Deep Learning Nomogram for the Identification of Deep Stromal Invasion in Patients With Early-Stage Cervical Adenocarcinoma and Adenosquamous Carcinoma: A Multicenter Study.

BACKGROUND: Deep stromal invasion (DSI) is one of the predominant risk factors that determined the types of radical hysterectomy (RH). Thus, the accurate assessment of DSI in cervical adenocarcinoma (AC)/adenosquamous carcinoma (ASC) can facilitate optimal therapy decision. PURPOSE: To develop a nomogram to identify DSI in cervical AC/ASC. STUDY TYPE: Retrospective. POPULATION: Six hundred and fifty patients (mean age of 48.2 years) were collected from center 1 (primary cohort, 536), centers 2 and 3 (external validation cohorts 1 and 2, 62 and 52). FIELD STRENGTH/SEQUENCE: 5-T, T2-weighted imaging (T2WI, SE/FSE), diffusion-weighted imaging (DWI, EPI), and contrast-enhanced T1-weighted imaging (CE-T1WI, VIBE/LAVA). ASSESSMENT: The DSI was defined as the outer 1/3 stromal invasion on pathology. The region of interest (ROI) contained the tumor and 3 mm peritumoral area. The ROIs of T2WI, DWI, and CE-T1WI were separately imported into Resnet18 to calculate the DL scores (TDS, DDS, and CDS). The clinical characteristics were retrieved from medical records or MRI data assessment. The clinical model and nomogram were constructed by integrating clinical independent risk factors only and further combining DL scores based on primary cohort and were validated in two external validation cohorts. STATISTICAL TESTS: Student's t-test, Mann-Whitney U test, or Chi-squared test were used to compare differences in continuous or categorical variables between DSI-positive and DSI-negative groups. DeLong test was used to compare AU-ROC values of DL scores, clinical model, and nomogram. RESULTS: The nomogram integrating menopause, disruption of cervical stromal ring (DCSRMR), DDS, and TDS achieved AU-ROCs of 0.933, 0.807, and 0.817 in evaluating DSI in primary and external validation cohorts. The nomogram had superior diagnostic ability to clinical model and DL scores in primary cohort (all P < 0.0125 [0.05/4]) and CDS (P = 0.009) in external validation cohort 2. DATA CONCLUSION: The nomogram achieved good performance for evaluating DSI in cervical AC/ASC. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

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

OBJECTIVE: To develop a comprehensive nomogram based on MRI intra- and peritumoral radiomics signatures and independent risk factors for predicting parametrial invasion (PMI) in patients with early-stage cervical adenocarcinoma (AC) and adenosquamous carcinoma (ASC). METHODS: A total of 460 patients with IB to IIB cervical AC and ASC who underwent preoperative MRI examination and radical trachelectomy/hysterectomy were retrospectively enrolled and divided into primary, internal validation, and external validation cohorts. The original (Ori) and wavelet (Wav)-transform features were extracted from the volumetric region of interest of the tumour (ROI-T) and 3mm- and 5mm-peritumoral rings (ROI-3 and ROI-5), respectively. Then the Ori and Ori-Wav feature-based radiomics signatures from the tumour (RST) and 3 mm- and 5 mm-peritumoral regions (RS3 and RS5) were independently built and their diagnostic performances were compared to select the optimal ones. Finally, the nomogram was developed by integrating optimal intra- and peritumoral signatures and clinical independent risk factors based on multivariable logistic regression analysis. RESULTS: FIGO stage, disruption of the cervical stromal ring on MRI (DCSRMR), parametrial invasion on MRI (PMIMR), and serum CA-125 were identified as independent risk factors. The nomogram constructed by integrating independent risk factors, Ori-Wav feature-based RST, and RS5 yielded AUCs of 0.874 (0.810-0.922), 0.885 (0.834-0.924), and 0.966 (0.887-0.995) for predicting PMI in the primary, internal and external validation cohorts, respectively. Furthermore, the nomogram was superior to radiomics signatures and clinical model for predicting PMI in three cohorts. CONCLUSION: The nomogram can preoperatively, accurately, and noninvasively predict PMI in patients with early-stage cervical AC and ASC. CLINICAL RELEVANCE STATEMENT: The nomogram can preoperatively, accurately, and noninvasively predict PMI and facilitate precise treatment decisions regarding chemoradiotherapy or radical hysterectomy in patients with early-stage cervical AC and ASC. KEY POINTS: The accurate preoperative prediction of PMI in early-stage cervical AC and ASC can facilitate precise treatment decisions regarding chemoradiotherapy or radical hysterectomy. The nomogram integrating independent risk factors, Ori-Wav feature-based RST, and RS5 can preoperatively, accurately, and noninvasively predict PMI in early-stage cervical AC and ASC. The nomogram was superior to radiomics signatures and clinical model for predicting PMI in early-stage cervical AC and ASC.

