Differentiation of benign and malignant uterine corpus tumors by using proton MR spectroscopy at 3T: preliminary study

The genetic characterization of germplasm and identification of the litter size trait associated candidate genes in Dexin mutton and fine-wool sheep

Xinjiang is a major province of sheep breeding in China, which plays an important role in meeting people's needs for meat products, increasing farmers' income and sustainable development of animal husbandry. However, the genetic differentiation relationship between breeds was not clear, and most sheep had low fecundity, which seriously restricted the efficient development of sheep industry. Therefore, this study used the whole genome resequencing to detect the genetic variation of Dexin mutton and fine-wool sheep, explored the selected regions and important genes of the litter size traits, analyzed the genetic mechanism of reproductive traits, and provided new insights for the high fecundity breeding of sheep. A total of 5,236.338 G genome data and 35,884,037 SNPs were obtained. Furthermore, we identified 39 selection signals spanning candidate genes, 99 genes were significantly associated related to growth, reproduction and immunity, among which, BRIP1, BMPR1B, BMP4, NGF, etc. genes, and MAKP signaling pathway, Fanconi anemia pathway and Thyroid hormone signaling pathway and other signaling pathways were significantly correlated with litter size trait. Among them, we identified NGF, TrKA and BRIP1 genes was the important genes for sheep litter size traits and the mutation frequencies of 9 SNPs in BRIP1 gene were significantly different in domestic sheep in the world. The research provided new insights for the breeding of self-cultivated meat fine-wool sheep.

Magnetic resonance spectroscopy associations with clinicopathologic features of estrogen-dependent endometrial cancer

BACKGROUND

We studied the magnetic resonance spectroscopy (MRS) associations with clinicopathologic features of estrogen-dependent endometrial cancer (type I EC).

METHODS

Totally 45 patients with type I EC who underwent preoperative multi-voxel MRS at 3.0 T were enrolled. The mean ratio of the Cho peak integral to the unsuppressed water peak integral (Cho/water) of the tumor was calculated. The Cho/water and apparent diffusion coefficient (ADC) of type I EC with and without local invasion, as well as with different levels of Ki-67 staining index (SI) (≤ 40% and > 40%), were compared. Correlation test was used to examine the relationship of Cho/water, as well as mean ADC, with Ki-67 SI, tumor stage, and tumor grade.

RESULTS

The mean Cho/water of EC with Ki-67 SI ≤ 40% (2.28 ± 0.93) × 10^-3 was lower than that with Ki-67 SI > 40% (4.08 ± 1.00) × 10^-3 (P < 0.001). The mean Cho/water of EC with deep and superficial myometrial invasion was (3.41 ± 1.26) × 10^-3 and (2.43 ± 1.11) × 10^-3, respectively (P = 0.011). There was no significant difference in Cho/water between type I EC with and without cervical invasioin ([2.68 ± 1.00] × 10^-3 and [2.77 ± 1.28] × 10^-3, P = 0.866). The mean Cho/water of type I EC with and without lymph node metastasis was (4.02 ± 1.90) × 10^-3 and (2.60 ± 1.06) × 10^-3, respectively (P = 0.014). The Cho/water was positively correlated with the Ki-67 SI (r = 0.701, P < 0.001). There were no significant differences in ADC among groups (all P > 0.05).

CONCLUSION

MRS is helpful for preoperative assessment of clinicopathological features of type I EC.

Imaging biomarkers for evaluating tumor response: RECIST and beyond

Response Evaluation Criteria in Solid Tumors (RECIST) is the gold standard for assessment of treatment response in solid tumors. Morphologic change of tumor size evaluated by RECIST is often correlated with survival length and has been considered as a surrogate endpoint of therapeutic efficacy. However, the detection of morphologic change alone may not be sufficient for assessing response to new anti-cancer medication in all solid tumors. During the past fifteen years, several molecular-targeted therapies and immunotherapies have emerged in cancer treatment which work by disrupting signaling pathways and inhibited cell growth. Tumor necrosis or lack of tumor progression is associated with a good therapeutic response even in the absence of tumor shrinkage. Therefore, the use of unmodified RECIST criteria to estimate morphological changes of tumor alone may not be sufficient to estimate tumor response for these new anti-cancer drugs. Several studies have reported the low reliability of RECIST in evaluating treatment response in different tumors such as hepatocellular carcinoma, lung cancer, prostate cancer, brain glioma, bone metastasis, and lymphoma. There is an increased need for new medical imaging biomarkers, considering the changes in tumor viability, metabolic activity, and attenuation, which are related to early tumor response. Promising imaging techniques, beyond RECIST, include dynamic contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI), diffusion-weight imaging (DWI), magnetic resonance spectroscopy (MRS), and ¹⁸ F-fluorodeoxyglucose (FDG) positron emission tomography (PET). This review outlines the current RECIST with their limitations and the new emerging concepts of imaging biomarkers in oncology.

