Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification

OBJECTIVE

To evaluate performance of AI as a standalone reader in ultra-low-dose CT lung cancer baseline screening, and compare it to that of experienced radiologists.

METHODS

283 participants who underwent a baseline ultra-LDCT scan in Moscow Lung Cancer Screening, between February 2017-2018, and had at least one solid lung nodule, were included. Volumetric nodule measurements were performed by five experienced blinded radiologists, and independently assessed using an AI lung cancer screening prototype (AVIEW LCS, v1.0.34, Coreline Soft, Co. ltd, Seoul, Korea) to automatically detect, measure, and classify solid nodules. Discrepancies were stratified into two groups: positive-misclassification (PM); nodule classified by the reader as a NELSON-plus /EUPS-indeterminate/positive nodule, which at the reference consensus read was < 100 mm3, and negative-misclassification (NM); nodule classified as a NELSON-plus /EUPS-negative nodule, which at consensus read was ≥ 100 mm3.

RESULTS

1149 nodules with a solid-component were detected, of which 878 were classified as solid nodules. For the largest solid nodule per participant (n = 283); 61 [21.6 %; 53 PM, 8 NM] discrepancies were reported for AI as a standalone reader, compared to 43 [15.1 %; 22 PM, 21 NM], 36 [12.7 %; 25 PM, 11 NM], 29 [10.2 %; 25 PM, 4 NM], 28 [9.9 %; 6 PM, 22 NM], and 50 [17.7 %; 15 PM, 35 NM] discrepancies for readers 1, 2, 3, 4, and 5 respectively.

CONCLUSION

Our results suggest that through the use of AI as an impartial reader in baseline lung cancer screening, negative-misclassification results could exceed that of four out of five experienced radiologists, and radiologists' workload could be drastically diminished by up to 86.7%.

Braincase anatomy of extant Crocodylia, with new insights into the development and evolution of the neurocranium in crocodylomorphs

Present-day crocodylians exhibit a remarkably akinetic skull with a highly modified braincase. We present a comprehensive description of the neurocranial osteology of extant crocodylians, with notes on the development of individual skeletal elements and a discussion of the terminology used for this project. The quadrate is rigidly fixed by multiple contacts with most braincase elements. The parabasisphenoid is sutured to the pterygoids (palate) and the quadrate (suspensorium); as a result, the basipterygoid joint is completely immobilized. The prootic is reduced and externally concealed by the quadrate. It has a verticalized buttress that participates in the canal for the temporal vasculature. The ventrolateral processes of the otoccipitals completely cover the posteroventral region of the braincase, enclose the occipital nerves and blood vessels in narrow bony canals and also provide additional sutural contacts between the braincase elements and further consolidate the posterior portion of the crocodylian skull. The otic capsule of crocodylians has a characteristic cochlear prominence that corresponds to the lateral route of the perilymphatic sac. Complex internal structures of the otoccipital (extracapsular buttress) additionally arrange the neurovascular structures of the periotic space of the cranium. Most of the braincase elements of crocodylians are excavated by the paratympanic pneumatic sinuses. The braincase in various extant crocodylians has an overall similar structure with some consistent variation between taxa. Several newly observed features of the braincase are present in Gavialis gangeticus and extant members of Crocodylidae to the exclusion of alligatorids: the reduced exposure of the prootic buttress on the floor of the temporal canal, the sagittal nuchal crest of the supraoccipital projecting posteriorly beyond the postoccipital processes and the reduced paratympanic pneumaticity. The most distinctive features of the crocodylian braincase (fixed quadrate and basipterygoid joint, consolidated occiput) evolved relatively rapidly at the base of Crocodylomorpha and accompanied the initial diversification of this clade during the Late Triassic and Early Jurassic. We hypothesize that profound rearrangements in the individual development of the braincases of basal crocodylomorphs underlie these rapid evolutionary modifications. These rearrangements are likely reflected in the embryonic development of extant crocodylians and include the involvement of neomorphic dermal anlagen in different portions of the developing chondrocranium, the extensive ossification of the palatoquadrate cartilage as a single expanded quadrate and the anteromedial inclination of the quadrate.

A simplified cluster model and a tool adapted for collaborative labeling of lung cancer CT scans

BACKGROUND AND OBJECTIVE

Lung cancer is the most common type of cancer with a high mortality rate. Early detection using medical imaging is critically important for the long-term survival of the patients. Computer-aided diagnosis (CAD) tools can potentially reduce the number of incorrect interpretations of medical image data by radiologists. Datasets with adequate sample size, annotation, and truth are the dominant factors in developing and training effective CAD algorithms. The objective of this study was to produce a practical approach and a tool for the creation of medical image datasets.

METHODS

The proposed model uses the modified maximum transverse diameter approach to mark a putative lung nodule. The modification involves the possibility to use a set of overlapping spheres of appropriate size to approximate the shape of the nodule. The algorithm embedded in the model also groups the marks made by different readers for the same lesion. We used the data of 536 randomly selected patients of Moscow outpatient clinics to create a dataset of standard-dose chest computed tomography (CT) scans utilizing the double-reading approach with arbitration. Six volunteer radiologists independently produced a report for each scan using the proposed model with the main focus on the detection of lesions with sizes ranging from 3 to 30 mm. After this, an arbitrator reviewed their marks and annotations.