Radiologists with MRI-based radiomics aids to predict the pelvic lymph node metastasis in endometrial cancer: a multicenter study.

OBJECTIVE: To construct a MRI radiomics model and help radiologists to improve the assessments of pelvic lymph node metastasis (PLNM) in endometrial cancer (EC) preoperatively. METHODS: During January 2014 and May 2019, 622 EC patients (age 56.6 ± 8.8 years; range 27-85 years) from five different centers (A to E) were divided into training set, validation set 1 (351 cases from center A), and validation set 2 (271 cases from centers B-E). The radiomics features were extracted basing on T2WI, DWI, ADC, and CE-T1WI images, and most related radiomics features were selected using the random forest classifier to build a radiomics model. The ROC curve was used to evaluate the performance of training set and validation sets, radiologists based on MRI findings alone, and with the aid of the radiomics model. The clinical decisive curve (CDC), net reclassification index (NRI), and total integrated discrimination index (IDI) were used to assess the clinical benefit of using the radiomics model. RESULTS: The AUC values were 0.935 for the training set, 0.909 and 0.885 for validation sets 1 and 2, 0.623 and 0.643 for the radiologists 1 and 2 alone, and 0.814 and 0.842 for the radiomics-aided radiologists 1 and 2, respectively. The AUC, CDC, NRI, and IDI showed higher diagnostic performance and clinical net benefits for the radiomics-aided radiologists than for the radiologists alone. CONCLUSIONS: The MRI-based radiomics model could be used to assess the status of pelvic lymph node and help radiologists improve their performance in predicting PLNM in EC. KEY POINTS: • A total of 358 radiomics features were extracted. The 37 most important features were selected using the random forest classifier. • The reclassification measures of discrimination confirmed that the radiomics-aided radiologists performed better than the radiologists alone, with an NRI of 1.26 and an IDI of 0.21 for radiologist 1 and an NRI of 1.37 and an IDI of 0.24 for radiologist 2.

Preoperative Assessment for High-Risk Endometrial Cancer by Developing an MRI- and Clinical-Based Radiomics Nomogram: A Multicenter Study.

BACKGROUND: High- and low-risk endometrial cancer (EC) differ in whether lymphadenectomy is performed. Assessment of high-risk EC is essential for planning surgery appropriately. PURPOSE: To develop a radiomics nomogram for high-risk EC prediction preoperatively. STUDY TYPE: Retrospective. POPULATION: In all, 717 histopathologically confirmed EC patients (mean age, 56 years ± 9) divided into a primary group (394 patients from Center A), validation groups 1 and 2 (146 patients from Center B and 177 patients from Centers C-E). FIELD STRENGTH/SEQUENCE: 1.5/3T scanners; T2 -weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, and contrast enhancement sequences. ASSESSMENT: A radiomics nomogram was generated by combining the selected radiomics features and clinical parameters (metabolic syndrome, cancer antigen 125, age, tumor grade following curettage, and tumor size). The area under the curve (AUC) of the receiver operator characteristic was used to evaluate the predictive performance of the radiomics nomogram for high-risk EC. The surgical procedure suggested by the nomogram was compared with the actual procedure performed for the patients. Net benefit of the radiomics nomogram was evaluated by a clinical decision curve (CDC), net reclassification index (NRI), and integrated discrimination improvement (IDI). STATISTICAL TESTS: Binary least absolute shrinkage and selection operator (LASSO) logistic regression, linear regression, and multivariate binary logistic regression were used to select radiomics features and clinical parameters. RESULTS: The AUC for prediction of high-risk EC for the radiomics nomogram in the primary group, validation groups 1 and 2 were 0.896 (95% confidence interval [CI]: 0.866-0.926), 0.877 (95% CI: 0.825-0.930), and 0.919 (95% CI: 0.879-0.960), respectively. The nomogram achieved good net benefit by CDC analysis for high-risk EC. NRIs were 1.17, 1.28, and 1.51, and IDIs were 0.41, 0.60, and 0.61 in the primary group, validation groups 1 and 2, respectively. DATA CONCLUSION: The radiomics nomogram exhibited good performance in the individual prediction of high-risk EC, and might be used for surgical management of EC. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1872-1882.

Role of proton MR spectroscopy in the differentiation of borderline from malignant epithelial ovarian tumors: A preliminary study.

