0.05). Moreover, the combination of APTw, MK, and MD yielded the highest AUC (0.864), with the corresponding sensitivity of 76.5% and specificity of 88.6%. Conclusion: APTw and ZOOMit DKI parameters may serve as potential noninvasive biomarkers in predicting LNM of CC.

MR Imaging in Cervical Cancer

Cervical cancer remains a significant contributor to morbidity and mortality for women globally despite medical advances in preventative medicine and treatment. The 2018 Internal Federation of Gynecology and Obstetrics committee modified their original 2009 staging scheme to incorporate advanced imaging modalities, where available, to increase the accuracy of staging and to guide evolving treatments. Having a robust understanding of the newest staging iteration, its consequences on treatment pathways, and common imaging pitfalls will aid the radiologist in generating valuable and practical reports to optimize treatment strategies.

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.

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

Cervical cancer is the fourth most common cancer in women globally and the second most common cancer in Indian women, more common in lower socioeconomic strata. Improvement in survival and decrease in morbidity reflect the earlier detection with screening and imaging, as well as multifactorial multimodality therapy integrating surgery, and concurrent chemoradiation therapy providing superior therapeutic benefits. Imaging plays a vital role in assessing the extent of disease and staging of cervical cancer. The appropriateness criteria of a modality are different from its availability based on infrastructure, medical facilities, and resource status. Although in an ideal situation, magnetic resonance imaging (MRI) would be of greatest value in locoregional assessment of extent of disease and fluorodeoxyglucose positron emission tomography-computed tomography for distant staging; often, an ultrasonography, chest radiograph, and bone scans are utilized, with contrast-enhanced computed tomography representing a fair superior diagnostic accuracy, and can be reported as per the RECIST 1.1 criteria. MRI is also of good utility in the assessment of residual disease, predicting response and detecting small volume recurrence. MRI offers the highest diagnostic accuracy in determining parametrial invasion and hence surgical planning; so also, MRI-guided radiation planning helps in more accurate graded radiation dose planning in radiation therapy. Stage and therapy-based surveillance imaging should be encouraged and recommended.

Clinical Value of Serum miR-106a in the Diagnosis and Prognosis of Human Papillomavirus-Positive Cervical Cancer

INTRODUCTION

Cervical cancer (CC) is a prevailing malignant tumor in women, mainly caused by human papillomavirus (HPV) infection. This study investigated miR-106a expression in the serum of HPV-positive CC patients and estimated its value in diagnosis and prognosis.

METHODS

We enrolled 120 CC patients as study subjects, with another 80 healthy women as controls. Clinical baseline data and clinicopathological indexes including age, tumor size, differentiation degree, FIGO stage, lymph node metastasis, and squamous cell carcinoma antigen (SCC-Ag) were recorded. Serum miR-106a expression was measured using reverse transcription-quantitative polymerase chain reaction. Receiver operating characteristic curve was employed to estimate the efficacy of miR-106a in diagnosing CC or HPV-positive CC. Under a 5-year follow-up, patient survival was recorded, and the impact of miR-106a on overall survival rate was analyzed by the Kaplan-Meier method. The logistic regression model was used to analyze whether miR-106a was an independent prognostic factor for HPV infection in CC patients.

RESULTS

Serum miR-106a was upregulated in CC patients and the level >1.365 assisted the CC diagnosis. miR-106a expression in HPV-positive CC patients was elevated relative to HPV-negative CC patients, and serum miR-106a level >1.300 distinguishing HPV positive and HPV negative. HPV positivity was linked with tumor differentiation degree, FIGO stage, lymph node metastasis, and SCC-Ag in CC patients, but not with age and tumor size. High expression of miR-106a in HPV-positive CC patients increased the risk of poor prognosis, and miR-106a expression is an independent prognostic factor for HPV infection in CC patients.

CONCLUSION

High expression of miR-106a assists in the diagnosis of HPV-positive CC and predicts poor prognosis.

Recurrence risk stratification for locally advanced cervical cancer using multi-modality transformer network

Objectives

Recurrence risk evaluation is clinically significant for patients with locally advanced cervical cancer (LACC). We investigated the ability of transformer network in recurrence risk stratification of LACC based on computed tomography (CT) and magnetic resonance (MR) images.

Methods

A total of 104 patients with pathologically diagnosed LACC between July 2017 and December 2021 were enrolled in this study. All patients underwent CT and MR scanning, and their recurrence status was identified by the biopsy. We randomly divided patients into training cohort (48 cases, non-recurrence: recurrence = 37: 11), validation cohort (21 cases, non-recurrence: recurrence = 16: 5), and testing cohort (35 cases, non-recurrence: recurrence = 27: 8), upon which we extracted 1989, 882 and 315 patches for model's development, validation and evaluation, respectively. The transformer network consisted of three modality fusion modules to extract multi-modality and multi-scale information, and a fully-connected module to perform recurrence risk prediction. The model's prediction performance was assessed by six metrics, including the area under the receiver operating characteristic curve (AUC), accuracy, f1-score, sensitivity, specificity and precision. Univariate analysis with F-test and T-test were conducted for statistical analysis.