Clinical value of N-acetyl mucinous compounds and lipid peaks in differentiating benign and malignant ovarian mucinous tumors by MR spectroscopy

PURPOSE

To retrospectively evaluate the clinical significance of the peaks of N-acetyl mucinous compounds (NAMC) at 2 ppm and lipid at 1.3 ppm in in-vivo proton magnetic resonance (MR) spectroscopy for distinguishing benign and malignant mucinous tumors in patients with ovarian masses.

METHODS

MR spectroscopy was performed in patients with pathologically diagnosed mucinous ovarian tumors at 3 T MRI system. The peaks of NAMC, lipid, and total choline compounds (tCho) were classified into three classes in comparison with the noise level by visual estimation. The NAMC concentration was quantified relative to unsuppressed water by using LCModel analysis.

RESULTS

A total of 27 ovarian mucinous tumors in 27 patients were included in this study. The NAMC peak was observed in all 27 mucinous tumors, and the lipid peak was observed in 14 of 27 tumors: 1 of 9 benign tumors (11%), and 13 of 18 malignant tumors (11 borderline malignancies and 7 carcinomas) (72%). The presence of the lipid peak for the diagnosis of malignant mucinous tumor showed generally better diagnostic ability than MR imaging, with a sensitivity of 72%, specificity of 89%, accuracy of 78%, PPV of 93%, and NPV of 62%. The concentration of the NAMC in malignant mucinous tumors tended to be higher than that in benign mucinous tumors, but there was no statistically significant difference.

CONCLUSIONS

The bimodal peaks of NAMC and lipid are suggestive of malignant mucinous tumors, and the presence of the lipid peak may be useful in distinguishing benign from malignant ovarian mucinous tumors.

A Diagnostic Algorithm using Multi-parametric MRI to Differentiate Benign from Malignant Myometrial Tumors: Machine-Learning Method

This study aimed to develop a diagnostic algorithm for preoperative differentiating uterine sarcoma from leiomyoma through a supervised machine-learning method using multi-parametric MRI. A total of 65 participants with 105 myometrial tumors were included: 84 benign and 21 malignant lesions (belonged to 51 and 14 patients, respectively; based on their postoperative tissue diagnosis). Multi-parametric MRI including T1-, T2-, and diffusion-weighted (DW) sequences with ADC-map, contrast-enhanced images, as well as MR spectroscopy (MRS), was performed for each lesion. Thirteen singular MRI features were extracted from the mentioned sequences. Various combination sets of selective features were fed into a machine classifier (coarse decision-tree) to predict malignant or benign tumors. The accuracy metrics of either singular or combinational models were assessed. Eventually, two diagnostic algorithms, a simple decision-tree and a complex one were proposed using the most accurate models. Our final simple decision-tree obtained accuracy = 96.2%, sensitivity = 100% and specificity = 95%; while the complex tree yielded accuracy, sensitivity and specificity of 100%. To summarise, the complex diagnostic algorithm, compared to the simple one, can differentiate tumors with equal sensitivity, but a higher specificity and accuracy. However, it needs some further time-consuming modalities and difficult imaging calculations. Trading-off costs and benefits in appropriate situations must be determinative.

A machine learning approach for distinguishing uterine sarcoma from leiomyomas based on perfusion weighted MRI parameters

PURPOSE

To propose a computer-assisted method for distinguishing uterine sarcoma from leiomyomas based on perfusion weighted magnetic resonance imaging (PWI).

