Preoperative 18F-FDG PET/CT tumor markers outperform MRI-based markers for the prediction of lymph node metastases in primary endometrial cancer

Objectives To compare the diagnostic accuracy of preoperative 18F-FDG PET/CT and MRI tumor markers for prediction of lymph node metastases (LNM) and aggressive disease in endometrial cancer (EC). Methods Preoperative whole-body 18F-FDG PET/CT and pelvic MRI were performed in 215 consecutive patients with histologically confirmed EC. PET/CT-based tumor standardized uptake value (SUVmax and SUVmean), metabolic tumor volume (MTV), and PET-positive lymph nodes (LNs) (SUVmax > 2.5) were analyzed together with the MRI-based tumor volume (VMRI), mean apparent diffusion coefficient (ADCmean), and MRI-positive LN (maximum short-axis diameter ≥ 10 mm). Imaging parameters were explored in relation to surgicopathological stage and tumor grade. Receiver operating characteristic (ROC) curves were generated yielding optimal cutoff values for imaging parameters, and regression analyses were used to assess their diagnostic performance for prediction of LNM and progression-free survival. Results For prediction of LNM, MTV yielded the largest area under the ROC curve (AUC) (AUC = 0.80), whereas VMRI had lower AUC (AUC = 0.72) (p = 0.03). Furthermore, MTV > 27 ml yielded significantly higher specificity (74%, p  10 ml (58%, 62%, and 9.7, respectively). MTV > 27 ml also tended to yield higher sensitivity than PET-positive LN (81% vs 50%, p = 0.13). Both VMRI > 10 ml and MTV > 27 ml were significantly associated with reduced progression-free survival. Conclusions Tumor markers from 18F-FDG PET/CT outperform MRI markers for the prediction of LNM. MTV > 27 ml yields a high diagnostic performance for predicting aggressive disease and represents a promising supplement to conventional PET/CT reading in EC.publishedVersio

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.publishedVersio

MRI-assessed tumor-free distance to serosa predicts deep myometrial invasion and poor outcome in endometrial cancer

Objectives To explore the diagnostic accuracy of preoperative magnetic resonance imaging (MRI)-derived tumor measurements for the prediction of histopathological deep (≥ 50%) myometrial invasion (pDMI) and prognostication in endometrial cancer (EC). Methods Preoperative pelvic MRI of 357 included patients with histologically confirmed EC were read independently by three radiologists blinded to clinical information. The radiologists recorded imaging findings (T1 post-contrast sequence) suggesting deep (≥ 50%) myometrial invasion (iDMI) and measured anteroposterior tumor diameter (APD), depth of myometrial tumor invasion (DOI) and tumor-free distance to serosa (iTFD). Receiver operating characteristic (ROC) curves for the prediction of pDMI were plotted for the different MRI measurements. The predictive and prognostic value of the MRI measurements was analyzed using logistic regression and Cox proportional hazard model. Results iTFD yielded highest area under the ROC curve (AUC) for the prediction of pDMI with an AUC of 0.82, whereas DOI, APD and iDMI yielded AUCs of 0.74, 0.81 and 0.74, respectively. Multivariate analysis for predicting pDMI yielded highest predictive value of iTFD <  6 mm with OR of 5.8 (p < 0.001) and lower figures for DOI ≥ 5 mm (OR = 2.8, p = 0.01), APD ≥ 17 mm (OR = 2.8, p < 0.001) and iDMI (OR = 1.1, p = 0.82). Patients with iTFD < 6 mm also had significantly reduced progression-free survival with hazard ratio of 2.4 (p < 0.001). Conclusion For predicting pDMI, iTFD yielded best diagnostic performance and iTFD < 6 mm outperformed other cutoff-based imaging markers and conventional subjective assessment of deep myometrial invasion (iDMI) for diagnosing pDMI. Thus, iTFD at MRI represents a promising preoperative imaging biomarker that may aid in predicting pDMI and high-risk disease in EC.publishedVersio