BACKGROUND: Due to the overlapping imaging appearances between borderline and malignant epithelial ovarian tumors (EOTs), borderline EOTs often represent a diagnostic challenge on conventional MRI. Proton magnetic resonance spectroscopy (1 H-MRS) might have potential to differentiate borderline from malignant tumors. PURPOSE: To investigate the ability of 1 H-MRS to differentiate borderline from malignant EOTs. STUDY TYPE: Prospective. POPULATION: In all, 278 patients with adnexal masses. FIELD STRENGTH/SEQUENCE: 1.5 T Siemens Avanto MRI system and 1 H-MRS using a point-resolved spectroscopy sequence (PRESS). ASSESSMENT: Resonance peak integrals of the most common metabolites were analyzed and compared between the two groups. STATISTICAL TESTS: The ratios of metabolites between borderline and malignant EOTs were compared with the Mann-Whitney U-test. A receiver operating characteristic (ROC) curve was used to determine their differential diagnosis performances. RESULTS: In the solid components of borderline and malignant EOTs, the mean Cho/Cr, NAA/Cr, and NAA/Cho ratios were 4.4 ± 1.1 and 9.9 ± 2.8; 10.4 ± 3.0 and 2.2 ± 1.0; and 2.4 ± 0.7 and 0.3 ± 0.1, respectively (all P < 0.001). The sensitivity, specificity, and area under the curve (AUC) were 91%, 100%, and 0.98 for the Cho/Cr ratio; 100%, 98%, and 0.99 for the NAA/Cr ratio; and 100%, 100%, and 1.00 for the NAA/Cho ratio, respectively. In the cystic components, the mean Cho/Cr, NAA/Cr, and NAA/Cho ratios were 3.2 ± 0.8 and 5.1 ± 1.2; 9.1 ± 3.4 and 2.3 ± 1.4; and 2.9 ± 1.2 and 0.5 ± 0.4, respectively (all P < 0.001). The sensitivity, specificity, and AUC were 84%, 82%, and 0.89 for the Cho/Cr ratio; 94%, 97%, and 0.99 for the NAA/Cr ratio; and 94%, 97%, and 0.99 for the NAA/Cho ratio, respectively. DATA CONCLUSION: The NAA/Cho ratio is a reliable biomarker for differentiating borderline from malignant EOTs. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:1684-1693.

Diffusion kurtosis imaging for differentiating borderline from malignant epithelial ovarian tumors: A correlation with Ki-67 expression.

PURPOSE: To investigate the use of diffusion kurtosis imaging (DKI) in differentiating borderline from malignant epithelial ovarian tumors (MEOTs) and to correlate DKI parameters with Ki-67 expression. MATERIALS AND METHODS: Fifty-two consecutive patients with epithelial ovarian tumors (17 borderline epithelial ovarian tumors, BEOTs; 35 MEOTs) were prospectively evaluated using DKI with b values of 0, 500, 1000, 1500, 2000, and 2500 s/mm2 and standard diffusion-weighted imaging (DWI) with b values of 0 and 1000 s/mm2 using a 1.5T magnetic resonance imaging (MRI) unit. The kurtosis (K) and diffusion coefficient (D) from DKI and apparent diffusion coefficient (ADC) from standard DWI were measured, compared, and correlated with Ki-67 expression between the two groups. Statistical analyses were performed using the Mann-Whitney U-test, receiver operating characteristic (ROC) curves, and Spearman's correlation. RESULTS: The K value was significantly lower in BEOTs than in MEOTs (0.55 ± 0.09 vs. 0.9 ± 0.2), while the D and ADC values were significantly higher in BEOTs than in MEOTs (2.27 ± 0.35 vs. 1.39 ± 0.37 and 1.72 ± 0.36 vs. 1.1 ± 0.25, respectively) (P < 0.001). For differentiating between BEOTs and MEOTs, the sensitivity, specificity, and accuracy were 88.2%, 94.3%, and 92.3% for K value; 88.2%, 91.4%, and 90.4% for D value; and 88.2%, 88.6%, and 88.5% for ADC value, respectively. However, there were no differences in the diagnostic performances among the three parameters above (K vs. ADC, P = 0.203; D vs. ADC, P = 0.148; K vs. D, P = 0.904). The K value was positively correlated with Ki-67 expression (r = 0.699), while the D and ADC values were negatively correlated with Ki-67 expression (r = -0.680, -0.665, respectively). CONCLUSION: Preliminary findings demonstrate that DKI is an alternative tool for differentiating BEOTs from MEOTs, and is correlated with Ki-67 expression. However, no added value is found for DKI compared with standard DWI. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1499-1506.

Endometrial Stromal Sarcoma of the Uterus: Magnetic Resonance Imaging Findings Including Apparent Diffusion Coefficient Value and Its Correlation With Ki-67 Expression.

