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1.
AJNR Am J Neuroradiol ; 44(1): 82-90, 2023 01.
Article in English | MEDLINE | ID: mdl-36549845

ABSTRACT

BACKGROUND AND PURPOSE: Fetal brain MR imaging interpretations are subjective and require subspecialty expertise. We aimed to develop a deep learning algorithm for automatically measuring intracranial and brain volumes of fetal brain MRIs across gestational ages. MATERIALS AND METHODS: This retrospective study included 246 patients with singleton pregnancies at 19-38 weeks gestation. A 3D U-Net was trained to segment the intracranial contents of 2D fetal brain MRIs in the axial, coronal, and sagittal planes. An additional 3D U-Net was trained to segment the brain from the output of the first model. Models were tested on MRIs of 10 patients (28 planes) via Dice coefficients and volume comparison with manual reference segmentations. Trained U-Nets were applied to 200 additional MRIs to develop normative reference intracranial and brain volumes across gestational ages and then to 9 pathologic fetal brains. RESULTS: Fetal intracranial and brain compartments were automatically segmented in a mean of 6.8 (SD, 1.2) seconds with median Dices score of 0.95 and 0.90, respectively (interquartile ranges, 0.91-0.96/0.89-0.91) on the test set. Correlation with manual volume measurements was high (Pearson r = 0.996, P < .001). Normative samples of intracranial and brain volumes across gestational ages were developed. Eight of 9 pathologic fetal intracranial volumes were automatically predicted to be >2 SDs from this age-specific reference mean. There were no effects of fetal sex, maternal diabetes, or maternal age on intracranial or brain volumes across gestational ages. CONCLUSIONS: Deep learning techniques can quickly and accurately quantify intracranial and brain volumes on clinical fetal brain MRIs and identify abnormal volumes on the basis of a normative reference standard.


Subject(s)
Deep Learning , Imaging, Three-Dimensional , Pregnancy , Female , Humans , Gestational Age , Imaging, Three-Dimensional/methods , Retrospective Studies , Brain/diagnostic imaging
3.
J Surg Oncol ; 54(3): 193-8, 1993 Nov.
Article in English | MEDLINE | ID: mdl-8412179

ABSTRACT

Salivary duct carcinoma is an uncommon malignant tumor that occurs mainly in the parotid gland of elderly men. The 11 cases of salivary duct carcinoma which are included in this study occurred in older men (mean age 56 years) and were located in the parotid (7), submandibular salivary gland (2), and the minor salivary glands in the maxilla (2). The maximum tumor dimension ranged from 3 to 9 cm. Microscopically, all had infiltrating margins, with circumscribed groups of epithelial cells arranged in various patterns; the invasive component was embedded in a desmoplastic stroma. Perineural invasion and lymph node metastasis were noted in seven and three cases, respectively, at the time of initial surgery. Radical surgery was offered to ten patients and postoperative radiotherapy to nine patients. Salivary duct carcinoma appears to be an aggressive tumor with distinctive histological features, which has not been described in the minor salivary glands of the maxilla to date. The clinicopathologic features of these tumors are presented, with a review of the literature.


Subject(s)
Adenocarcinoma/pathology , Salivary Gland Neoplasms/pathology , Adenocarcinoma/therapy , Adult , Aged , Aged, 80 and over , Humans , Male , Middle Aged , Salivary Gland Neoplasms/therapy
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