Advanced imaging biomarkers in endometrial cancer

Background: Endometrial cancer is the most common gynecological cancer in highdeveloped regions of the world, and the incidence has been increasing over the last half century, largely driven by a concurrent increase in population obesity. Primary treatment is surgical in most cases, but only limited preoperative risk stratification has been applied in traditional clinical practice. To enable more individualized treatment, improved methods for preoperative tumor characterization are highly warranted. Aim: To identify and evaluate new imaging markers that may aid in the preoperative risk stratification and tailoring of treatment in endometrial cancer. Material and methods: The studies included in this thesis are based on collected imaging-, clinical- and histological data from endometrial cancer patients treated at Haukeland University Hospital during April 2009 to November 2013. Standardized MR imaging data were acquired for 216 prospectively included patients with histologically confirmed endometrial cancer. From this cohort, four different subcohorts were included in study I-IV. In Paper I, three radiologists independently measured tumor size on conventional MR images for 212 patients. In Paper II, metabolic features were extracted from MR spectroscopy performed on 77 patients. In Paper III, texture features were extracted from MR images, using a filtrationhistogram technique in 180 patients. In Paper IV, CT imaging data were retrospectively collected and texture features extracted for 155 patients. In all studies, the respective imaging markers were evaluated as predictors of histopathological highrisk features and survival. Results: The interobserver variability for MRI-measured tumor size is very low (ICC 0.78-0.85) (Paper I). AP diameter greater than 2 cm independently predicts deep myometrial invasion (OR 6.7, p24.2) independently predicts high-risk histological subtype (OR 3.7, p=0.01) (Paper IV). High tumor kurtosis tends to independently predict reduced recurrenceand progression-free survival (adjusted HR 1.1, p=0.06) (Paper IV). Conclusions: Tumor size can be measured on preoperative conventional MRI with very low interobserver variability. Large tumor size predicts deep myometrial invasion, lymph node metastases and poor outcome in endometrial cancer, and thus, imaging markers based on tumor size may improve preoperative risk stratification (Paper I). High choline levels, measured by MR spectroscopy, differentiate tumor tissue from normal tissue in endometrial cancer patients, but do not have significant prognostic value in our study (Paper II). MRI-derived tumor texture parameters predict deep myometrial invasion, high-risk histological subtype, and reduced recurrence- and progression-free survival in endometrial cancer (Paper III). CT-derived tumor texture features predict deep myometrial invasion and cervical stroma invasion in endometrial cancer, and also tend to predict high-risk histological subtype and survival (Paper IV). The image texture features entropy, kurtosis and MPP seem to reflect tumor heterogeneity and may aid in preoperative risk assessment (Paper III and IV)

Tumour texture features from preoperative CT predict high-risk disease in endometrial cancer

BACKGROUND To enable more individualised treatment of endometrial cancer, improved methods for preoperative tumour characterization are warranted. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in oncological imaging, but largely unexplored in endometrial cancer AIM To explore whether tumour texture features from preoperative computed tomography (CT) are related to known prognostic histopathological features and to outcome in endometrial cancer patients. MATERIALS AND METHODS Preoperative pelvic contrast-enhanced CT was performed in 155 patients with histologically confirmed endometrial cancer. Tumour ROIs were manually drawn on the section displaying the largest cross-sectional tumour area, using dedicated texture analysis software. Using the filtration-histogram technique, the following texture features were calculated: mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis. These imaging markers were evaluated as predictors of histopathological high-risk features and recurrence- and progression-free survival using multivariable logistic regression and Cox regression analysis, including models adjusting for high-risk status based on preoperative biopsy, magnetic resonance imaging (MRI) findings, and age. RESULTS High tumour entropy independently predicted deep myometrial invasion (odds ratio [OR] 3.7, p=0.008) and cervical stroma invasion (OR 3.9, p=0.02). High value of MPP (MPP5 >24.2) independently predicted high-risk histological subtype (OR 3.7, p=0.01). Furthermore, high tumour kurtosis tended to independently predict reduced recurrence- and progression-free survival (HR 1.1, p=0.06). CONCLUSION CT texture analysis yields promising imaging markers in endometrial cancer and may supplement other imaging techniques in providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies

Tumour texture features from preoperative CT predict high-risk disease in endometrial cancer

BACKGROUND To enable more individualised treatment of endometrial cancer, improved methods for preoperative tumour characterization are warranted. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in oncological imaging, but largely unexplored in endometrial cancer AIM To explore whether tumour texture features from preoperative computed tomography (CT) are related to known prognostic histopathological features and to outcome in endometrial cancer patients. MATERIALS AND METHODS Preoperative pelvic contrast-enhanced CT was performed in 155 patients with histologically confirmed endometrial cancer. Tumour ROIs were manually drawn on the section displaying the largest cross-sectional tumour area, using dedicated texture analysis software. Using the filtration-histogram technique, the following texture features were calculated: mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis. These imaging markers were evaluated as predictors of histopathological high-risk features and recurrence- and progression-free survival using multivariable logistic regression and Cox regression analysis, including models adjusting for high-risk status based on preoperative biopsy, magnetic resonance imaging (MRI) findings, and age. RESULTS High tumour entropy independently predicted deep myometrial invasion (odds ratio [OR] 3.7, p=0.008) and cervical stroma invasion (OR 3.9, p=0.02). High value of MPP (MPP5 >24.2) independently predicted high-risk histological subtype (OR 3.7, p=0.01). Furthermore, high tumour kurtosis tended to independently predict reduced recurrence- and progression-free survival (HR 1.1, p=0.06). CONCLUSION CT texture analysis yields promising imaging markers in endometrial cancer and may supplement other imaging techniques in providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies

Preoperative 18F-FDG PET/CT tumor markers outperform MRI-based markers for the prediction of lymph node metastases in primary endometrial cancer

Objectives To compare the diagnostic accuracy of preoperative 18F-FDG PET/CT and MRI tumor markers for prediction of lymph node metastases (LNM) and aggressive disease in endometrial cancer (EC). Methods Preoperative whole-body 18F-FDG PET/CT and pelvic MRI were performed in 215 consecutive patients with histologically confirmed EC. PET/CT-based tumor standardized uptake value (SUVmax and SUVmean), metabolic tumor volume (MTV), and PET-positive lymph nodes (LNs) (SUVmax > 2.5) were analyzed together with the MRI-based tumor volume (VMRI), mean apparent diffusion coefficient (ADCmean), and MRI-positive LN (maximum short-axis diameter ≥ 10 mm). Imaging parameters were explored in relation to surgicopathological stage and tumor grade. Receiver operating characteristic (ROC) curves were generated yielding optimal cutoff values for imaging parameters, and regression analyses were used to assess their diagnostic performance for prediction of LNM and progression-free survival. Results For prediction of LNM, MTV yielded the largest area under the ROC curve (AUC) (AUC = 0.80), whereas VMRI had lower AUC (AUC = 0.72) (p = 0.03). Furthermore, MTV > 27 ml yielded significantly higher specificity (74%, p  10 ml (58%, 62%, and 9.7, respectively). MTV > 27 ml also tended to yield higher sensitivity than PET-positive LN (81% vs 50%, p = 0.13). Both VMRI > 10 ml and MTV > 27 ml were significantly associated with reduced progression-free survival. Conclusions Tumor markers from 18F-FDG PET/CT outperform MRI markers for the prediction of LNM. MTV > 27 ml yields a high diagnostic performance for predicting aggressive disease and represents a promising supplement to conventional PET/CT reading in EC

Preoperative tumor size at MRI predicts deep myometrial invasion, lymph node metastases, and patient outcome in endometrial carcinomas