OBJECTIVE: This study aimed to investigate the conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) features of endometrial stromal sarcoma (ESS) including a preliminary investigation of the correlation between the apparent diffusion coefficient (ADC) value and Ki-67 expression. METHODS: The clinical and MRI data of 15 patients with ESS confirmed by surgery and pathology were analyzed retrospectively. The conventional MR morphological features, signal intensity on DWI, ADC value (n = 14), and clinicopathological marker Ki-67 (n = 13) were evaluated. RESULTS: Of 15 patients with ESS, 13 tumors were low-grade ESS (LGESS), and the remaining 2 were high-grade ESS (HGESS); 9 tumors were located in the myometrium, 5 were located in the endometrium and/or cervical canal, and 1 was located in extrauterine. Thirteen (87%) of 15 tumors showed a homo- or heterogeneous isointensity on T1-weighted imaging and a heterogeneous hyperintensity on T2-weighted imaging. The hypointense bands were observed in 11 tumors (73%) on T2-weighted imaging. The degenerations (cystic/necrosis/hemorrhage) were observed in 7 LGESS tumors and 2 HGESS tumors. The DWI hyperintensity was observed in 13 tumors (93%) and isointensity in remaining 1. The mean ADC value of the solid components in 14 ESSs was (1.05 ± 0.20) × 10mm/s. The contrast-enhanced MRI showed an obvious enhancement in 14 tumors (93%) (heterogeneous in 7 LGESSs and 2 HGESSs; homogeneous in 5 LGESSs). The ADC value was inversely correlated with the Ki-67 expression (r = -0.613, P = 0.026). CONCLUSIONS: Patients with ESS showed some characteristics on conventional MRI and DWI, and there was an inverse correlation between the ADC value and Ki-67 expression.

MRI for differentiating primary fallopian tube carcinoma from epithelial ovarian cancer.

PURPOSE: To compare potential discriminatory magnetic resonance imaging (MRI) features of primary fallopian tube carcinoma (PFTC) and primary epithelial ovarian cancer (EOC). MATERIALS AND METHODS: MRI features (the laterality, shape, size, signal intensity, enhancement of solid portion, amount of ascites, peritoneal planting, lymph nodes, or distant metastasis) of 27 tumors in 23 patients with PFTC confirmed by surgery and pathology were compared with 42 tumors in 37 patients with EOC. RESULTS: The mean maximum diameter was 6.1 ± 0.7 cm in PFTC versus 10.2 ± 0.6 cm in EOC. MRI features of PFTC were sausage-like shape (19/27, 70%), or irregular (8/27, 30%) shape; solid (20/27, 74%) or cystic-solid (7/27, 26%) mass; homogeneous (21/27, 78%) or heterogeneous (6/27, 22%) signal on T2 -weighted images; mild (8/27, 30%), moderate (13/27, 48%), or prominent (6/27, 22%) enhancement; associated hydrosalpinx (13/27, 48%) or intrauterine fluid accumulation (7/23, 30%). Significant differences between PFTC and EOC were found in the size, shape, configuration, signal homogeneity, and enhancement pattern, associated hydrosalpinx, and intrauterine fluid accumulation (P < 0.001, < 0.001, 0.015, 0.001, < 0.001, < 0.001, and 0.001, respectively). CONCLUSION: PFTC often appears as a small-sized solid mass, with a sausage-like shape, homogeneous signal, mild or moderate enhancement, hydrosalpinx, or intrauterine fluid accumulation. Our preliminary study shows that MRI can identify the characteristic features of PFTC and differentiate PFTC from EOC.

MR Spectroscopy for Differentiating Benign From Malignant Solid Adnexal Tumors.

OBJECTIVE: The purpose of this article is to investigate the proton MR spectroscopy ((1)H-MRS) features of solid adnexal tumors and to evaluate the efficacy of (1)H-MRS for differentiating benign from malignant solid adnexal tumors. MATERIALS AND METHODS: Sixty-nine patients with surgically and histologically proven solid adnexal tumors (27 benign and 42 malignant) underwent conventional MRI and (1)H-MRS. Single-voxel spectroscopy was performed using the point-resolved spectroscopy localization technique with a voxel size of 2 × 2 × 2 cm(3). Resonance peak integrals of choline, N-acetyl aspartate (NAA), creatine, lactate, and lipid were analyzed, and the choline-tocreatine, NAA-to-creatine, lactate-to-creatine, and lipid-to-creatine ratios were recorded and compared between benign and malignant tumors. RESULTS: A choline peak was detected in all 69 cases (100%), NAA peak in 67 cases (97%, 25 benign and 42 malignant), lipid peak in 47 cases (17 benign and 30 malignant), and lactate peak in eight cases (four benign and four malignant). The mean (± SD) choline-tocreatine ratio was 5.13 ± 0.6 in benign tumors versus 8.90 ± 0.5 in malignant solid adnexal tumors, a statistically significant difference (p = 0.000). There were no statistically significant differences between benign and malignant tumors in the NAA-to-creatine and lipid-to-creatine ratios (p = 0.263 and 0.120, respectively). When the choline-to-creatine threshold was 7.46 for differentiating between benign and malignant tumors, the sensitivity, specificity, and accuracy were 94.1%, 97.1%, and 91.2%, respectively. CONCLUSION: Our preliminary study shows that the (1)H-MRS patterns of benign and malignant solid adnexal tumors differ. The choline-to-creatine ratio can help clinicians differentiate benign from malignant tumors.