Results

The proposed transformer network is superior to conventional radiomics methods and other deep learning networks in both training, validation and testing cohorts. Particularly, in testing cohort, the transformer network achieved the highest AUC of 0.819 ± 0.038, while four conventional radiomics methods and two deep learning networks got the AUCs of 0.680 ± 0.050, 0.720 ± 0.068, 0.777 ± 0.048, 0.691 ± 0.103, 0.743 ± 0.022 and 0.733 ± 0.027, respectively.

Conclusions

The multi-modality transformer network showed promising performance in recurrence risk stratification of LACC and may be used as an effective tool to help clinicians make clinical decisions.

Greater increases in intratumoral apparent diffusion coefficients after chemoradiotherapy predict better overall survival of patients with cervical cancer

PURPOSE

To evaluate whether 1) the intratumoral apparent diffusion coefficients (ADCs) change during cervical cancer treatment and 2) the pretreatment ADC values or their change after treatment predict the treatment outcome or overall survival of patients with cervical cancer.

METHODS

We retrospectively enrolled 52 patients with inoperable cervical cancer treated with chemoradiotherapy, who had undergone diffusion weighted MRI before treatment and post external beam radiotherapy (EBRT) and concurrent chemotherapy. A subgroup of patients (n = 28) underwent altogether six consecutive diffusion weighted MRIs; 1) pretreatment, 2) post-EBRT and concurrent chemotherapy; 3-5) during image-guided brachytherapy (IGBT) and 6) after completing the whole treatment course. To assess interobserver and intertechnique reproducibility two observers independently measured the ADCs by drawing freehand a large region of interest (L-ROI) covering the whole tumor and three small ROIs (S-ROIs) in areas with most restricted diffusion.

RESULTS

Reproducibility was equally good for L-ROIs and S-ROIs. The pretreatment ADCs were higher in L-ROIs (883 mm2/s) than in S-ROIs (687 mm2/s, P < 0.001). The ADCs increased significantly between the pretreatment and post-EBRT scans (L-ROI: P < 0.001; S-ROI: P = 0.001). The ADCs remained significantly higher than pretreatment values during the whole IGBT. Using S-ROIs, greater increases in ADCs between pretreatment and post-EBRT MRI predicted better overall survival (P = 0.018).

CONCLUSION

ADC values significantly increase during cervical cancer treatment. Greater increases in ADC values between pretreatment and post-EBRT predicted better overall survival using S-ROIs. Standardized methods for timing and delineation of ADC measurements are advocated in future studies.

Cervical cancer in Cape Verde: reappraisal upon referral to a tertiary cancer centre

Background

Cervical cancer (CC) is the first cause of cancer-related deaths among Cape Verdean women. The absence of a national screening programme and a lack of dedicated cancer treatment facilities contribute to its high mortality rate. In an effort to improve the prognosis of these women, a health cooperation agreement was established between Portugal and Cape Verde (CV), allowing their evacuation to Portuguese hospitals. Our aim was to characterise CC among CV women, and to assess the response given to these patients in Instituto Português de Oncologia de Lisboa Francisco Gentil (IPOLFG), so that their treatment and follow-up protocols can be optimised and overall prognosis improved.

Methods

Retrospective evaluation of women diagnosed with CC in CV that underwent therapy in IPOLFG between 2013 and 2020. Risk factors, demographic and tumour characteristics, treatment and outcomes were reviewed.

Results

Fifty-eight patients were included. Squamous cell carcinoma was the most frequent (91.5%) histological type. HPV DNA was present in 25 out of 26 samples.The agreement rate between the pathology analysis performed in CV and in Portugal was high (87.9%); however, the agreement regarding the FIGO stage was low (15.5%). This may be explained by both the time interval between diagnosis and treatment (around 6 months) and by the absence of resources to accurately stage the disease in CV. In IPOLFG, 77.6% of patients received combined chemo-radiotherapy. Post-treatment follow-up varied widely, due to disease-related and bureaucratic issues. Eighteen patients developed cancer-related complications and/or cancer-related death. The survival rate and median overall survival (OS) in our cohort were of 89.7% and 73.2 months, respectively.

Conclusions

Although most women had advanced-stage disease, the OS in our cohort was better than what has been reported for other African countries, probably because state-of-the-art treatment, frequently not accessible in those countries, was offered to all patients.

Utility of the Diffusion Weighted Sequence in Gynecological Imaging: Review Article

Simple Summary

Diffusion weighted imaging (DWI) is a magnetic resonance imaging sequence with diverse clinical applications in malignant and nonmalignant gynecological conditions. It provides vital supplemental information in the diagnosis and management of various gynecological conditions. Radiologists should be aware of fundamental concepts, clinical applications and pitfalls of DWI. Additionally we briefly discuss potential scope of newer advanced techniques based on DWI including diffusion tensor imaging and diffusion-weighted whole-body imaging with background signal suppression.

