The incidence of thyroid cancer is rising steadily because of overdiagnosis and overtreatment conferred by widespread use of sensitive imaging techniques for screening. This overall incidence growth ...is especially driven by increased diagnosis of indolent and well-differentiated papillary subtype and early-stage thyroid cancer, whereas the incidence of advanced-stage thyroid cancer has increased marginally. Thyroid ultrasound is frequently used to diagnose thyroid cancer. The aim of this study was to use deep convolutional neural network (DCNN) models to improve the diagnostic accuracy of thyroid cancer by analysing sonographic imaging data from clinical ultrasounds.
We did a retrospective, multicohort, diagnostic study using ultrasound images sets from three hospitals in China. We developed and trained the DCNN model on the training set, 131 731 ultrasound images from 17 627 patients with thyroid cancer and 180 668 images from 25 325 controls from the thyroid imaging database at Tianjin Cancer Hospital. Clinical diagnosis of the training set was made by 16 radiologists from Tianjin Cancer Hospital. Images from anatomical sites that were judged as not having cancer were excluded from the training set and only individuals with suspected thyroid cancer underwent pathological examination to confirm diagnosis. The model's diagnostic performance was validated in an internal validation set from Tianjin Cancer Hospital (8606 images from 1118 patients) and two external datasets in China (the Integrated Traditional Chinese and Western Medicine Hospital, Jilin, 741 images from 154 patients; and the Weihai Municipal Hospital, Shandong, 11 039 images from 1420 patients). All individuals with suspected thyroid cancer after clinical examination in the validation sets had pathological examination. We also compared the specificity and sensitivity of the DCNN model with the performance of six skilled thyroid ultrasound radiologists on the three validation sets.
Between Jan 1, 2012, and March 28, 2018, ultrasound images for the four study cohorts were obtained. The model achieved high performance in identifying thyroid cancer patients in the validation sets tested, with area under the curve values of 0·947 (95% CI 0·935–0·959) for the Tianjin internal validation set, 0·912 (95% CI 0·865–0·958) for the Jilin external validation set, and 0·908 (95% CI 0·891–0·925) for the Weihai external validation set. The DCNN model also showed improved performance in identifying thyroid cancer patients versus skilled radiologists. For the Tianjin internal validation set, sensitivity was 93·4% (95% CI 89·6–96·1) versus 96·9% (93·9–98·6; p=0·003) and specificity was 86·1% (81·1–90·2) versus 59·4% (53·0–65·6; p<0·0001). For the Jilin external validation set, sensitivity was 84·3% (95% CI 73·6–91·9) versus 92·9% (84·1–97·6; p=0·048) and specificity was 86·9% (95% CI 77·8–93·3) versus 57·1% (45·9–67·9; p<0·0001). For the Weihai external validation set, sensitivity was 84·7% (95% CI 77·0–90·7) versus 89·0% (81·9–94·0; p=0·25) and specificity was 87·8% (95% CI 81·6–92·5) versus 68·6% (60·7–75·8; p<0·0001).
The DCNN model showed similar sensitivity and improved specificity in identifying patients with thyroid cancer compared with a group of skilled radiologists. The improved technical performance of the DCNN model warrants further investigation as part of randomised clinical trials.
The Program for Changjiang Scholars and Innovative Research Team in University in China, and National Natural Science Foundation of China.
Purpose To examine the effects of subconcussive impacts resulting from a single season of youth (age range, 8-13 years) football on changes in specific white matter (WM) tracts as detected with ...diffusion-tensor imaging in the absence of clinically diagnosed concussions. Materials and Methods Head impact data were recorded by using the Head Impact Telemetry system and quantified as the combined-probability risk-weighted cumulative exposure (RWE
). Twenty-five male participants were evaluated for seasonal fractional anisotropy (FA) changes in specific WM tracts: the inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus, and superior longitudinal fasciculus (SLF). Fiber tracts were segmented into a central core and two fiber terminals. The relationship between seasonal FA change in the whole fiber, central core, and the fiber terminals with RWE
was also investigated. Linear regression analysis was conducted to determine the association between RWE
and change in fiber tract FA during the season. Results There were statistically significant linear relationships between RWE
and decreased FA in the whole (R
= 0.433; P = .003), core (R
= 0.3649; P = .007), and terminals (R
= 0.5666; P < .001) of left IFOF. A trend toward statistical significance (P = .08) in right SLF was observed. A statistically significant correlation between decrease in FA of the right SLF terminal and RWE
was also observed (R
= 0.2893; P = .028). Conclusion This study found a statistically significant relationship between head impact exposure and change of FA fractional anisotropy value of whole, core, and terminals of left IFOF and right SLF's terminals where WM and gray matter intersect, in the absence of a clinically diagnosed concussion.