Primary fallopian tube carcinoma: correlation between magnetic resonance and diffuse weighted imaging characteristics and histopathologic findings.

OBJECTIVE: The aim of this study was to investigate the magnetic resonance (MR) and diffusion-weighted (DW) imaging characteristics of primary fallopian tube carcinoma (PFTC). METHODS: The clinical, MR, and DW imaging characteristics and pathologic findings of 23 patients with 27 tumors were studied retrospectively. The MR and DW imaging appearance of tumors including laterality, size and shape, architecture, signal intensity, apparent diffusion coefficient (ADC) value, enhancement pattern, hydrosalpinx, and intrauterine fluid collection were evaluated and correlated with pathologic findings. RESULTS: Histopathologically, all 27 tumors were serous carcinoma with a unilateral tumor in 19 patients and bilateral tumors in 4 patients. Thirteen patients (57%) with PFTC were misdiagnosed preoperatively, 10 of which as epithelial ovarian carcinoma. The mean (SD) largest diameter was 61 (7) mm. The tumor shape was fusiform, sausagelike, or serpentine in 19 patients (70%) and nodular or irregular in 8 patients (30%). Twenty (74%) of the 27 tumors were solid, and 7 (26%) were cystic-solid. The solid components showed hypointensity to isointensity on T1-weighted imaging, and isointensity to slight hyperintensity on T2-weighted imaging. There were obvious hyperintensity on DW imaging; obvious hypointensity on ADC maps with a mean (SD) ADC value of 0.79 (0.22) × 10 mm; and mild (8/27, 30%), moderate (13/27, 48%), and marked (6/27, 22%) enhancement on contrast-enhanced imaging. Ipsilateral hydrosalpinx, intrauterine fluid collection, and ascites were found in 14 tumors (52%) and 7 (30%) and 5 (22%) patients, respectively. CONCLUSIONS: The PFTC has some characteristic MR imaging features. The DW imaging, ADC maps, and ADC values are helpful for the detection and differentiation of PFTC from other pelvic masses.

Primary ovarian endometrioid adenocarcinoma: magnetic resonance imaging findings including a preliminary observation on diffusion-weighted imaging.

OBJECTIVE: This study aimed to investigate the magnetic resonance imaging (MRI) features of ovarian endometrioid adenocarcinoma (OEC) and to evaluate conventional MRI and diffusion-weighted imaging (DWI) for diagnosing OEC. MATERIALS AND METHODS: Twenty patients with OEC proven by surgery and pathology underwent MRI. The MRI features of the tumors evaluated included laterality, shape, size, configuration, mural nodules, signal intensity, apparent diffusion coefficient (ADC) values, enhancement, peritoneal implants, ascites, and synchronous primary cancer (SPC) of the ovary and endometrium. RESULTS: Unilateral ovarian masses were observed in 18 (90%) of the 20 patients with 22 OEC lesions, whereas the remaining 2 (10%) patients had bilateral masses. Oval, lobulated, and irregular shapes were observed in 13 (59%), 6 (27%), and 3 (14%) tumors, respectively. The maximum diameter of the tumors ranged from 3.7 to 22.5 cm, with a mean of 11.2 ± 5.1 cm. Fifteen (68%) masses were mainly cystic with mural nodules, 5 (23%) were mixed cystic-solid, and 2 (9%) were solid. The solid components of tumors showed isointensity (100%) on T1-weighted imaging (T1WI), heterogeneous hyperintensity on T2-weighted imaging (T2WI) (86%), and hyperintensity on DWI (82%), with a mean ADC value of (0.96 ± 0.20) × 10 mm/s. The cystic components showed isointensity or hyperintensity (85%) on T1WI, hyperintensity on T2WI (100%), and hypointensity on DWI (63%), with a mean ADC value of (2.27 ± 0.27) × 10 mm/s. Ten (50%) of the patients were SPC. The mean ADC values of the solid components were (0.85 ± 0.19) × 10 mm/s and (1.08 ± 0.15) × 10 mm/s in only-OEC and SPC, respectively, with a statistically significant difference (P = 0.012). CONCLUSIONS: Ovarian endometrioid adenocarcinoma usually appears as a large, oval, or lobulated cystic mass with mural nodules. Cystic components show isointensity or hyperintensity on T1WI, solid components and hyperintensity on T2WI and DWI. Synchronous primary cancer of the ovary endometrium is another characteristic feature of OEC.

MRI appearances of mucinous borderline ovarian tumors: pathological correlation.