Abstract

Functional imaging with diffusion-weighted imaging (DWI) is a complementary tool to conventional diagnostic magnetic resonance imaging sequences. It is being increasingly investigated to predict tumor response and assess tumor recurrence. We elucidate the specific technical modifications of DWI preferred for gynecological imaging, including the different b-values and planes for image acquisition. Additionally, we discuss the problems and potential pitfalls encountered during DWI interpretation and ways to overcome them. DWI has a wide range of clinical applications in malignant and non-malignant gynecological conditions. It provides supplemental information helpful in diagnosing and managing tubo-ovarian abscess, uterine fibroids, endometriosis, adnexal torsion, and dermoid. Similarly, DWI has diverse applications in gynecological oncology in diagnosis, staging, detection of recurrent disease, and tumor response assessment. Quantitative evaluation with apparent diffusion coefficient (ADC) measurement is being increasingly evaluated for correlation with various tumor parameters in managing gynecological malignancies aiding in preoperative treatment planning. Newer advanced DWI techniques of diffusion tensor imaging (DTI) and whole body DWI with background suppression (DWIBS) and their potential uses in pelvic nerve mapping, preoperative planning, and fertility-preserving surgeries are briefly discussed.

Bone Marrow Mesenchymal Stem Cells (BMSCs) with a Disintegrin and Metalloprotease 17 (ADAM17) Overexpression Increase Cervical Cancer Cell Proliferation and Migration Through Epidermal Growth Factor Receptor (EGFR)/Phosphatidylinositol 3-Kinase (PI3K)/Protein Kinase b (AKT) Signaling

ADAM-17 is a membrane-bound protease and highly expressed in multiple tumors. BMSCs carrying target genes are delivered to damaged sites. This study aimed to investigate the mechanism underlying BMSCs with ADAM-17 in cervical cancer (CC). BMSCs were transfected with ADAM-17 mimics and co-cultured with CC cells followed by analysis of cell proliferation and migration by MTT assay and scratch assay, ADAM-17 and target genes (LAMB3, Robol) level by Western blot and RT-qPCR. As the effectiveness of ADAM-17 transfection was confirmed by its increased level, the presence of empty vector rarely affected ADAM-17 expression and biological activities of CC cells compared to control group (p > 0.05). BMSCs with ADAM-17 overexpression increased CC cell proliferation and enhanced scratch healing rate (p < 0.05), accompanied with upregulated LAMB3 and Robol. The difference in LAMB3 and Robol expression between empty vector group and control group did not reach a significance. In conclsuion, this study elucidates that BMSCs with ADAM-17 overexpression promotes CC cell progression through up-regulation of LAMB3 and Robol and activation EGFR/PI3K/Akt signaling, providing a novel BMSC-based targeted therapy.

Diagnosis of Early Cervical Cancer with a Multimodal Magnetic Resonance Image under the Artificial Intelligence Algorithm

This research was conducted to explore the value of multimodal magnetic resonance imaging (MRI) based on the alternating direction algorithm in the diagnosis of early cervical cancer. 64 patients diagnosed with early cervical cancer clinicopathologically were included, and according to the examination methods, they were divided into A group with conventional multimodal MRI examination and B group with the multimodal MRI examination under the alternating direction algorithm. The diagnostic results of two types of multimodal MRI for early cervical cancer staging were compared with the results of clinicopathological examination to judge the application value in the early diagnosis of cervical cancer. The results showed that in the 6 randomly selected samples of early cervical cancer patients, the peak signal-to-noise ratio (PSNR) and structural similarity image measurement (SSIM) of multimodal MRI images under the alternating direction algorithm were significantly higher than those of conventional multimodal MRI images and the image reconstruction was clearer under this algorithm. By comparing MRI multimodal staging, statistical analysis showed that the staging accuracy of B group was 75%, while that of A group was only 59.38%. For the results of postoperative medical examinations, the examination consistency of B group was better than that of A group, with a statistically significant difference (P < 0.05). The area under the receiver operating characteristic (ROC) curve (AUC) of B group was larger than that of A group; thus, sensitivity was improved and misdiagnosis was reduced significantly. Multimodal MRI under the alternating direction algorithm was superior to conventional multimodal MRI examination in the diagnosis of early cervical cancer, as the lesions were displayed more clearly, which was conducive to the detection rate of small lesions and the staging accuracy. Therefore, it could be used as an ideal MRI method for the assistant diagnosis of cervical cancer staging.

MRI-derived radiomics analysis improves the noninvasive pretreatment identification of multimodality therapy candidates with early-stage cervical cancer

OBJECTIVES

To develop and validate a clinical-radiomics model that incorporates radiomics signatures and pretreatment clinicopathological parameters to identify multimodality therapy candidates among patients with early-stage cervical cancer.

