Ovarian teratomas include mature cystic teratomas (dermoid cysts), immature teratomas, and monodermal teratomas (eg, struma ovarii, carcinoid tumors, neural tumors). Most mature cystic teratomas can be diagnosed at ultrasonography (US) but may have a variety of appearances, characterized by echogenic sebaceous material and calcification. At computed tomography (CT), fat attenuation within a cyst is diagnostic. At magnetic resonance (MR) imaging, the sebaceous component is specifically identified with fat-saturation techniques. The US appearances of immature teratoma are nonspecific, although the tumors are typically heterogeneous, partially solid lesions, usually with scattered calcifications. At CT and MR imaging, immature teratomas characteristically have a large, irregular solid component containing coarse calcifications. Small foci of fat help identify these tumors. The US features of struma ovarii are also nonspecific, but a heterogeneous, predominantly solid mass may be seen. On T1- and T2-weighted images, the cystic spaces demonstrate both high and low signal intensity. Familiarity with the US, CT, and MR imaging features of ovarian teratomas can aid in differentiation and diagnosis.

Leiomyomas are the most common uterine neoplasm and are composed of smooth muscle with varying amounts of fibrous connective tissue. As leiomyomas enlarge, they may outgrow their blood supply, resulting in various types of degeneration: hyaline or myxoid degeneration, calcification, cystic degeneration, and red degeneration. Leiomyomas are classified as submucosal, intramural, or subserosal; the latter may become pedunculated and simulate ovarian neoplasms. Although most leiomyomas are asymptomatic, patients may present with abnormal uterine bleeding, pressure on adjacent organs, pain, infertility, or a palpable abdominalpelvic mass. Magnetic resonance (MR) imaging is the most accurate imaging technique for detection and localization of leiomyomas. On T2-weighted images, nondegenerated leiomyomas appear as well-circumscribed masses of decreased signal intensity; however, cellular leiomyomas can have relatively higher signal intensity on T2-weighted images and demonstrate enhancement on contrast material-enhanced images. Degenerated leiomyomas have variable appearances on T2-weighted images and contrast-enhanced images. The differential diagnosis of leiomyomas includes adenomyosis, solid adnexal mass, focal myometrial contraction, and uterine leiomyosarcoma. For patients with symptoms, medical or surgical treatment may be indicated. MR imaging also has a role in treatment of leiomyomas by assisting in surgical planning and monitoring the response to medical therapy.

Adnexal masses present a special diagnostic challenge, in part because benign adnexal masses greatly outnumber malignant ones. Determination of a degree of suspicion for malignancy is critical and is based largely on imaging appearance. Endovaginal ultrasonography (US) is the most practical modality for assessment of ovarian tumors because it is readily available and has a high negative predictive value. Morphologic analysis of adnexal masses is accurate for identifying masses as either low risk or high risk. The most important morphologic features are non-fatty solid (vascularized) tissue, thick septations, and papillary projections. Color Doppler US helps identify solid, vascularized components in a mass. Spectral Doppler waveform characteristics (eg, resistive index, pulsatility index) correlate well with malignancy but generally add little information to morphologic considerations. Computed tomography can help assess the extent of disease in patients before and after primary cytoreductive surgery. Magnetic resonance (MR) imaging is better reserved for problem solving when US findings are nondiagnostic or equivocal because, although it is more accurate for diagnosis, it is also more expensive. The signal intensity characteristics of ovarian masses make possible a systematic approach to diagnosis. Mature cystic teratomas, cysts, endometriomas, leiomyomas, fibromas, and other lesions can be accurately diagnosed on the basis of T1-weighted, T2-weighted, and fat-saturated T1-weighted MR imaging findings.

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The goal of oncology is the individualization of patient care to optimize therapeutic responses and minimize toxicities. Achieving this will require noninvasive, quantifiable, and early markers of tumor response. Preclinical data from xenografted tumors using a variety of antitumor therapies have shown that magnetic resonance imaging (MRI)-measured mobility of tissue water (apparent diffusion coefficient of water, or ADCw) is a biomarker presaging cell death in the tumor. This communication tests the hypothesis that changes in water mobility will quantitatively presage tumor responses in patients with metastatic liver lesions from breast cancer. A total of 13 patients with metastatic breast cancer and 60 measurable liver lesions were monitored by diffusion MRI after initiation of new courses of chemotherapy. MR images were obtained prior to, and at 4, 11, and 39 days following the initiation of therapy for determination of volumes and ADCw values. The data indicate that diffusion MRI can predict response by 4 or 11 days after commencement of therapy, depending on the analytic method. The highest concordance was observed in tumor lesions that were less than 8 cm3 in volume at presentation. These results suggest that diffusion MRI can be useful to predict the response of liver metastases to effective chemotherapy.

Ferumoxtran 10-enhanced MR imaging was safe and effective and facilitated improved diagnostic performance. Use of iron oxide-enhanced MR imaging increased the positive predictive value by 20% and the accuracy by 14% compared with reader assessment. Differentiating patients with no nodal metastatic involvement was more reliable with ferumoxtran 10-enhanced MR imaging than with precontrast MR imaging.

Overexpression of the HMGA2 gene is a common feature of neoplastic cells both in experimental and human models. Intragenic and extragenic HMGA2 rearrangements responsible for HMGA2 gene overexpression have been frequently detected in human benign tumours of mesenchymal origin. To better understand the role of HMGA2 overexpression in human tumorigenesis, we have generated transgenic mice carrying the HMGA2 gene under the transcriptional control of the cytomegalovirus promoter. High expression of the transgene was demonstrated in all the mouse tissues analysed, whereas no expression of the endogenous HMGA2 gene was detected in the same tissues from wild-type mice. In this study, two indipendent lines of transgenic mice have been generated. By 6 months of age, 85% of female animals of both transgenic lines developed pituitary adenomas secreting prolactin and growth hormone. The transgenic males developed the same phenotype with a lower penetrance (40%) and a longer latency period (about 18 months). Therefore, these data demonstrate that the overexpression of HMGA2 leads to the onset of mixed growth hormone/ prolactin cell pituitary adenomas. These transgenic mice may represent an important tool for the study of this kind of neoplasia.

Assessing skeletal muscle mass (SMM) is critical in studying and detecting sarcopenia. Direct measurements by MRI or computerized tomography are expensive or high in radiation exposure. Dual-energy X-ray absorptiometry (DXA) is promising for body composition assessments, but the validity of DXA for predicting SMM in the elderly is still under investigation. The objective of this study was to assess the relationship between DXA-derived measurements of lean soft tissue mass (LSTM) and SMM in older women. Study participants were postmenopausal women (n = 101) recruited in southern Arizona. Total and regional body composition was measured using MRI and DXA (QDR4500w). The participants' mean age was 70.7 +/- 6.4 y and their mean BMI was 27.4 +/- 5.1 kg/m2. DXA-derived LSTM was highly correlated with MRI-derived SMM for the whole body (r = 0.94; P < 0.001) and leg region (r = 0.91; P < 0.001). In multivariate models, adjusting for age and DXA-derived percent fat slightly increased the amount of variance in SMM that can be explained by the DXA-derived LSTM assessments for the leg region but not for the total body. In conclusion, although the relationships between DXA measures and MRI-derived SMM vary by region of interest, the overall prediction of SMM by DXA is excellent. We conclude that DXA is a reliable method for cross-sectional assessments of SMM in older women.