RSNA, 2016.
Introduction
Mid‐life dietary patterns are associated with Alzheimer's disease (AD) risk, although few controlled trials have been conducted.
Methods
Eighty‐seven participants (age range: 45 to 65) ...with normal cognition (NC, n = 56) or mild cognitive impairment (MCI, n = 31) received isocaloric diets high or low in saturated fat, glycemic index, and sodium (Western‐like/West‐diet vs. Mediterranean‐like/Med‐diet) for 4 weeks. Diet effects on cerebrospinal fluid (CSF) biomarkers, cognition, and cerebral perfusion were assessed to determine whether responses differed by cognitive status.
Results
CSF amyloid beta (Aβ)42/40 ratios increased following the Med‐diet, and decreased after West‐diet for NC adults, whereas the MCI group showed the reverse pattern. For the MCI group, the West‐diet reduced and the Med‐diet increased total tau (t‐tau), whereas CSF Aβ42/t‐tau ratios increased following the West‐diet and decreased following the Med‐diet. For NC participants, the Med‐diet increased and the West‐diet decreased cerebral perfusion.
Discussion
Diet response during middle age may highlight early pathophysiological processes that increase AD risk.
A 21-year old male presented with ataxia and dysarthria that had appeared over a period of months. Exome sequencing identified a de novo missense variant in ATP1A3, the gene encoding the α3 subunit ...of Na,K-ATPase. Several lines of evidence suggest that the variant is causative. ATP1A3 mutations can cause rapid-onset dystonia-parkinsonism (RDP) with a similar age and speed of onset, as well as severe diseases of infancy. The patient's ATP1A3 p.Gly316Ser mutation was validated in the laboratory by the impaired ability of the expressed protein to support the growth of cultured cells. In a crystal structure of Na,K-ATPase, the mutated amino acid was directly apposed to a different amino acid mutated in RDP. Clinical evaluation showed that the patient had many characteristics of RDP, however he had minimal fixed dystonia, a defining symptom of RDP. Successive magnetic resonance imaging (MRI) revealed progressive cerebellar atrophy, explaining the ataxia. The absence of dystonia in the presence of other RDP symptoms corroborates other evidence that the cerebellum contributes importantly to dystonia pathophysiology. We discuss the possibility that a second de novo variant, in ubiquilin 4 (UBQLN4), a ubiquitin pathway component, contributed to the cerebellar neurodegenerative phenotype and differentiated the disease from other manifestations of ATP1A3 mutations. We also show that a homozygous variant in GPRIN1 (G protein-regulated inducer of neurite outgrowth 1) deletes a motif with multiple copies and is unlikely to be causative.
The human default mode network (DMN) is engaged at rest and in cognitive states such as self-directed thoughts. Interconnected homologous cortical areas in primates constitute a network considered as ...the equivalent. Here, based on a cross-species comparison of the DMN between humans and non-hominoid primates (macaques, marmosets, and mouse lemurs), we report major dissimilarities in connectivity profiles. Most importantly, the medial prefrontal cortex (mPFC) of non-hominoid primates is poorly engaged with the posterior cingulate cortex (PCC), though strong correlated activity between the human PCC and the mPFC is a key feature of the human DMN. Instead, a fronto-temporal resting-state network involving the mPFC was detected consistently across non-hominoid primate species. These common functional features shared between non-hominoid primates but not with humans suggest a substantial gap in the organization of the primate’s DMN and its associated cognitive functions.
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•Resting-state fMRI reveals DMN structure across four primate species•Two distinct networks in non-hominoid primates included homolog areas of the human DMN•The mPFC cluster is poorly connected to the PCC cluster in non-hominoid primates•Functional atlases available for each species
By comparing resting-state networks in humans, macaques, marmosets, and mouse lemurs, Garin et al. identify two networks in non-hominoid primates that include homolog areas of the human default mode network. The mPFC and PCC are tightly connected in the human DMN but poorly connected to each other across non-hominoid primates.
G-protein-coupled receptor 119 (GPR119) has emerged as a promising target for treating type 2 diabetes mellitus. Activating GPR119 improves glucose homeostasis, while suppressing appetite and weight ...gain. Measuring GPR119 levels in vivo could significantly advance GPR119-based drug development strategies including target engagement, occupancy, and distribution studies. To date, no positron emission tomography (PET) ligands are available to image GPR119. In this paper, we report the synthesis, radiolabeling, and preliminary biological evaluations of a novel PET radiotracer 18FKSS3 to image GPR119. PET imaging will provide information on GPR119 changes with diabetic glycemic loads and the efficacy of GPR119 agonists as antidiabetic drugs. Our results demonstrate 18FKSS3’s high radiochemical purity, specific activity, cellular uptake, and in vivo and ex vivo uptake in pancreas, liver, and gut regions, with high GPR119 expression. Cell pretreatment with nonradioactive KSS3, rodent PET imaging, biodistribution, and autoradiography studies showed significant blocking in the pancreas showing 18FKSS3’s high specificity.