METHODS

Between January 2017 and February 2021, 235 patients with IB1-IIA1 cervical cancer who underwent radical hysterectomy were enrolled and divided into training (n = 194, training:validation = 8:2) and testing (n = 41) sets according to surgical time. The radiomics features of each patient were extracted from preoperative sagittal T2-weighted images. Significance testing, Pearson correlation analysis, and Least Absolute Shrinkage and Selection Operator were used to select radiomic features associated with multimodality therapy administration. A clinical-radiomics model incorporating radiomics signature, age, 2018 Federation International of Gynecology and Obstetrics (FIGO) stage, menopausal status, and preoperative biopsy histological type was developed to identify multimodality therapy candidates. A clinical model and a clinical-conventional radiological model were also constructed. A nomogram and decision curve analysis were developed to facilitate clinical application.

RESULTS

The clinical-radiomics model showed good predictive performance, with an area under the curve, sensitivity, and specificity in the testing set of 0.885 (95% confidence interval: 0.781-0.989), 78.9%, and 81.8%, respectively. The AUC, sensitivity, and specificity of the clinical model and clinical-conventional radiological model were 0.751 (0.603-0.900), 63.2%, and 63.6%, 0.801 (0.661-0.942), 73.7%, and 68.2%, respectively. A decision curve analysis demonstrated that when the threshold probability was > 20%, the clinical-radiomics model or nomogram may be more advantageous than the treat all or treat-none strategy.

CONCLUSIONS

The clinical-radiomics model and nomogram can potentially identify multimodality therapy candidates in patients with early-stage cervical cancer.

KEY POINTS

• Pretreatment identification of multimodality therapy candidates among patients with early-stage cervical cancer helped to select the optimal primary treatment and reduce severe complication risk and costs. • The clinical-radiomics model achieved a better prediction performance compared with the clinical model and the clinical-conventional radiological model. • An easy-to-use nomogram exhibited good performance for individual preoperative prediction.

PET-CT versus MRI in the diagnosis of lymph node metastasis of cervical cancer: A meta-analysis

To compare the clinical application value of positron emission tomography-computed tomography (PET-CT) and magnetic resonance imaging (MRI) in the diagnosis of cervical cancer lymph node metastasis. We searched PubMed and other databases for the studies comparing the use of PET-CT and MRI for the diagnosis of cervical cancer lymph node metastasis up to January 20, 2021. We strictly followed the inclusion and exclusion criteria to screen the literature and extract the data. Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool was used for quality evaluation of included studies, and Revman 5.3 and Stata 15.0 software were used for evaluating heterogeneity, synthesize sensitivity (SEN), specificity (SPE), positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and the area under the curve (AUC) and comparing the pretest and posttest probabilities. Finally, 11 studies were included for meta-analysis. The synthesized results indicated that the SEN value of PET-CT was 0.65 (0.60 ~ 0.69) and SPE was 0.93 (0.91 ~ 0.94), and the SEN value of MRI was 0.58 (0.54 ~ 0.63) and SPE was 0.91 (0.90 ~ 0.92). AUC of PET-CT was 0.824, which was significantly higher than that of MRI (AUC = 0.702; p < .05). The subgroup analysis showed that the AUC value of the study based on study design and use of blinding methods was not statistically significant (all p > .05). There was no obvious publication bias in the synthesized analysis of the diagnostic value of PET-CT and MRI (all p > .05). HIGHLIGHTS: To compare positron emission tomography-computed tomography (PET-CT) and magnetic resonance imaging (MRI) in diagnosis of cervical cancer lymph node metastasis. Synthesize sensitivity value of PET-CT was comparable with that of MRI. Area under the curve of PET-CT was significantly higher than that of MRI. There was no obvious publication bias in synthesized analysis.

Interobserver agreement and prognostic impact for MRI-based 2018 FIGO staging parameters in uterine cervical cancer

OBJECTIVES

To evaluate the interobserver agreement for MRI-based 2018 International Federation of Gynecology and Obstetrics (FIGO) staging parameters in patients with cervical cancer and assess the prognostic value of these MRI parameters in relation to other clinicopathological markers.

METHODS

This retrospective study included 416 women with histologically confirmed cervical cancer who underwent pretreatment pelvic MRI from May 2002 to December 2017. Three radiologists independently recorded MRI-derived staging parameters incorporated in the 2018 FIGO staging system. Kappa coefficients (κ) for interobserver agreement were calculated. The predictive and prognostic values of the MRI parameters were explored using ROC analyses and Kaplan-Meier with log-rank tests, and analyzed in relation to clinicopathological patient characteristics.

