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Preclinical evidence suggests that inter-individual variation in the structure of the hypothalamus at birth is associated with variation in the intrauterine environment, with downstream implications for future disease susceptibility. However, scientific advancement in humans is limited by a lack of validated methods for the automatic segmentation of the newborn hypothalamus. N = 215 healthy full-term infants with paired T1-/T2-weighted MR images across four sites were considered for primary analyses (mean postmenstrual age = 44.3 ± 3.5 weeks, nmale /nfemale  = 110/106). The outputs of FreeSurfers hypothalamic subunit segmentation tools designed for adults (segFS) were compared against those of a novel registration-based pipeline developed here (segATLAS) and against manually edited segmentations (segMAN) as reference. Comparisons were made using Dice Similarity Coefficients (DSCs) and through expected associations with postmenstrual age at scan. In addition, we aimed to demonstrate the validity of the segATLAS pipeline by testing for the stability of inter-individual variation in hypothalamic volume across the first year of life (n = 41 longitudinal datasets available). SegFS and segATLAS segmentations demonstrated a wide spread in agreement (mean DSC = 0.65 ± 0.14 SD; range = {0.03-0.80}). SegATLAS volumes were more highly correlated with postmenstrual age at scan than segFS volumes (n = 215 infants; RsegATLAS 2  = 65% vs. RsegFS 2  = 40%), and segATLAS volumes demonstrated a higher degree of agreement with segMAN reference segmentations at the whole hypothalamus (segATLAS DSC = 0.89 ± 0.06 SD; segFS DSC = 0.68 ± 0.14 SD) and subunit levels (segATLAS DSC = 0.80 ± 0.16 SD; segFS DSC = 0.40 ± 0.26 SD). In addition, segATLAS (but not segFS) volumes demonstrated stability from near birth to ~1 years age (n = 41; R2  = 25%; p

Preclinical evidence suggests that inter‐individual variation in the structure of the hypothalamus at birth is associated with variation in the intrauterine environment, with downstream implications for future disease susceptibility. However, scientific advancement in humans is limited by a lack of validated methods for the automatic segmentation of the newborn hypothalamus. N = 215 healthy full‐term infants with paired T1‐/T2‐weighted MR images across four sites were considered for primary analyses (mean postmenstrual age = 44.3 ± 3.5 weeks, nmale/nfemale = 110/106). The outputs of FreeSurfer's hypothalamic subunit segmentation tools designed for adults (segFS) were compared against those of a novel registration‐based pipeline developed here (segATLAS) and against manually edited segmentations (segMAN) as reference. Comparisons were made using Dice Similarity Coefficients (DSCs) and through expected associations with postmenstrual age at scan. In addition, we aimed to demonstrate the validity of the segATLAS pipeline by testing for the stability of inter‐individual variation in hypothalamic volume across the first year of life (n = 41 longitudinal datasets available). SegFS and segATLAS segmentations demonstrated a wide spread in agreement (mean DSC = 0.65 ± 0.14 SD; range = {0.03–0.80}). SegATLAS volumes were more highly correlated with postmenstrual age at scan than segFS volumes (n = 215 infants; RsegATLAS2 = 65% vs. RsegFS2 = 40%), and segATLAS volumes demonstrated a higher degree of agreement with segMAN reference segmentations at the whole hypothalamus (segATLAS DSC = 0.89 ± 0.06 SD; segFS DSC = 0.68 ± 0.14 SD) and subunit levels (segATLAS DSC = 0.80 ± 0.16 SD; segFS DSC = 0.40 ± 0.26 SD). In addition, segATLAS (but not segFS) volumes demonstrated stability from near birth to ~1 years age (n = 41; R2 = 25%; p < 10−3). These findings highlight segATLAS as a valid and publicly available (https://github.com/jerodras/neonate%5fhypothalamus%5fseg) pipeline for the segmentation of hypothalamic subunits using human newborn MRI up to 3 months of age collected at resolutions on the order of 1 mm isotropic. Because the hypothalamus is traditionally understudied due to a lack of high‐quality segmentation tools during the early life period, and because the hypothalamus is of high biological relevance to human growth and development, this tool may stimulate developmental and clinical research by providing new insight into the unique role of the hypothalamus and its subunits in shaping trajectories of early life health and disease. [ABSTRACT FROM AUTHOR]

Background and Purpose: Pituitary macroadenomas and meningiomas are common neoplasms arising within the cavernous sinus. Imaging characteristics on MRI can often distinguish these tumors from one another; however, some cases may be more difficult to differentiate. This study compares patterns of cavernous segment internal carotid artery (CS‐ICA) stenosis between the two tumor types to establish a novel radiographic method of differentiation. Methods: A retrospective analysis of patients with pathology‐confirmed meningioma and pituitary adenomas at Tufts Medical Center was performed. The diameter of the CS‐ICA at the narrowest point within the cavernous sinus was measured and compared to the ipsilateral petrous segment ICA and contralateral CS‐ICA. The mean and range of percent stenosis and frequency of cases of CS‐ICA stenosis >15% were determined. Statistical analysis to compare the groups was conducted using the Chi‐squared test, Fisher's exact test, and t‐test. Results: There were a total of 78 out of 231 patients who were included in the study. The mean % ICA stenosis for all meningiomas was 9.3%, with increasing stenosis with increasing World Health Organization grade. Of all meningioma cases, 13 (33%) had greater than 15% ICA stenosis. Mean ICA stenosis for pituitary adenomas was –1.48%. There were no cases of pituitary adenomas causing ICA stenosis >15%. Conclusions: Differentiating pituitary adenomas and intracavernous meningioma tumors can have important implications on surgical approach and outcome. Our study found that stenosis of the CS‐ICA greater than 15% is highly specific to meningiomas and can serve as a radiologic sign to distinguish between these two tumors. [ABSTRACT FROM AUTHOR]

Systemic immunoglobulin light-chain primary amyloidosis (AL) is the most common type of systemic amyloidosis. Recent advances in AL amyloidosis include the use of definitive proteomic typing, confirming the type of amyloid in patients with two possible amyloid-forming proteins. Laser microdissection followed by mass spectrometry (LMD/MS) can correctly identify the amyloid type with over 95% sensitivity and specificity. We report the case of a 68-year-old man with a history of IgA lambda monoclonal gammopathy and peripheral neuropathy who was diagnosed with pelvic nodal and psoas amyloidosis. The amyloid was found to be AL kappa type by LMD/MS. While LMD/MS has been effective in distinguishing among AL, secondary amyloidosis and hereditary forms of amyloidosis, our case demonstrates that typing can also identify unusual instances of discordance between light chain isotypes associated with clonal processes. [ABSTRACT FROM AUTHOR]