Feng Hua Ma

MRI for differentiating primary fallopian tube carcinoma from epithelial ovarian cancer

To compare potential discriminatory magnetic resonance imaging (MRI) features of primary fallopian tube carcinoma (PFTC) and primary epithelial ovarian cancer (EOC).

MRI appearances of mucinous borderline ovarian tumors: Pathological correlation

The purpose of this study is to evaluate the MRI features of mucinous borderline ovarian tumors (MBOT).

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.

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

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.

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) × 10−3 mm2; 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.

MRI features and score for differentiating borderline from malignant epithelial ovarian tumors

PURPOSE To identify the MRI features of borderline epithelial ovarian tumors (BEOTs) and to differentiate BEOTs from malignant epithelial ovarian tumors (MEOTs). MATERIALS AND METHODS The clinical and MRI data of 89 patients with a BEOT and 109 patients with a MEOT proven by surgery and histopathology were retrospectively reviewed. MRI features, including bilaterality, size, shape, margin, cystic-solid interface, configuration, papillae or nodules, signal intensity, enhancement, presence of an ipsilateral ovary, peritoneal implants and ascites were analyzed and compared. Based on the odds ratio (OR) values, the significant risk features for BEOTs were scored as 3 (OR≈∞), 2 (5≤OR<∞) or 1 (OR<5). RESULTS There were 89 BEOT patients with 113 tumors [mean size of (13±6.7)cm], with bilateral ovary involvement in 24 cases. There were 109 MEOT patients with 142 tumors [(9.3±4.2)cm] with bilateral ovary involvement in 33 cases. There were eight significant risk factors for BEOTs, including round or oval shape (OR=2.714), well-defined margins (OR=3.318), clear cystic-solid interfaces (OR=5.593), purely cystic (OR=15.206), predominantly cystic with papillae or nodules (OR=2.579), exophytic papillae or nodules (OR=5.351), branching papilla (OR≈∞) and the presence of an ipsilateral ovary (OR≈∞). Based on the scoring of the eight risk factors, a cut-off score of 3.5 yielded a differential sensitivity, specificity, and accuracy of 82%, 85% and 84%, respectively. CONCLUSION In contrast to MEOTs, BEOTs frequently had the following features on MRI: round or oval, with well-defined margins and clear cystic-solid interfaces, purely cystic or predominantly cystic with papillae or nodules, branching or exophytic papillae, with the presence of an ipsilateral ovary. MRI can reveal the distinct morphological features of BEOTs and MEOTs and facilitate their discrimination.

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) × 10−3 mm2/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) × 10−3 mm2/s. Ten (50%) of the patients were SPC. The mean ADC values of the solid components were (0.85 ± 0.19) × 10−3 mm2/s and (1.08 ± 0.15) × 10−3 mm2/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.

Role of proton MR spectroscopy in the differentiation of borderline from malignant epithelial ovarian tumors: A preliminary study: 1H-MRS and Epithelial Ovarian Tumors

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 (1H‐MRS) might have potential to differentiate borderline from malignant tumors.

The value of MR-detectable ipsilateral ovaries in characterizing the origin and malignancy of adnexal tumors

OBJECTIVE To investigate the magnetic resonance (MR) imaging morphological relationship between adnexal tumors and the ipsilateral ovaries to characterize the origin and malignancy of tumors. MATERIAL AND METHODS Clinical and MR imaging data of 496 adnexal tumors confirmed by histology (ovary tumors, n = 400, non-ovarian tumors, n = 96; benign tumors, n = 183, borderline tumors, n = 120, and malignant tumors, n = 193) were retrospectively analyzed. The presence and shape of the ipsilateral ovaries within the context of adnexal tumors of different origins, malignancies and configurations were evaluated. The relationships between the presence of the ipsilateral ovary and patient age, menstrual status and tumor size were also analyzed. RESULT The ipsilateral ovary was detected on MRI in 23% (90/400) of ovarian tumors and in 45% (43/96) of non-ovarian tumors (p < 0.001). A normal ovoid morphology of the ipsilateral ovary was found in only 7% (26/400) of ovarian tumors and in 26% (25/96) of non-ovarian tumors (p < 0.001). The ipsilateral ovary was detectable in 38% (69/183) of benign tumors, 35% (42/120) of borderline tumors, and 11% (22/193) of malignant tumors (p <  0.001); in 24% (24/101) of cystic tumors, 27% (49/179) of mixed cystic-solid tumors and 28% (60/216) of solid tumors (p = 0.737); and in 40% (120/303) of adnexal tumors in premenopausal patients and 7% (13/193) of adnexal tumors in postmenopausal patients (p < 0.001). CONCLUSION Detection of the ipsilateral ovary contributes to the localization and characterization of adnexal tumors. The ipsilateral ovary can be detected more frequently in non-ovarian tumors and in benign or borderline ovarian tumors.

Apparent diffusion coefficients measured using different regions of interest in differentiating borderline from malignant ovarian tumors

Background Apparent diffusion coefficients (ADCs) measured using different regions of interest (ROIs) are widely used in differentiating ovarian tumors. Purpose To evaluate the diagnostic performance of ADCs with different ROIs in differentiating borderline ovarian tumors (BOTs) from malignant ovarian tumors (MOTs). Material and Methods Thirty-five BOTs and 54 MOTs who underwent diffusion-weighted magnetic resonance imaging (MRI) were evaluated retrospectively. ADC values were independently measured using five ROI methods: round; rectangle; hot-spot; edge drawing; and five sample ROIs. The inter- and intraclass correlation coefficients (ICCs), one-way analysis of variance, receiver operating characteristic curve analysis, and unpaired t-tests were used to perform the statistical analyses. Results The measurement reproducibility of the minimum ADC and mean ADC values were good or excellent for BOTs and MOTs (ICC = 0.70–0.95). The minimum and mean ADC value by the edge drawing ROI were significantly higher than those of the other ROI methods (both P < 0.05). The area under the curve (AUC) of the minimum ADC value was less than that of the mean ADC value from the five ROI methods, whereas the AUCs of the mean ADC values from the round ROI and five sample ROIs were significantly larger than those of the other ROI methods (P < 0.05). The minimum and mean ADC values from the five ROI methods showed significant differences between BOTs and MOTs (all P < 0.05). Conclusion The ROI shape influences the diagnostic performance of ADC value for differentiating BOTs from MOTs. The mean ADC values from the round ROI and five sample ROIs have better diagnostic efficiency.