RESULTS

Overall agreement was substantial for the staging parameters: tumor size > 2 cm (κ = 0.80), tumor size > 4 cm (κ = 0.76), tumor size categories (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) (κ = 0.78), parametrial invasion (κ = 0.63), vaginal invasion (κ = 0.61), and enlarged lymph nodes (κ = 0.63). Higher MRI-derived tumor size category (≤ 2 cm; > 2 and ≤ 4 cm; > 4 cm) was associated with a stepwise reduction in survival (p ≤ 0.001 for all). Tumor size > 4 cm and parametrial invasion at MRI were associated with aggressive clinicopathological features, and the incorporation of these MRI-based staging parameters improved risk stratification when compared to corresponding clinical assessments alone.

CONCLUSION

The interobserver agreement for central MRI-derived 2018 FIGO staging parameters was substantial. MRI improved the identification of patients with aggressive clinicopathological features and poor survival, demonstrating the potential impact of MRI enabling better prognostication and treatment tailoring in cervical cancer.

KEY POINTS

• The overall interobserver agreement was substantial (κ values 0.61-0.80) for central MRI staging parameters in the 2018 FIGO system. • Higher MRI-derived tumor size category was linked to a stepwise reduction in survival (p ≤ 0.001 for all). • MRI-derived tumor size > 4 cm and parametrial invasion were associated with aggressive clinicopathological features, and the incorporation of these MRI-derived staging parameters improved risk stratification when compared to clinical assessments alone.

Correlation of clinical staging and MRI staging for cervical cancer

Background

Cervical cancer is a major public health problem for women. Accurate staging may lead to proper management of cervical cancer. We retrospectively reviewed all patients with cervical cancer who underwent pre-treatment MRI between January 2009 and December 2018 and analyzed the correlation between the clinical staging and MRI staging.

Results

Correlation of overall clinical and MRI staging by percent agreement is moderate (73.9%), but the kappa coefficient showed a slight correlation. The correlation of clinical and MRI findings in the vaginal invasion, pelvic sidewall invasion, adjacent pelvic organ invasion, and spreading to distant organ also showed moderate-to-strong correlation by percent agreement (ranging from 67.6 to 91.9%) but slight correlation between clinical and MRI examinations by kappa or weighted kappa coefficient (K = 0.000–0.128w).

Conclusion

In patients with cervical cancer, pretreatment MRI provides higher spatial soft tissue resolution which can define pelvic tumor extent, including a more accurate assessment of tumor size (due to multiplanar evaluation), parametrial invasion, pelvic sidewall invasion, and adjacent pelvic organ invasion. This could potentially lead to a reduction in staging morbidity by invasive investigation such as cystoscopy and proctoscopy.

Prognostic Value of Pretherapeutic Primary Tumor MTV from [18F]FDG PET in Radically Treated Cervical Cancer Patients

The aim of this study was to assess the usefulness of pretherapeutic primary tumor metabolic tumor volume (MTV) in the prognosis of radically treated cervical cancer patients. Retrospective, single-centre analysis was performed on a group of 508 cervical cancer patients. All patients underwent a pretreatment [¹⁸F]FDG PET/CT study for the assessment of the disease stage. Several PET-derived parameters—namely, maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), total lesion glycolysis (TLG) and MTV, as well as the clinical parameters, were analysed in terms of the overall survival (OS), event-free survival (EFS), locoregional control (LRC) and freedom from distant metastases (FFDM). Hyperthermia and brachytherapy were prognostic for EFS, OS, and LRC.FIGO stage > II showed a significant effect on EFS, OS, and FFDM. Moreover, hysterectomy was prognostic for OS and histology was prognostic for FFDM. From the PET-derived parameters only MTV of the primary tumor had a significant influence on OS (cutoff point: >12.7 mL, HR: 2.8, 1.75–4.48 95% CI, p < 0.001), LRC (cutoff point: >13.7 mL, HR 2.82, 1.42–5.61 95% CI, p = 0.003), EFS (cutoff point: >10.4 mL, HR: 2.57, 1.67–3.97 95% CI, p < 0.001) and FFDM (cutoff point: >10.4 mL, HR: 5.04, 1.82–13.99 95% CI, p = 0.002). Pretreatment MTV from the primary tumor is the only independent prognostic parameter in OS, LRC, EFS, and FFDM in radically treated cervical cancer patients and should be used in clinical practice in assessing prognosis in these patients.

Useful MRI Findings for Minimally Invasive Surgery for Early Cervical Cancer

Simple Summary

Radical hysterectomy and lymph node dissection are extensive procedures with severe post-operative morbidities and should be avoided on patients with low risk of recurrence. Still, due to lack of good prognostic tools, radical surgery is performed on most patients with early stage cervical cancer, leading to overtreatment and unnecessary morbidities. The recent International Federation of Gynecology and Obstetrics (FIGO) staging system accepts the use of magnetic resonance imaging (MRI) in addition to physical examination. Currently, 3 Tesla (3T) MRI is available widely and, due to its high soft tissue contrast, can provide more useful information on precise estimation of tumor size and metastasis than can physical examination in patients with cervical cancer. Therefore, this imaging modality can help gynecologic oncologists to determine whether minimally invasive surgery is necessary and can be used for early detection of small recurrent cancers.