MATERIALS AND METHODS

Forty-two women confirmed to have a total of 60 masses (10 uterine sarcomas and 50 benign leiomyomas) were included. The reference diagnosis was based on postoperative histopathological examination. All women underwent the standard MRI protocol with 3-Tesla MR imager (Magnetom Trio, Siemens, Erlangen, Germany) for assessment of myometrial masses, followed by PWI. For each mass, two regions of interest (ROI) were outlined manually by an experienced radiologist; one (ROI_L) represented the entire tumor while the other (ROIs) was placed on the area of the lesion with the most marked contrast enhancement. Two additional ROI_s with diameters similar to ROI_s (3.0 to 3.1 mm) were placed on psoas muscle (ROI_P) and myometrium (ROI_M) in order to provide baselines for comparisons. The obtained ROIs of PWI images were then analyzed using the DCE Tool plug-in (version 2.0SP1) within ClearCanvas (Toronto, Ontario, Canada) framework. The DCE Tool provides seven parameters (K^trans, k_ep, V_b, IAUC, initial slope, peak, the mean squared error) for modelling contrast uptake within an ROI using the modified Tofts model. Parameters extracted from the ROIs were fed into a decision tree ensemble, which classified the corresponding lesions either as malignant or benign. The leave-one-out cross validation (LOOCV) was utilized to evaluate the performance of the classifier.

RESULTS

None of the parameters extracted from ROI_L or ROI_s differed significantly between uterine sarcoma and benign leiomyomas (all p > 0.05). The overall accuracy of 66.7% was obtained by feeding seven parameters extracted from ROI_L to the classifier. When 21 features extracted from ROI_L, ROI_M, and ROI_P were fed into the classifier an accuracy of 91.7%, sensitivity of 100%, and specificity of 90% were achieved in the optimal operating point of classifier.

CONCLUSION

Although none of the PWI parameters differed significantly between benign and malignant lesions, when the information provided by the extracted features was aggregated using a machine learning method, a promising discriminative power was obtained. This suggests that the proposed model for combining the PWI parameters is potentially useful for differentiating uterine sarcoma from leiomyomas.

Uterine Leiomyosarcoma: Can MRI Differentiate Leiomyosarcoma From Benign Leiomyoma Before Treatment?

OBJECTIVE

The purpose of this article is to provide background on the epidemiologic, clinical, and economic impact of uterine leiomyomas, summarize the concerns associated with treating women with potential occult leiomyosarcomas (LMSs), and review the known and emerging imaging features of typical and atypical leiomyomas and explain how to differentiate them from LMSs.

CONCLUSION

Surgical management of presumed benign uterine leiomyomas received popular media attention when a case of disseminated LMS occurred after laparoscopic power morcellator-assisted hysterectomy. A subsequent U.S. Food and Drug Administration review found a higher prevalence of unsuspected uterine sarcoma and LMS among patients undergoing myomectomy or hysterectomy for presumed benign leiomyomas than was previously reported. This heightened concern has led to increased pressure on radiologists to distinguish LMSs from leiomyomas.

In vivo MR spectroscopy predicts high tumor grade in endometrial cancer

Background In vivo magnetic resonance spectroscopy (MRS) enables non-invasive measurements of tumor metabolites. Choline-containing metabolites play a key role in tumor metabolism. Purpose To explore whether preoperative MRS-derived tumor choline levels are associated with clinical and histological features in endometrial carcinomas. Material and Methods Preoperative pelvic magnetic resonance imaging (MRI) (1.5T), including structural and diffusion-weighted imaging and localized multivoxel proton MR (1H-MR) spectroscopy, was performed in 77 prospectively included patients with histologically confirmed endometrial carcinomas. Relative levels of total choline-containing metabolites (tCho) in tumor and myometrium were measured using the ratios: tCho/Creatine; tCho/Water; and tCho/Noise. MRS parameters were analyzed in relation to histological subtype and grade, surgicopathological staging parameters, MRI-measured tumor volume, and tumor apparent diffusion coefficient (ADC) value and clinical outcome. Results Tumor tissue had significantly higher ratios for tCho/Creatine, tCho/Water, and tCho/Noise than normal myometrial tissue ( P < 0.001 for all). High tumor tCho/Water ratio was significantly associated with high tumor grade in endometrioid tumors ( P = 0.02). Tumor tCho/Creatine ratio was positively correlated to MRI-measured tumor volume (r_s = 0.25; P = 0.03). Conclusion High choline levels in tumor are associated with high-risk features. In vivo MRS may potentially aid in the preoperative risk stratification in endometrial cancer.

