Fibroid location, volume, number, T1- and T2-weighted signal intensity, and enhancement provide important pretreatment information [25,62-65]. Intracavitary fibroids may be amenable to hysteroscopic resection, whereas submucosal, intramural, and broad-based subserosal fibroids are amenable to UFE. Cervical fibroids may not respond as well or have a durable response to embolization. Submucosal and intramural fibroids that contact the endometrium may be expelled following successful UFE in 2.2% to 7.7% of cases [1,25,66]. Pedunculated fibroids, depending on location and stalk caliber, may be treated hysteroscopically, laparoscopically, or with UFE [25]. Postcontrast imaging allows assessment of fibroid viability, uterine artery anatomy, and detection of ovarian arterial collateral supply to the uterus [67-71]. Nonviable/autoinfarcted fibroids, found in up to 20% of UFE candidates, do not respond to UFE and are therefore important to identify at time of treatment planning [71]. A meta-analysis on the utility of ADC values concluded that, because of heterogeneity, it is unclear whether ADC values are useful to predict UFE response [72]. Conventional MRI, however, cannot accurately differentiate fibroids from sarcomas, a critical distinction for surgical planning and optimizing outcomes [31-33]. Diffusion-weighted imaging with ADC, especially when Fibroids incorporated into an MRI algorithm, has shown promising results in distinguishing the two entities [20,34-40]. In a large, case-controlled retrospective study of women with atypical uterine masses, a diagnostic algorithm based on enlarged lymph nodes, peritoneal implants, high diffusion MRI signal, and low ADC values was developed and validated. The resulting algorithm achieved a 98% sensitivity and a 96% specificity in the training set and 83% to 88% sensitivity and 97% to 100% specificity in the validation sets [34]. Machine learning with texture analysis is under investigation and may have the potential to improve diagnostic accuracy [20].
Fibroids. Fibroid location, volume, number, T1- and T2-weighted signal intensity, and enhancement provide important pretreatment information [25,62-65]. Intracavitary fibroids may be amenable to hysteroscopic resection, whereas submucosal, intramural, and broad-based subserosal fibroids are amenable to UFE. Cervical fibroids may not respond as well or have a durable response to embolization. Submucosal and intramural fibroids that contact the endometrium may be expelled following successful UFE in 2.2% to 7.7% of cases [1,25,66]. Pedunculated fibroids, depending on location and stalk caliber, may be treated hysteroscopically, laparoscopically, or with UFE [25]. Postcontrast imaging allows assessment of fibroid viability, uterine artery anatomy, and detection of ovarian arterial collateral supply to the uterus [67-71]. Nonviable/autoinfarcted fibroids, found in up to 20% of UFE candidates, do not respond to UFE and are therefore important to identify at time of treatment planning [71]. A meta-analysis on the utility of ADC values concluded that, because of heterogeneity, it is unclear whether ADC values are useful to predict UFE response [72]. Conventional MRI, however, cannot accurately differentiate fibroids from sarcomas, a critical distinction for surgical planning and optimizing outcomes [31-33]. Diffusion-weighted imaging with ADC, especially when Fibroids incorporated into an MRI algorithm, has shown promising results in distinguishing the two entities [20,34-40]. In a large, case-controlled retrospective study of women with atypical uterine masses, a diagnostic algorithm based on enlarged lymph nodes, peritoneal implants, high diffusion MRI signal, and low ADC values was developed and validated. The resulting algorithm achieved a 98% sensitivity and a 96% specificity in the training set and 83% to 88% sensitivity and 97% to 100% specificity in the validation sets [34]. Machine learning with texture analysis is under investigation and may have the potential to improve diagnostic accuracy [20].