RESULTS

The maximum transverse diameter approach outperformed the alternative methods (3D box, ellipsoid, and complete outline construction) in a study of 10,000 computer-generated tumor models of different shapes in terms of accuracy and speed of nodule shape approximation. The markup and annotation of the CTLungCa-500 dataset revealed 72 studies containing no lung nodules. The remaining 464 CT scans contained 3151 lesions marked by at least one radiologist: 56%, 14%, and 29% of the lesions were malignant, benign, and non-nodular, respectively. 2887 lesions have the target size of 3-30 mm. Only 70 nodules were uniformly identified by all the six readers. An increase in the number of independent readers providing CT scans interpretations led to an accuracy increase associated with a decrease in agreement. The dataset markup process took three working weeks.

CONCLUSIONS

The developed cluster model simplifies the collaborative and crowdsourced creation of image repositories and makes it time-efficient. Our proof-of-concept dataset provides a valuable source of annotated medical imaging data for training CAD algorithms aimed at early detection of lung nodules. The tool and the dataset are publicly available at https://github.com/Center-of-Diagnostics-and-Telemedicine/FAnTom.git and https://mosmed.ai/en/datasets/ct_lungcancer_500/, respectively.

[Adrenal imaging: anatomy and pathology (literature review)]

This literature review focuses on the normal adrenal gland anatomy and typical imaging features necessary to evaluate benign and malignant lesions. In particular, adenoma, pheochromocytoma, metastases and adrenocortical carcinoma were discussed as some of the most common lesions. For this purpose, a review of relevant local and international literature sources up to January 2021 was conducted.In many cases, adrenal incidentalomas have distinctive features allowing characterization using noninvasive methods. It is possible to suspect a malignant nature and promptly refer the patient for the necessary invasive examinations in some cases. -Computed tomography, especially with intravenous contrast enhancement, is the primary imaging modality because it enables differential diagnosis. Magnetic resonance tomography remains a sensitive method in lesion detection and follow-up but is not very specific for determining the malignant potential. Positron emission computed tomography also remains an additional method and is used mainly for differential diagnosis of malignant tumors, detecting metastases and recurrences after surgical treatment. Ultrasound has a limited role but is nevertheless of great importance in the pediatric population, especially newborns. Promising techniques such as radiomics and dual-energy CT can expand imaging capabilities and improve diagnostic accuracy.Because adrenal lesions are often incidentally detected by imaging performed for other reasons, it is vital to interpret such findings correctly. This review should give the reader a broad overview of how different imaging modalities can evaluate adrenal pathology and guide radiologists and clinicians.

[Moscow Screening: Lung Cancer Screening With Low-Dose Computed Tomography]

For the first time in Moscow and Russia, a program of selective lung cancer screening has been implemented with a comprehensive approach, including organizational, management, medical, technical and educational aspects and quality control. Unique ultra-low-dose protocols (ultra-LDCT) have been developed to implement the screening program. These protocols allow performing high-quality chest computed tomography for lung nodule detection with an effective dose of less than 1 mSv. The possibility of using neural networks ("artificial intelligence") for quality control of screening results has been proven for the first time.

[The future of computer-aided diagnostics in chest computed tomography]

Recently, more and more attention has been paid to the utility of artificial intelligence in medicine. Radiology differs from other medical specialties with its high digitalization, so most software developers operationalize this area of medicine. The primary condition for machine learning is met because medical diagnostic images have high reproducibility. Today, the most common anatomic area for computed tomography is the thorax, particularly with the widespread lung cancer screening programs using low-dose computed tomography. In this regard, the amount of information that needs to be processed by a radiologist is snowballing. Thus, automatic image analysis will allow more studies to be interpreted. This review is aimed at highlighting the possibilities of machine learning in the chest computed tomography.

Age and Gender Differences of the Frontal Bone: A Computed Tomographic (CT)-Based Study

BACKGROUND

Age-related changes of the frontal bone in both males and females have received limited attention, although understanding these changes is crucial to developing the best surgical and nonsurgical treatment plans for this area.

OBJECTIVES

To investigate age-related and gender-related changes of the forehead.

METHODS

Cranial computed tomographic images from 157 Caucasian individuals were investigated (10 males and 10 females from each of the following decades: 20-29 years, 30-39 years, 40-49 years, 50-59 years, 60-69 years, 70-79 years, 80-89 years, and of 8 males and 9 females aged 90-98 years). Frontal bone thickness and forehead distance measurements were carried out to analyze age and gender differences.

RESULTS

With increasing age, the size of a male forehead reduces until no significant differences to a female forehead is present at old age (P = 0.307). The thickness of the frontal bone of the lower forehead (≤4 cm cranial to the nasal root) increased slightly in both genders with increasing age. In the upper forehead (≥4 cm cranial to the nasal root), frontal bone thickness decreased significantly (P = 0.002) in males but showed no statistically significant change in thickness in females (P = 0.165).

CONCLUSIONS

The shape of the frontal bone varies in young individuals of different genders and undergoes complex changes with age because of bone remodeling. Understanding these bony changes, in addition to those in the soft tissues, helps physicians choose the best surgical and nonsurgical treatment options for the forehead.

LEVEL OF EVIDENCE: 4