PURPOSE: The purpose of this study is to evaluate the MRI features of mucinous borderline ovarian tumors (MBOT). MATERIALS AND METHODS: MRI morphology of 30 MBOT proven MBOT by surgery and pathology was retrospectively studied and correlated with the histopathological findings. On MRI, tumors were classified into three morphological categories: (i) unilocular cyst in five (17%) tumors. (ii) multilocular cyst in 23 (76%) tumors. (iii) solid mass in 2 (7%) tumors. MRI features of tumors were identified including the multilocularity (23/30, 77%), honeycomb loculi (15/30, 50%), signal discrepancy (different signal intensity on T1WI and T2WI) (19/30, 63%), thickened wall or septa (>3 mm) (16/30, 53%). RESULTS: Intestinal type and endocervical type of MBOT, two distinctly histologic subtypes, were found in 20 (67%) and 10 (33%) tumors respectively. There were a higher prevalence of multilocularity (P = 0.026), honeycomb loculi (P = 0.025), and signal discrepancy (P = 0.024) in intestinal type than endocervical type of MBOT. CONCLUSION: Typical MRI features of MBOT are large multilocular tumors with honeycomb loculi, heterogeneous signal intensity of the loculi, and thickened wall or septa.

Diffusion-weighted MR imaging for differentiating borderline from malignant epithelial tumours of the ovary: pathological correlation.

OBJECTIVES: To investigate diffusion-weighted (DW) magnetic resonance (MR) imaging for differentiating borderline from malignant epithelial tumours of the ovary. METHODS: This retrospective study included 60 borderline epithelial ovarian tumours (BEOTs) in 48 patients and 65 malignant epithelial ovarian tumours (MEOTs) in 54 patients. DW imaging as well as conventional MR imaging was performed. Signal intensity on DW imaging was assessed and apparent diffusion coefficient (ADC) value was measured. The results were correlated with histopathology and cell density. RESULTS: The majority of MEOTs showed high signal intensity on DW imaging, whereas most BEOTs showed low or moderate signal intensity (P = 0.000). The mean ADC value of the solid components in BEOTs (1.562 ± 0.346 × 10(-3) mm(2)/s) was significantly higher than in MEOTs (0.841 ± 0.209 × 10(-3) mm(2)/s). A threshold value of 1.039 × 10(-3) mm(2)/s permitted the distinction with a sensitivity of 97.0%, a specificity of 92.2% and an accuracy of 96.4%. There was an inverse correlation between ADC value and cell density (r = -0.609; P = 0.0000) which was significantly lower in BEOTs than in MEOTs. CONCLUSIONS: DW imaging is useful for differentiating borderline from malignant epithelial tumours of the ovary. KEY POINTS: DW MR imaging is useful for differentiating BEOTs from MEOTs. Patients with BEOTs are treated differently from patients with MEOTs. Conservative fertility-sparing laparoscopic surgery can be performed in patients with BEOTs. BEOTs often affect young women of childbearing age.

Comparison of MRI features among squamous cell carcinoma, adenocarcinoma and adenosquamous carcinoma, usual-type endocervical adenocarcinoma and gastric adenocarcinoma of cervix.

OBJECTIVE: To compare and explore the characteristics of squamous cell carcinoma (SCC), adenocarcinoma (AC) and adenosquamous carcinoma (ASC), usual-type endocervical adenocarcinoma (UEA) and gastric adenocarcinoma (GAC) of cervix. MATERIALS AND METHODS: A total of 728 cervical cancers (254 cases of AC, 252 cases of ASC, and 222 cases of SCC) confirmed by histopathology were retrospectively reviewed. Among AC, 119 UEA and 47 GAC were included. Clinical baseline data and tumor morphological features on MRI (including tumor location, shape, diameter and volume, margin, growth pattern, presence of fluid component or cyst, heterogenous and peritumoral enhancement) of all cases were collected and analyzed. The signal intensity (SI) of tumor and gluteus maximus muscle were measured and their ratios (SIR) were calculated based on T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and contrast-enhanced T1WI at arterial and delay phases (A/DCE-T1WI). These clinical and MRI features were compared between SCC, AC and ASC, UEA and GAC, and the specific ones of each subtype were identified. RESULTS: There was a significant difference in SCC-Ag, CA-199, CEA, ADC value, SIR-DWI, presence of intratumor cyst and peritumoral enhancement between AC and ASC; in patient age, menopausal status, International Federation of Gynecology and Obstetrics (FIGO) stage, SCC-Ag, CA-125, CA-199, CEA, tumor shape, growth pattern, margin, presence of intratumor fluid component and cyst, tumor diameter and volume, ADC value, SIR-T1WI, SIR-T2WI, and SIR-DWI between SCC and AC, as well as SCC and ASC. Also, there was a significant difference in deep stromal invasion (DSI), peritumoral and heterogenous enhancement between SCC and AC, and in SIR-ACE-T1WI between SCC and ASC. There was a significant difference in reproductive history, menopausal status, FIGO stage, CA-199, DSI, lymph node metastasis (LNM), parametrial invasion (PMI), tumor location, shape, margin, growth pattern, presence of fluid component and cyst, tumor diameter and volume, SIR-T1WI, SIR-DWI, and heterogenous enhancement between GAC and UEA. CONCLUSION: The clinical and MRI features with significant differences among SCC, AC and ASC, and between UEA and GAC, can help to identify each subtype of cervical cancer.

