Sonographic, Demographic, and Clinical Characteristics of Pre- and Postmenopausal Women with Endometrial Cancer; Results from a Post Hoc Analysis of the IETA4 (International Endometrial Tumor Analysis) Multicenter Cohort

In this study, we conducted a comparative analysis of demographic, histopathological, and sonographic characteristics between pre- and postmenopausal women diagnosed with endometrial cancer, while also examining sonographic and anthropometric features in 'low' and 'intermediate/high-risk' cases, stratified by menopausal status. Our analysis, based on data from the International Endometrial Tumor Analysis (IETA) 4 cohort comprising 1538 women (161 premenopausal, 1377 postmenopausal) with biopsy-confirmed endometrial cancer, revealed that premenopausal women, compared to their postmenopausal counterparts, exhibited lower parity (median 1, IQR 0-2 vs. 1, IQR 1-2, p = 0.001), a higher family history of colon cancer (16% vs. 7%, p = 0.001), and smaller waist circumferences (median 92 cm, IQR 82-108 cm vs. 98 cm, IQR 87-112 cm, p = 0.002). Premenopausal women more often had a regular endometrial-myometrial border (39% vs. 23%, p < 0.001), a visible endometrial midline (23% vs. 11%, p < 0.001), and undefined tumor (73% vs. 84%, p = 0.001). Notably, despite experiencing a longer duration of abnormal uterine bleeding (median 5 months, IQR 3-12 vs. 3 months, 2-6, p < 0.001), premenopausal women more often had 'low' risk disease (78% vs. 46%, p < 0.001). Among sonographic and anthropometric features, only an irregular endometrial-myometrial border was associated with 'intermediate/high' risk in premenopausal women. Conversely, in postmenopausal women, multiple features correlated with 'intermediate/high' risk disease. Our findings emphasize the importance of considering menopausal status when evaluating sonographic features in women with endometrial cancer.

Vaginosonography versus MRI in Pre-Treatment Evaluation of Early-Stage Cervical Cancer: An Old Tool for a New Precision Approach?

This study aims to analyze the sensitivity of vaginosonography (VGS) and magnetic resonance imaging (MRI) in the preoperative local evaluation of early-stage cervical cancers and to assess their accuracy in the detection of tumors, size of the lesions and stromal invasion by comparing them with the final histopathology report. This single-center study included 56 consecutive patients with cervical cancer who underwent VGS and MRI from November 2012 to January 2021. VGS significantly overestimated the lesion size by 2.7 mm (p = 0.002), and MRI underestimated it by 1.9 mm (p = 0.11). Both MRI and VGS had a good concordance with the pathology report (Cohen’s kappa of 0.73 and 0.81, respectively). However, MRI had a false-negative rate (38.1%) that was greater than VGS (0%) in cases of cervical tumor size <2 cm. We found a good concordance between histology and VGS in the stromal infiltration assessment, with 89% sensitivity (95% CI 0.44−0.83) and 89% specificity (95% CI 0.52−0.86). VGS is a simple, inexpensive, widely available, and fast execution method that can complement ultrasound in particular cases and show a good correlation with MRI in the assessment of tumor dimensions, with a better performance in detecting small tumors (<2 cm).

The Potential Impact of High-Risk Human Papillomavirus-Negative Cervical Intraepithelial Neoplasia 2+ on Primary Human Papillomavirus Screening

OBJECTIVES

To investigate the prevalence of high-risk human papillomavirus (HPV)-negative cervical intraepithelial neoplasia (CIN) and invasive cervical carcinoma (ICC) and to analyze the distribution of other genotypes in this subset.

METHODS

In total, 431 women who underwent excisional surgical treatment for CIN or ICC at the European Institute of Oncology, Milan, Italy, from January 2016 to December 2017 were retrospectively analyzed. The Linear Array HPV genotyping test (Roche Diagnostics) was performed on a postaliquot from high-risk-HPV-negative liquid-based cervical specimens, when available. Patient characteristics and the prevalence of high-risk-HPV-negative CIN grade 2 or worse (CIN2+) were tabulated. We used t tests to compare age between high-risk-HPV-positive and high-risk-HPV-negative patients.

RESULTS

Overall, 8.9% of CIN2+ and 7.5% of ICC cases were high-risk HPV negative. There was no age difference between high-risk-HPV-negative CIN2+ women (mean [SD], 41.3 [8.7] years) and high-risk-HPV-positive women (mean [SD], 39.5 [9.0] years) (P = .28). The Linear Array result was available in 22 cases. Most high-risk-HPV-negative patients were positive for a single other genotype infection (32.6%). HPV 73 was the most prevalent genotype, followed by HPV 53 and HPV 84. HPV 26 was detected in 1 case of ICC.

CONCLUSIONS

Our results showed a not-negligible proportion of high-risk-HPV-negative CIN2+, suggesting that cotesting would not miss these cases.

Comparison between model-predicted tumor oxygenation dynamics and vascular-/flow-related Doppler indices

PURPOSE

Mathematical modeling is a powerful and flexible method to investigate complex phenomena. It discloses the possibility of reproducing expensive as well as invasive experiments in a safe environment with limited costs. This makes it suitable to mimic tumor evolution and response to radiotherapy although the reliability of the results remains an issue. Complexity reduction is therefore a critical aspect in order to be able to compare model outcomes to clinical data. Among the factors affecting treatment efficacy, tumor oxygenation is known to play a key role in radiotherapy response. In this work, we aim at relating the oxygenation dynamics, predicted by a macroscale model trained on tumor volumetric data of uterine cervical cancer patients, to vascularization and blood flux indices assessed on Ultrasound Doppler images.

METHODS

We propose a macroscale model of tumor evolution based on three dynamics, namely active portion, necrotic portion, and oxygenation. The model parameters were assessed on the volume size of seven cervical cancer patients administered with 28 fractions of intensity modulated radiation therapy (IMRT) (1.8 Gy/fraction). For each patient, five Doppler ultrasound tests were acquired before, during, and after the treatment. The lesion was manually contoured by an expert physician using 4D View^® (General Electric Company - Fairfield, Connecticut, United States), which automatically provided the overall tumor volume size along with three vascularization and/or blood flow indices. Volume data only were fed to the model for training purpose, while the predicted oxygenation was compared a posteriori to the measured Doppler indices.

RESULTS

The model was able to fit the tumor volume evolution within 8% error (range: 3-8%). A strong correlation between the intrapatient longitudinal indices from Doppler measurements and oxygen predicted by the model (about 90% or above) was found in three cases. Two patients showed an average correlation value (50-70%) and the remaining two presented poor correlations. The latter patients were the ones featuring the smallest tumor reduction throughout the treatment, typical of hypoxic conditions. Moreover, the average oxygenation value predicted by the model was close to the average vascularization-flow index (average difference: 7%).

CONCLUSIONS

The results suggest that the modeled relation between tumor evolution and oxygen dynamics was reasonable enough to provide realistic oxygenation curves in five cases (correlation greater than 50%) out of seven. In case of nonresponsive tumors, the model failed in predicting the oxygenation trend while succeeded in reproducing the average oxygenation value according to the mean vascularization-flow index. Despite the need for deeper investigations, the outcomes of the present work support the hypothesis that a simple macroscale model of tumor response to radiotherapy is able to predict the tumor oxygenation. The possibility of an objective and quantitative validation on imaging data discloses the possibility to translate them as decision support tools in clinical practice and to move a step forward in the treatment personalization.