Abstract

According to the recent International Federation of Gynecology and Obstetrics (FIGO) staging system, Stage III cervical cancer indicates pelvic or paraaortic lymph node metastasis. Accordingly, the new FIGO stage accepts imaging modalities, such as MRI, as part of the FIGO 2018 updated staging. Magnetic resonance imaging (MRI) is the best imaging modality to estimate the size or volume of uterine cancer because of its excellent soft tissue contrast. As a result, MRI is being used increasingly to determine treatment options and follow-up for cervical cancer patients. Increasing availability of cancer screening and vaccination have improved early detection of cervical cancer. However, the incidence of early cervical cancers has increased compared to that of advanced cervical cancer. A few studies have investigated if MRI findings are useful in management of early cervical cancer. MRI can precisely predict tumor burden, allowing conization, trachelectomy, and simple hysterectomy to be considered as minimally invasive treatment options for early cervical cancer. This imaging modality also can be used to determine whether there is recurrent cancer following minimally invasive treatments. The purpose of this review is to highlight useful MRI features for managing women with early cervical cancer.

The Diagnosis of Perineural Invasion: A Crucial Factor in Novel Algorithm of Coexistence of Conventional and Nerve-Sparing Radical Hysterectomy

Nerve-sparing radical hysterectomy (NSRH) was introduced to mitigate adverse effects associated with conventional radical hysterectomy (CRH) in cervical cancer. However, the introduction of NSRH was compromised by possible existence of perineural invasion (PNI). Additionally, the coexistence of NSRH and CRH is currently the fact. The aim of the study was to review the literature and attempt to construct a novel and preliminary PNI diagnostic algorithm that would establish the coexistence of NSRH and CRH in one system of early-stage cervical cancer (ESCC) surgical treatment. This algorithm takes into account the PNI risk factors and current and future diagnostic methods such as imaging and biopsy.

The role of lymph nodes in cervical cancer: incidence and identification of lymph node metastases-a literature review

Correct identification of patients with lymph node metastasis from cervical cancer prior to treatment is of great importance, because it allows more tailored therapy. Patients may be spared unnecessary surgery or extended field radiotherapy if the nodal status can be predicted correctly. This review captures the existing knowledge on the identification of lymph node metastases in cervical cancer. The risk of nodal metastases increases per 2009 FIGO stage, with incidences in the pelvic region ranging from 2% (stage IA2) to 14-36% (IB), 38-51% (IIA) and 47% (IIB); and in the para-aortic region ranging from 2 to 5% (stage IB), 10-20% (IIA), 9% (IIB), 13-30% (III) and 50% (IV). In addition, age, tumor size, lymph vascular space invasion, parametrial invasion, depth of stromal invasion, histological type, and histological grade are reported to be independent prognostic factors for the risk of nodal metastases. Furthermore, biomarkers can contribute to predict a patient's nodal status, of which the squamous cell carcinoma antigen (SCC-Ag) is currently the most widely used in squamous cell cervical cancer. Still, pre-treatment lymph node assessment is primarily performed by imaging, of which diffusion-weighted magnetic resonance imaging has the highest sensitivity and 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission computed tomography the highest specificity. Imaging results can be combined with clinical parameters in nomograms to increase the accuracy of predicting positives nodes. Despite all the progress regarding pre-treatment prediction of lymph node metastases in cervical cancer in recent years, prediction rates are not robust enough to safely abandon surgical staging of the pelvic or para-aortic region yet.

[The Value of MRI in Early Cervical Cancer Staging with Vaginal Filling of Ultrasound Gel]

OBJECTIVE

To investigate the value of MRI after ultrasonic gel vagina filling in the staging of early-stage cervical cancer.

METHODS

A total of 158 patients with cervical cancer who underwent MRI examination after their cervical cancer diagnosis was confirmed by cervical biopsy were prospectively enrolled. Routine MRI examination was performed first, followed by another MRI examination after vaginal filling with ultrasound gel. Two physicians used a double-blind method to determine the staging of cervical cancer based on the MRI images before and after vaginal filling of ultrasound gel. Results of the postoperative pathology analysis were used as the golden standard. The positive predictive value and negative predictive value for stage Ⅱa cases of the two examinations of the same patient were compared, and the sensitivity, specificity and accuracy in identifying stage Ⅱa cervical cancer were compared.

RESULTS

Two physicians used the double blind method to determine the staging of cervical cancer based on conventional MRI images, achieving moderate consistency ( κ=0.680). However, for the staging of cervical cancer with MRI images after vaginal filling of ultrasound gel, the two physicians achieved highly consistent results ( κ=0.932). Regarding identifying stage Ⅱa cervical cancer, the positive predictive value of conventional MRI was 66.67%, the negative predictive value was 76.74%, and the sensitivity, specificity and accuracy were 70.59%, 73.33% and 72.15%, respectively. The positive predictive value of MRI after vaginal filling of ultrasound gel was 90.91%, the negative predictive value was 91.3%, and the sensitivity, specificity and accuracy were 88.24%, 93.33% and 91.14%, respectively. The sensitivity, specificity and accuracy of the two methods were compared and the difference was statistical significant ( P<0.05).