Radiomics Nomogram in Assisting Lymphadenectomy Decisions by Predicting Lymph Node Metastasis in Early-Stage Endometrial Cancer.

Background: Lymph node metastasis (LNM) is an important risk factor affecting treatment strategy and prognosis for endometrial cancer (EC) patients. A radiomics nomogram was established in assisting lymphadenectomy decisions preoperatively by predicting LNM status in early-stage EC patients. Methods: A total of 707 retrospective clinical early-stage EC patients were enrolled and randomly divided into a training cohort and a test cohort. Radiomics features were extracted from MR imaging. Three models were built, including a guideline-recommended clinical model (grade 1-2 endometrioid tumors by dilatation and curettage and less than 50% myometrial invasion on MRI without cervical infiltration), a radiomics model (selected radiomics features), and a radiomics nomogram model (combing the selected radiomics features, myometrial invasion on MRI, and cancer antigen 125). The predictive performance of the three models was assessed by the area under the receiver operating characteristic (ROC) curves (AUC). The clinical decision curves, net reclassification index (NRI), and total integrated discrimination index (IDI) based on the total included patients to assess the clinical benefit of the clinical model and the radiomics nomogram were calculated. Results: The predictive ability of the clinical model, the radiomics model, and the radiomics nomogram between LNM and non-LNM were 0.66 [95% CI: 0.55-0.77], 0.82 [95% CI: 0.74-0.90], and 0.85 [95% CI: 0.77-0.93] in the training cohort, and 0.67 [95% CI: 0.56-0.78], 0.81 [95% CI: 0.72-0.90], and 0.83 [95% CI: 0.74-0.92] in the test cohort, respectively. The decision curve analysis, NRI (1.06 [95% CI: 0.81-1.32]), and IDI (0.05 [95% CI: 0.03-0.07]) demonstrated the clinical usefulness of the radiomics nomogram. Conclusions: The predictive radiomics nomogram could be conveniently used for individualized prediction of LNM and assisting lymphadenectomy decisions in early-stage EC patients.

Radiomics feature as a preoperative predictive of lymphovascular invasion in early-stage endometrial cancer: A multicenter study.

Background: The presence of lymphovascular space invasion (LVSI) has been demonstrated to be significantly associated with poor outcome in endometrial cancer (EC). No effective clinical tools could be used for the prediction of LVSI preoperatively in early-stage EC. A radiomics nomogram based on MRI was established to predict LVSI in patients with early-stage EC. Methods: This retrospective study included 339 consecutive patients with early-stage EC with or without LVSI from five centers. According to the ratio of 2:1, 226 and 113 patients were randomly assigned to a training group and a test group, respectively. Radiomics features were extracted from T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), contrast-enhanced (CE), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. The radiomics signatures were constructed by using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm in the training group. The radiomics nomogram was developed using multivariable logistic regression analysis by incorporating radiomics signatures and clinical risk factors. The sensitivity, specificity, and AUC of the radiomics signatures, clinical risk factors, and radiomics nomogram were also calculated. Results: The individualized prediction nomogram was constructed by incorporating the radiomics signatures with the clinical risk factors (age and cancer antigen 125). The radiomics nomogram exhibited a good performance in discriminating between negative and positive LVSI patients with AUC of 0.89 (95% CI: 0.83-0.95) in the training group and of 0.85 (95% CI: 0.75-0.94) in the test group. The decision curve analysis indicated that clinicians could be benefit from the using of radiomics nomogram to predict the presence of LVSI preoperatively. Conclusion: The radiomics nomogram could individually predict LVSI in early-stage EC patients. The nomogram could be conveniently used to facilitate the treatment decision for clinicians.

An MRI radiomics nomogram improves the accuracy in identifying eligible candidates for fertility-preserving treatment in endometrioid adenocarcinoma.