Purpose
To reduce the total scan time of multiple postlabeling delay (multi‐PLD) pseudo‐continuous arterial spin labeling (pCASL) by developing a hierarchically structured 3D convolutional neural ...network (H‐CNN) that estimates the arterial transit time (ATT) and cerebral blow flow (CBF) maps from the reduced number of PLDs as well as averages.
Methods
A total of 48 subjects (38 females and 10 males), aged 56–80 years, compromising a training group (n = 45) and a validation group (n = 3) underwent MRI including multi‐PLD pCASL. We proposed an H‐CNN to estimate the ATT and CBF maps using a reduced number of PLDs and a separately reduced number of averages. The proposed method was compared with a conventional nonlinear model fitting method using the mean absolute error (MAE).
Results
The H‐CNN provided the MAEs of 32.69 ms for ATT and 3.32 mL/100 g/min for CBF estimations using a full data set that contains six PLDs and six averages in the 3 test subjects. The H‐CNN also showed that the smaller number of PLDs can be used to estimate both ATT and CBF without significant discrepancy from the reference (MAEs of 231.45 ms for ATT and 9.80 mL/100 g/min for CBF using three of six PLDs).
Conclusion
The proposed machine learning–based ATT and CBF mapping offers substantially reduced scan time of multi‐PLD pCASL.
Long acting insulin detemir administered intranasally for three weeks enhanced memory for adults with Alzheimer's disease dementia (AD) or amnestic mild cognitive impairment (MCI). The investigation ...of longer-term administration is necessary to determine whether benefits persist, whether they are similar to benefits provided by regular insulin, and whether either form of insulin therapy affects AD biomarkers.
The present study aimed to determine whether four months of treatment with intranasal insulin detemir or regular insulin improves cognition, daily functioning, and AD biomarkers for adults with MCI or AD.
This randomized, double-blind, placebo-controlled trial included an intent-to-treat sample consisting of 36 adults diagnosed with MCI or mild to moderate AD. Participants received placebo (n = 12), 40 IU of insulin detemir (n = 12), or 40 IU of regular insulin (n = 12) daily for four months, administered with a nasal delivery device. A cognitive battery was administered at baseline and after two and four months of treatment. MRI was administered for all participants and lumbar puncture for a subset (n = 20) at baseline and four months. The primary outcome was change from baseline to four months on a memory composite (sum of Z scores for delayed list and story recall). Secondary outcomes included: global cognition (Alzheimer's Disease Assessment Scale-Cognition), daily functioning (Dementia Severity Rating Scale), MRI volume changes in AD-related regions of interest, and cerebrospinal fluid AD markers.
The regular insulin treated group had better memory after two and four months compared with placebo (p < 0.03). No significant effects were observed for the detemir-assigned group compared with the placebo group, or for daily functioning for either group. Regular insulin treatment was associated with preserved volume on MRI. Regular insulin treatment was also associated with reduction in the tau-P181/Aβ42 ratio.
Future research is warranted to examine the mechanistic basis of treatment differences, and to further assess the efficacy and safety of intranasal insulin.
The large language model called ChatGPT has drawn extensively attention because of its human-like expression and reasoning abilities. In this study, we investigate the feasibility of using ChatGPT in ...experiments on translating radiology reports into plain language for patients and healthcare providers so that they are educated for improved healthcare. Radiology reports from 62 low-dose chest computed tomography lung cancer screening scans and 76 brain magnetic resonance imaging metastases screening scans were collected in the first half of February for this study. According to the evaluation by radiologists, ChatGPT can successfully translate radiology reports into plain language with an average score of 4.27 in the five-point system with 0.08 places of information missing and 0.07 places of misinformation. In terms of the suggestions provided by ChatGPT, they are generally relevant such as keeping following-up with doctors and closely monitoring any symptoms, and for about 37% of 138 cases in total ChatGPT offers specific suggestions based on findings in the report. ChatGPT also presents some randomness in its responses with occasionally over-simplified or neglected information, which can be mitigated using a more detailed prompt. Furthermore, ChatGPT results are compared with a newly released large model GPT-4, showing that GPT-4 can significantly improve the quality of translated reports. Our results show that it is feasible to utilize large language models in clinical education, and further efforts are needed to address limitations and maximize their potential.
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