An automated screening model for aortic emergencies using convolutional neural networks and cropped computed tomography angiography images of the aorta.

PURPOSE: Patients with aortic emergencies, such as aortic dissection and rupture, are at risk of rapid deterioration, necessitating prompt diagnosis. This study introduces a novel automated screening model for computed tomography angiography (CTA) of patients with aortic emergencies, utilizing deep convolutional neural network (DCNN) algorithms. METHODS: Our model (Model A) initially predicted the positions of the aorta in the original axial CTA images and extracted the sections containing the aorta from these images. Subsequently, it predicted whether the cropped images showed aortic lesions. To compare the predictive performance of Model A in identifying aortic emergencies, we also developed Model B, which directly predicted the presence or absence of aortic lesions in the original images. Ultimately, these models categorized patients based on the presence or absence of aortic emergencies, as determined by the number of consecutive images expected to show the lesion. RESULTS: The models were trained with 216 CTA scans and tested with 220 CTA scans. Model A demonstrated a higher area under the curve (AUC) for patient-level classification of aortic emergencies than Model B (0.995; 95% confidence interval [CI], 0.990-1.000 vs. 0.972; 95% CI, 0.950-0.994, respectively; p = 0.013). Among patients with aortic emergencies, the AUC of Model A for patient-level classification of aortic emergencies involving the ascending aorta was 0.971 (95% CI, 0.931-1.000). CONCLUSION: The model utilizing DCNNs and cropped CTA images of the aorta effectively screened CTA scans of patients with aortic emergencies. This study would help develop a computer-aided triage system for CT scans, prioritizing the reading for patients requiring urgent care and ultimately promoting rapid responses to patients with aortic emergencies.

Patient with penile metastasis from prostate cancer and survival over 5 years: A case report with longitudinal evaluation using computed tomography and magnetic resonance imaging.

Penile metastasis of malignant tumors is a very rare condition, often occurring as a part of systemic metastases, and is therefore associated with a poor prognosis. Although there have been reports of magnetic resonance imaging findings of penile metastasis, longitudinal imaging changes have not been presented previously. We report a case of a 80-year-old male patient with penile metastasis from prostate adenocarcinoma. First magnetic resonance imaging demonstrated multiple penile nodules in the left corpus cavernosum corpora cavernosa, and these nodules were fused and across the septum of the penis, forming an enlarged, diffusely spreading mass on the follow-up exam 5 years later. In this case, a longitudinal evaluation of magnetic resonance imaging demonstrated the course of the extension of the rare penile metastasis.

Leaf margin phenotype-specific restriction-site-associated DNA-derived markers for pineapple (Ananas comosus L.).

To explore genome-wide DNA polymorphisms and identify DNA markers for leaf margin phenotypes, a restriction-site-associated DNA sequencing analysis was employed to analyze three bulked DNAs of F1 progeny from a cross between a 'piping-leaf-type' cultivar, 'Yugafu', and a 'spiny-tip-leaf-type' variety, 'Yonekura'. The parents were both Ananas comosus var. comosus. From the analysis, piping-leaf and spiny-tip-leaf gene-specific restriction-site-associated DNA sequencing tags were obtained and designated as PLSTs and STLSTs, respectively. The five PLSTs and two STSLTs were successfully converted to cleaved amplified polymorphic sequence (CAPS) or simple sequence repeat (SSR) markers using the sequence differences between alleles. Based on the genotyping of the F1 with two SSR and three CAPS markers, the five PLST markers were mapped in the vicinity of the P locus, with the closest marker, PLST1_SSR, being located 1.5 cM from the P locus. The two CAPS markers from STLST1 and STLST3 perfectly assessed the 'spiny-leaf type' as homozygotes of the recessive s allele of the S gene. The recombination value between the S locus and STLST loci was 2.4, and STLSTs were located 2.2 cM from the S locus. SSR and CAPS markers are applicable to marker-assisted selection of leaf margin phenotypes in pineapple breeding.