Magnetic Resonance Spectroscopy and its Clinical Applications: A Review

In vivo NMR spectroscopy is known as magnetic resonance spectroscopy (MRS). MRS has been applied as both a research and a clinical tool in order to detect visible or nonvisible abnormalities. The adaptability of MRS allows a technique that can probe a wide variety of metabolic uses across different tissues. Although MRS is mostly applied for brain tissue, it can be used for detection, localization, staging, tumour aggressiveness evaluation, and tumour response assessment of breast, prostate, hepatic, and other cancers. In this article, the medical applications of MRS in the brain, including tumours, neural and psychiatric disorder studies, breast, prostate, hepatic, gastrointestinal, and genitourinary investigations have been reviewed.

Proton magnetic resonance spectroscopy in oncology: the fingerprints of cancer?

Abnormal metabolism is a key tumor hallmark. Proton magnetic resonance spectroscopy (1H-MRS) allows measurement of metabolite concentration that can be utilized to characterize tumor metabolic changes. 1H-MRS measurements of specific metabolites have been implemented in the clinic. This article performs a systematic review of image acquisition and interpretation of 1H-MRS for cancer evaluation, evaluates its strengths and limitations, and correlates metabolite peaks at 1H-MRS with diagnostic and prognostic parameters of cancer in different tumor types.

Carcinosarcoma of the uterus: MRI findings including diffusion-weighted imaging and MR spectroscopy

BACKGROUND

Recently carcinosarcoma has become regarded as a subset of endometrial carcinoma. Because the clinical course of carcinosarcoma is aggressive with poor prognosis, it should be differentiated from endometrial carcinomas for the appropriate surgical management and adjuvant therapy.

PURPOSE

To clarify the magnetic resonance imaging (MRI) characteristics of uterine carcinosarcoma including diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) measurement and MR spectroscopy (MRS) with quantitative metabolite evaluation.

MATERIAL AND METHODS

MRI findings of 12 pathologically diagnosed uterine carcinosarcomas obtained on 3T MRI were retrospectively evaluated. The mean and minimum ADCs, and the lipid and choline concentration levels were compared with those of pathologically diagnosed 38 endometrial carcinomas.

RESULTS

The mean and minimum ADCs in carcinosarcomas and endometrial carcinomas were not significantly different. The mean ADC of carcinosarcomas was significantly higher than that of higher grade (G2 and G3) endometrial carcinomas. The choline concentration in carcinosarcomas was significantly lower than that in endometrial carcinomas. High lipid peak was observed in 91% of carcinosarcomas and in 24% of endometrial carcinomas.

CONCLUSION

Large, exophytic heterogeneous endometrial mass containing strongly enhanced areas, which may exhibit "tumor delivery", is a suggestive of carcinosarcoma. Relatively high mean ADC and low choline concentration considering its highly malignant nature due to intra-tumoral heterogeneity with necrosis and epithelial cystic components, and the presence of necrosis-associated high lipid peak may be compatible with carcinosarcoma.

MR Spectra of Normal Adult Testes and Variations with Age: Preliminary Observations

OBJECTIVES

The aim was to determine the proton MR (1H-MR) spectra of normal adult testes and variations with age.

METHODS

Forty-one MR spectra of normal testes, including 16 testes from men aged 20-39 years (group I) and 25 testes from men aged 40-69 years (group II), were analyzed. A single-voxel point-resolved spectroscopy sequence (PRESS), with TR/TE: 2000/25 ms was used. The volume of interest was placed to include the majority of normal testicular parenchyma. Association between normalized metabolite concentrations, defined as ratios of the calculated metabolite concentrations relative to creatine concentration, and age was assessed.