It is difficult to identify eligible candidates for fertility-preserving treatment (FPT) among endometrioid adenocarcinoma (EAC) and atypical hyperplasia (AH) patients. Therefore, new approaches for improving the accuracy of candidate selection are warranted. From December 2014 to January 2020, 236 EAC/AH patients (age <50 and premenopausal) were retrospectively reviewed and randomly divided into the primary group (n=158) and validation group 1 (n=78). From February 2020 to December 2021, 51 EAC/AH patients were prospectively enrolled and formed the validation group 2. From the primary group, 385 features were extracted using pyradiomics from multiparameter magnetic resonance imaging (MRI) (including T2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, and contrast enhancement sequences) and 13 radiomics features were selected using a least absolute shrinkage and selection operator. A clinical model based on clinical information (myometrial invasion on MRI and tumor grade in curettage) and a radiomics nomogram by integrating clinical information with the radiomics features was developed to identify eligible candidates of FPT. For identifying eligible candidates of FPT, the areas under the receiver operating characteristic curve (AUCs) were 0.63 (95% confidence interval [CI]: 0.53-0.73) in the primary group, and 0.62 (95% CI: 0.45-0.78) and 0.69 (95% CI: 0.53-0.86) in validation groups 1 and 2, respectively, for the clinical model; were 0.86 (95% CI: 0.80-0.93) in the primary group, and 0.82 (95% CI: 0.71-0.93) and 0.94 (95% CI: 0.87-1.0) in validation groups 1 and 2, respectively, for the radiomics nomogram. With the help of radiomics nomogram, the treatment decision determined from the clinical model was revised in 45 EAC/AH patients. The net reclassification index (NRI) was 0.80 and integrated discrimination improvement (IDI) was 0.17, indicating that the nomogram could improve the accuracy in identifying eligible EAC/AH candidates for FPT.

[Clinical observation of visual quality after implantation of toric intraocular lens].

OBJECTIVE: To observe the visual quality after implantation of Acrysof toric intraocular lens (IOL) in cataract patients. METHODS: Eighty eyes (60 patients) had implantation of Acrysof toric IOL in our hospital between Oct. 2009 and Sep. 2010. The patients were divided into four groups according to the toric models (T3, T4 and T5). The uncorrected visual acuity (UCVA), best corrected visual acuity (BCVA), residual cylinders, contrast sensitivity, high order aberration and IOL axis were evaluated preoperatively and 3 months postoperatively. Sixty-five eyes (45 patients) had implantation of Acrysof Natural IOL. RESULTS: The UCVA improved in the toric groups three months postoperatively. The UCVA of group T5b was lower than that of the other three groups. The UCVA of toric group was (0.19 ± 0.14) which was better than that of the control group (t = 4.04, P < 0.05). The residual cylinder was (1.69 ± 0.68) D in group T5b, which was statistically different from the other three groups. The residual cylinder of the toric group was (0.51 ± 0.78) D, which was much lower than the control group (t = 2.54, P < 0.05). The difference of contrast sensitivity between the four toric groups was not statistically significant. The low-order aberration and coma of group T5b was higher than that of the other three groups. The difference of contrast sensitivity between the toric group and the control group was not statistically significant. The low-order aberration and coma of the toric group were lower than those of the control group. The IOLs in 67 eyes (83.75%) rotated less than 5 degrees and all IOLs rotated less than 10 degrees. CONCLUSION: Implantation of the AcrySof toric IOL proves to be an effective, safe, and stable method of managing corneal astigmatism in cataract patients and provides good visual quality.

Prediction of Platinum-based Chemotherapy Response in Advanced High-grade Serous Ovarian Cancer: ADC Histogram Analysis of Primary Tumors.

RATIONALE AND OBJECTIVES: To investigate the feasibility of apparent diffusion coefficient (ADC) histogram analysis of primary advanced high-grade serous ovarian cancer (HGSOC) to predict patient response to platinum-based chemotherapy. MATERIALS AND METHODS: A total of 70 patients with 102 advanced stage HGSOCs (International Federation of Gynecology and Obstetrics (FIGO) stages III-IV) who received standard treatment of primary debulking surgery followed by the first line of platinum-based chemotherapy were retrospectively enrolled. Patients were grouped as platinum-resistant and platinum-sensitive according to whether relapse occurred within 6 months. Clinical characteristics, including age, pretherapy CA125 level, International Federation of Gynecology and Obstetrics stage, residual tumor, and histogram parameters derived from whole tumor and solid component such as ADCmean; 10th, 20th, 25th, 30th, 40th, 50th, 60th, 70th, 75th, 80th, 90th percentiles; skewness and kurtosis, were compared between platinum-resistant and platinum-sensitive groups. RESULTS: No significantly different clinical characteristics were observed between platinum-sensitive and platinum-resistant patients. There were no significant differences in any whole-tumor histogram-derived parameters between the two groups. Significantly higher ADCmean and percentiles and significantly lower skewness and kurtosis from the solid-component histogram parameters were observed in the platinum-sensitive group when compared with the platinum-resistant group. ADCmean, skewness and kurtosis showed moderate prediction performances, with areas under the curve of 0.667, 0.733 and 0.616, respectively. Skewness was an independent risk factor for platinum resistance. CONCLUSION: Pretreatment ADC histogram analysis of primary tumors has the potential to allow prediction of response to platinum-based chemotherapy in patients with advanced HGSOC.