OBJECTIVE: The aim of this study was to explore the relation between preoperative tumor size based on magnetic resonance imaging (MRI) and the surgical pathologic staging parameters (deep myometrial invasion, cervical stroma invasion, and metastatic lymph nodes) and to assess the prognostic impact of tumor size in endometrial carcinomas. Interobserver variability for the different tumor size measurements was also assessed. METHODS/MATERIALS: Preoperative pelvic MRI of 212 patients with histologically confirmed endometrial carcinomas was read independently by 3 radiologists. Maximum tumor diameters were measured in 3 orthogonal planes (anteroposterior, transverse, and craniocaudal planes [CC]), and tumor volumes were estimated. Tumor size was analyzed in relation to surgical staging results and patient survival. The multivariate analyses were adjusted for preoperative risk status based on endometrial biopsy. Intraclass correlation coefficients and receiver operating characteristics curves for the different tumor measurements were also calculated. RESULTS: Anteroposterior tumor diameter independently predicted deep myometrial invasion (P < 0.001), whereas CC tumor diameter tended to independently predict lymph node metastases (P = 0.06). Based on receiver operating characteristic curves, the following tumor size cutoff values were identified: anteroposterior diameter greater than 2 cm predicted deep myometrial invasion (unadjusted odds ratio [OR], 12.4; P < 0.001; adjusted OR, 6.7; P < 0.001) and CC diameter greater than 4 cm predicted lymph node metastases (unadjusted OR, 6.2; P < 0.001; adjusted OR, 4.9; P = 0.009). Large tumor size was associated with reduced progression/recurrence-free survival (P ≤ 0.005 for all size parameters), and CC diameter had an independent impact on survival (adjusted hazards ratio, 1.04; P = 0.009). The interobserver variability for the different size measurements was very low (intraclass correlation coefficient, 0.78-0.85). CONCLUSIONS: Anteroposterior tumor diameter greater than 2 cm predicts deep myometrial invasion, and CC tumor diameter greater than 4 cm predicts lymph node metastases. Tumor size is a strong prognostic factor in endometrial carcinomas. Preoperative tumor measurements based on MRI may potentially improve preoperative risk stratification models and thus enable better tailored surgical treatment in endometrial 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

The prognostic value of preoperative FDG-PET/CT metabolic parameters in cervical cancer patients

Abstract Background To explore quantitative metabolic and microstructural primary tumour parameters at pretreatment FDG-PET/CT and diffusion-weighted-magnetic resonance imaging (DW-MRI) in relation to clinical FIGO stage and outcome in uterine cervical cancer patients. Methods Fifty three patients with histopathologically verified cervical carcinoma with clinical FIGO stage IB1-IVA were subjected to FDG-PET/CT and subgroup also DW-MRI (n = 30) prior to treatment. Measurements from the FDG-PET/CT comprised lesion maximum-standardised uptake value (SUVmax), total lesion glycolysis (TLG) and metabolic tumour volume (MTV). In MR images longest-tumour-diameter (MRI-LD), tumour volume (MRI-TV) and mean tumour apparent-diffusion-coefficient (ADCmean) value were measured. FDG-PET/CT parameters were explored in relation to clinical prognostic factors at diagnosis and progression/recurrence free survival, and compared with the MRI parameters. Results The metabolic tumour parameters TLG and MTV were highly positively correlated to MRI-LD and MRI-TV (rs = 072–0.82; p < 0.001 for all), whereas tumour SUVmax was only moderately correlated to MRI-LD (rs = 0.29; p ≤ 0.04) and MRI-TV (rs = 0.36; p ≤ 0.01). High tumour TLG, MTV, MRI-LD and MRI-TV predicted advanced FIGO stage, whereas high tumour SUVmax did not. No significant correlations were observed between tumour ADCmean and the other imaging parameters or FIGO stage. High primary tumour MTV (≥56.7 mL), high TLG (≥412 g) and large MRI-TV (≥36 mL) predicted reduced progression/recurrence free survival yielding corresponding hazard ratios [HR] of 7.8 (P  =  0.002), 6.9 (P  =  0.004) and 4.6 (P  =  0.022), respectively. Also advanced FIGO stage (≥IIIA) was associated with reduced progression/recurrence free survival with HR of 6.9 (P  =  0.004). In multivariable analysis, advanced FIGO stage (≥IIIA) and high MTV (≥56.7 mL) were independent prognostic factors with adjusted HRs of 5.5 (P  =  0.020) and 7.8 (P  =  0.025), respectively. Conclusion High MTV at pre-treatment FDG-PET/CT and high clinical FIGO stage independently predict reduced progression/recurrence free survival in cervical cancer patients