RESULTS

Quantified metabolites of the spectra were choline (Cho), creatine (Cr), myo-inositol (mI), scyllo-inositol, taurine, lactate, GLx compound, glucose, lipids, and macromolecules resonating at 0.9 ppm (LM09), around 20 ppm (LM20), and at 13 ppm (LM13). Most prominent peaks were Cho, Cr, mI, and lipids. A weak negative correlation between mI and age (P = 0.015) was observed. Higher normalized concentrations of Cho (P = 0.03), mI (P = 0.08), and LM13 (P = 0.05) were found in group I than in group II.

CONCLUSIONS

1H-MR spectra of a normal adult testis showed several metabolite peaks. A decrease of levels of Cho, mI, and LM13 was observed with advancing age.

KEY POINTS

• Single-voxel PRESS MRS of a normal testis is feasible. • 1H-MR spectra of a normal testis showed several metabolite peaks. • Most prominent peaks were Cho, Cr, mI, and lipids. • A decrease of Cho, mI, and LM13 was seen with advancing age.

Can the signal-to-noise ratio of choline in magnetic resonance spectroscopy reflect the aggressiveness of endometrial cancer?

RATIONALE AND OBJECTIVES

To differentiate endometrial cancer (ECa) from benign lesions in endometrial or in submucosa (BLs-ESm), and investigate whether the signal-to-noise ratio (SNR) of choline-containing compounds (Cho) obtained from three-dimensional (1)H magnetic resonance spectroscopy (MRS) is associated with the aggressiveness of ECa.

MATERIALS AND METHODS

Thirty-three patients with ECa and 15 patients with BLs-ESm underwent preoperative multivoxel (1)H MRS at 3 T MR. The amplitude of Cho peak of each voxel was recorded, and the corresponding SNR of Cho peak (ChoSNR) was calculated. The maximum ChoSNR (max ChoSNR) for each lesion was identified. The max ChoSNR of ECa and BLs-ESm, as well as type I ECa and type II ECa, was compared. The relationship between max ChoSNR and pathologic characteristics of tumors, including tumor grade, stage, type, and tumor size, was analyzed.

RESULTS

The mean max ChoSNR (±standard deviation [SD]) was 30.93 ± 16.89 for ECa and 10.40 ± 3.07 for BLs-ESm (P < .001). The mean max ChoSNR for type II ECa (48.54 ± 21.46) was higher than that for type I ECa (26.19 ± 12.02, P = .001). There were no significant differences among different grades (P = .449). The Spearman coefficient between max ChoSNR and stage was 0.423 (P = .014); the difference existed only between Ia and III ECa (P = .048). The Pearson coefficient between ChoSNR and tumor size was 0.515 (P = .002).

CONCLUSIONS

The max ChoSNR obtained from MRS can differentiate ECa from BLs and type I ECa and type II ECa, but cannot differentiate between each grade ECa and each International Federation of Gynecology and Obstetrics stage ECa. However, max ChoSNR increased with the increase in International Federation of Gynecology and Obstetrics stage and size of ECa.

Advanced MRI in malignant neoplasms of the uterus

Conventional magnetic resonance imaging (MRI) such as T1-weighted and T2-weighted images of the female pelvis provide morphological information with excellent tissue contrast, which reflects the pathology of malignant diseases of the uterus. Owing to the recent improvement in hardware and software, in combination with extensive research in imaging techniques, not only MRI at higher magnetic field was facilitated, but also insight into tumor pathophysiology was provided. These methods include diffusion-weighted imaging (DWI), dynamic contrast-enhanced MRI (DCE-MRI) with pharmacokinetic analysis, and MR spectroscopy (MRS). The application of these techniques is expanding from the brain to the body because information on the tissue microenvironment and cytoarchitecture is helpful for lesion characterization, evaluation of treatment response after chemotherapy or radiation, differentiating posttherapeutic changes from residual active tumor, and for detecting recurrent cancer. These techniques may provide clues to optimize the treatment of patients with malignant diseases of the uterus. In the first half of this article we provide an overview of the technical aspects of MRI of the female pelvis, especially focusing on the state-of-the-art techniques such as 3 T MRI, DCE-MRI, DWI, etc. For the latter half we review the clinical aspects of these newly developed techniques, focusing on how these techniques are applicable, what has been revealed with respect to clinical impact, and the remaining problems.