CONCLUSION

MRI examination after ultrasound gel vaginal filling has better diagnostic value for identifying stage Ⅱa cervical cancer. The method is simple and easy to do, and can be used in routine MRI examination of cervical cancer.

EANM/SNMMI practice guideline for [18F]FDG PET/CT external beam radiotherapy treatment planning in uterine cervical cancer v1.0

PURPOSE

The aim of this EANM / SNMMI Practice Guideline with ESTRO endorsement is to provide general information and specific considerations about [18F]FDG PET/CT in advanced uterine cervical cancer for external beam radiotherapy planning with emphasis on staging and target definition, mostly in FIGO stages IB3-IVA and IVB, treated with curative intention.

METHODS

Guidelines from related fields, relevant literature and leading experts have been consulted during the development of this guideline. As this field is rapidly evolving, this guideline cannot be seen as definitive, nor is it a summary of all existing protocols. Local variations should be taken into consideration when applying this guideline.

CONCLUSION

The background, common clinical indications, qualifications and responsibilities of personnel, procedure / specifications of the examination, documentation / reporting and equipment specifications, quality control and radiation safety in imaging is discussed with an emphasis on the multidisciplinary approach.

Optimal treatment in locally advanced cervical cancer

Introduction: Locally advanced cervical cancer (LACC) (International Federation of Gynecology and Obstetrics (FIGO) 2009/2018 - stages IB2-IVA/IB3-IVA, respectively) is treated using a multimodal approach that includes chemoradiotherapy followed by brachytherapy.Areas covered: This review provides an overview of the progress made over the past decade in the treatment of LACC. Prognostic factors, FIGO classification and the role of imaging staging will be discussed. Efficacy of external-beam radiotherapy, brachytherapy and chemotherapy will be detailed. Indications for para-aortic staging lymphadenectomy and adjuvant hysterectomy, as well as follow-up and special population, will be covered.Expert opinion: The initial workup is one of the most crucial steps in the optimal care of patients, which should be realized by a multidisciplinary expert team. With the implementation of modern conformal radiotherapy techniques, the local control rate has been optimized. Nevertheless, 40% of patients experience recurrence with distant metastasis and a dismal prognosis. Currently, a clear benefit of neo- and adjuvant chemotherapy has not been established. The future likely involves (1) improved selection of patients for whom treatment intensification is justified, (2) a combination of new drugs with chemoradiation that are currently being tested in trials, and (3) the development of tailored treatment based on molecular characteristics.

Treatment Outcome and Prognosis Factors of FIGO 2018 Stage III Cervical Cancer Patients Treated with Definitive Concurrent Chemoradiation in Vietnam

Objective:

This study aimed to analyze the treatment outcome and toxicities, along with prognosis factors of patients with FIGO 2018 stage III cervical cancer treated with definitive concurrent chemoradiation.

Methods:

A total of 83 stage III cervical cancer patients with good performance status (ECOG PS 0, 1) were treated with three-dimensional conformal radiation therapy (3D-CRT) combined with chemotherapy (weekly cisplatin), followed by high-dose-rate (HDR) brachytherapy between January 2017 and March 2019 at Vietnam National Cancer hospital. Treatment outcomes and prognosis factors were assessed along with acute and late toxicities.

Results:

The 3-year DFS was 67.8% and 3-year OS was 80.3%. On multivariate analyses, short axis of pelvic lymph node diameter of ≥ 15mm, invasion of the lower third of vagina and para-aortic lymph node metastasis were identified as adverse prognostic factors for DFS. The cumulative incidence rate of gastrointestinal and genitourinary toxicity (≥ grade 2) at the 3-year follow-up were 29.6% and 11.6%, respectively.

Conclusions:

3D CRT and HDR brachytherapy with concurrent chemotherapy is an effective treatment, with acceptable toxicity for FIGO 2018 stage III cervical cancer in Vietnam.

Optimisation and evaluation of the random forest model in the efficacy prediction of chemoradiotherapy for advanced cervical cancer based on radiomics signature from high-resolution T2 weighted images

PURPOSE

Our objective was to establish a random forest model and to evaluate its predictive capability of the treatment effect of neoadjuvant chemotherapy-radiation therapy.

METHODS

This retrospective study included 82 patients with locally advanced cervical cancer who underwent scanning from March 2013 to May 2018. The random forest model was established and optimised based on the open source toolkit scikit-learn. Byoptimising of the number of decision trees in the random forest, the criteria for selecting the final partition index and the minimum number of samples partitioned by each node, the performance of random forest in the prediction of the treatment effect of neoadjuvant chemotherapy-radiation therapy on advanced cervical cancer (> IIb) was evaluated.

RESULTS

The number of decision trees in the random forests influenced the model performance. When the number of decision trees was set to 10, 25, 40, 55, 70, 85 and 100, the performance of random forest model exhibited an increasing trend first and then a decreasing one. The criteria for the selection of final partition index showed significant effects on the generation of decision trees. The Gini index demonstrated a better effect compared with information gain index. The area under the receiver operating curve for Gini index attained a value of 0.917.

CONCLUSION

The random forest model showed potential in predicting the treatment effect of neoadjuvant chemotherapy-radiation therapy based on high-resolution T2WIs for advanced cervical cancer (> IIb).

Updated applications of Ultrasound in Uterine Cervical Cancer

Cervical cancer is a common gynecologic malignancy worldwide. It is the fourth for both incidence and mortality. For cervical cancer, imaging and pathology assessments are incorporated in the revised 2018 Federation of Gynecology and Obstetrics (FIGO) staging system. Uses of imaging techniques for the pre-treatment work-up of cervical cancer have been increasing. Among imaging techniques for the evaluation of cervical cancer, ultrasound is cheaper, faster and widely available than other imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). Advanced technique in ultrasound, such as three-dimension (3D) ultrasound and color Doppler, have improved the clinical application of ultrasound in cervical cancer. Ultrasound may provide highly accurate information on detecting tumor presence and evaluating local tumor extent if performed by ultrasound-trained gynecologists; the experience of readers is also critical for correct pretreatment staging and assessment of response to treatment. Sonographic images could be useful to predict response of neoadjuvant chemotherapy, radiotherapy, chemotherapy and concurrent chemoradiotherapy in patients with cervical cancer. This review article attempted to present the most updated specific applications of ultrasound in cervical cancer.

An MRI-Based Radiomic Prognostic Index Predicts Poor Outcome and Specific Genetic Alterations in Endometrial Cancer

Integrative tumor characterization linking radiomic profiles to corresponding gene expression profiles has the potential to identify specific genetic alterations based on non-invasive radiomic profiling in cancer. The aim of this study was to develop and validate a radiomic prognostic index (RPI) based on preoperative magnetic resonance imaging (MRI) and assess possible associations between the RPI and gene expression profiles in endometrial cancer patients. Tumor texture features were extracted from preoperative 2D MRI in 177 endometrial cancer patients. The RPI was developed using least absolute shrinkage and selection operator (LASSO) Cox regression in a study cohort (n = 95) and validated in an MRI validation cohort (n = 82). Transcriptional alterations associated with the RPI were investigated in the study cohort. Potential prognostic markers were further explored for validation in an mRNA validation cohort (n = 161). The RPI included four tumor texture features, and a high RPI was significantly associated with poor disease-specific survival in both the study cohort (p < 0.001) and the MRI validation cohort (p = 0.030). The association between RPI and gene expression profiles revealed 46 significantly differentially expressed genes in patients with a high RPI versus a low RPI (p < 0.001). The most differentially expressed genes, COMP and DMBT1, were significantly associated with disease-specific survival in both the study cohort and the mRNA validation cohort. In conclusion, a high RPI score predicts poor outcome and is associated with specific gene expression profiles in endometrial cancer patients. The promising link between radiomic tumor profiles and molecular alterations may aid in developing refined prognostication and targeted treatment strategies in endometrial cancer.

Imaging modalities in fertility preservation in patients with gynecologic cancers

Fertility preservation is an integral component of clinical decision-making and treatment design. However, the selection criteria on imaging for patients eligible for fertility preservation is still unclear. The present review aimed to summarize the main findings reported in both the literature and international guidelines on the role of imaging in the selection of patients for fertility preservation. A search strategy was developed and applied to PubMed, Scopus, Web of Science, and EMBASE to identify previous citations reporting imaging and fertility preservation in patients with gynecological cancer. We also retrieved the published guidelines on the eligibility criteria for fertility-sparing treatment of gynecological neoplasms. A description of the internal multidisciplinary guidelines, clinically in use in our institution, is provided with representative clinical cases. The literature review revealed 1291 articles and 18 of these were selected for the analysis. Both ultrasound and MRI represented the primary imaging methods for selecting patients for fertility preservation in cervical and endometrial cancers. Eligibility criteria of fertility-sparing management in patients with cervical cancer were: tumor size <2 cm, tumor distance from the internal os >1 cm, and no parametrium invasion. For patients with endometrial cancer, these included no myometrial and cervical stroma invasion. Both ultrasound and MRI play a key role in characterizing adnexal masses. These modalities provide a useful tool in identifying small ovarian lesions, thus key in the surveillance of patients after fertility sparing surgery. However, efficacy in excluding disease beyond the ovary remains limited. This review provides an update of the literature and schematic outline for the counseling and management of patients with the desire for fertility preservation.