Choosing the right artificial intelligence solutions for your radiology department: key factors to consider.

The rapid evolution of artificial intelligence (AI), particularly in deep learning, has significantly impacted radiology, introducing an array of AI solutions for interpretative tasks. This paper provides radiology departments with a practical guide for selecting and integrating AI solutions, focusing on interpretative tasks that require the active involvement of radiologists. Our approach is not to list available applications or review scientific evidence, as this information is readily available in previous studies; instead, we concentrate on the essential factors radiology departments must consider when choosing AI solutions.

Quantitative evaluation of Saliency-Based Explainable artificial intelligence (XAI) methods in Deep Learning-Based mammogram analysis.

Background: Explainable Artificial Intelligence (XAI) is prominent in the diagnostics of opaque deep learning (DL) models, especially in medical imaging. Saliency methods are commonly used, yet there's a lack of quantitative evidence regarding their performance.

Objectives: To quantitatively evaluate the performance of widely utilized saliency XAI methods in the task of breast cancer detection on mammograms.

Deep learning for assessing image quality in bi-parametric prostate MRI: A feasibility study.

Background: Although systems such as Prostate Imaging Quality (PI-QUAL) have been proposed for quality assessment, visual evaluations by human readers remain somewhat inconsistent, particularly among less-experienced readers.

Objectives: To assess the feasibility of deep learning (DL) for the automated assessment of image quality in bi-parametric MRI scans and compare its performance to that of less-experienced readers.

Methods: We used bi-parametric prostate MRI scans from the PI-CAI dataset in this study.

Anatomically guided self-adapting deep neural network for clinically significant prostate cancer detection on bi-parametric MRI: a multi-center study.

Objective: To evaluate the effectiveness of a self-adapting deep network, trained on large-scale bi-parametric MRI data, in detecting clinically significant prostate cancer (csPCa) in external multi-center data from men of diverse demographics; to investigate the advantages of transfer learning.

Methods: We used two samples: (i) Publicly available multi-center and multi-vendor Prostate Imaging: Cancer AI (PI-CAI) training data, consisting of 1500 bi-parametric MRI scans, along with its unseen validation and testing samples; (ii) In-house multi-center testing and transfer learning data, comprising 1036 and 200 bi-parametric MRI scans. We trained a self-adapting 3D nnU-Net model using probabilistic prostate masks on the PI-CAI data and evaluated its performance on the hidden validation and testing samples and the in-house data with and without transfer learning.

Inter-reader agreement of the prostate imaging quality (PI-QUAL) score for basic readers in prostate MRI: A multi-center study.

Background: The Prostate Imaging Quality (PI-QUAL) score is the first step toward image quality assessment in multi-parametric prostate MRI (mpMRI). Previous studies have demonstrated moderate to excellent inter-rater agreement among expert readers; however, there is a need for studies to assess the inter-reader agreement of PI-QUAL scoring in basic prostate readers.

Objectives: To assess the inter-reader agreement of the PI-QUAL score amongst basic prostate readers on multi-center prostate mpMRI.

Automated LVO detection and collateral scoring on CTA using a 3D self-configuring object detection network: a multi-center study.

The use of deep learning (DL) techniques for automated diagnosis of large vessel occlusion (LVO) and collateral scoring on computed tomography angiography (CTA) is gaining attention. In this study, a state-of-the-art self-configuring object detection network called nnDetection was used to detect LVO and assess collateralization on CTA scans using a multi-task 3D object detection approach. The model was trained on single-phase CTA scans of 2425 patients at five centers, and its performance was evaluated on an external test set of 345 patients from another center.

The Role of Whole-Body Magnetic Resonance Imaging in Assessing Extrapulmonary Metastases in Osteosarcoma Staging and Restaging: A Pilot Study.

Objective: The aim of the study is to investigate the role of whole-body magnetic resonance imaging (MRI) in assessing extrapulmonary metastases in primary osteosarcoma staging.

Methods: We retrospectively reviewed medical data to identify primary osteosarcoma patients with available preoperative whole-body MRI obtained in the staging or restaging. Histopathology was the reference test for assessing the diagnostic performance, if available.

Does deep learning software improve the consistency and performance of radiologists with various levels of experience in assessing bi-parametric prostate MRI?

Objective: To investigate whether commercially available deep learning (DL) software improves the Prostate Imaging-Reporting and Data System (PI-RADS) scoring consistency on bi-parametric MRI among radiologists with various levels of experience; to assess whether the DL software improves the performance of the radiologists in identifying clinically significant prostate cancer (csPCa).

Methods: We retrospectively enrolled consecutive men who underwent bi-parametric prostate MRI at a 3 T scanner due to suspicion of PCa. Four radiologists with 2, 3, 5, and > 20 years of experience evaluated the bi-parametric prostate MRI scans with and without the DL software.

Does the menstrual phase affect gastric emptying? Prospective, observational study.

Objective: Pulmonary aspiration of gastric content is a serious complication of anesthesia. It is unclear what effects different parts of the menstrual cycle have on how long it takes for the stomach to empty. This prospective observational study assessed the relationship between menstrual cycle phases and gastric emptying using ultrasonography (USG) in volunteers of reproductive age.

Cribriform Pattern of The Prostate Adenocarcinoma: Sensitivity of Multiparametric MRI.

Background: The aim of this study was to investigate the diagnostic performance of mpMRI for detecting cribriform pattern prostate cancer.

Materials And Methods: This study retrospectively enrolled 33 patients who were reported cribriform pattern prostate cancer at final pathology. The localization, grade and volumetric properties of the dominant tumors and areas with cribriform pattern at the final pathological specimens were recorded and the diagnostic value of mpMRI was evaluated on the basis of the cribriform morphology detection rate.

A Comparative Study of Multiparametric MRI Sequences in Measuring Prostate Cancer Index Lesion Volume.

Objectives: To compare the effectiveness of individual multiparametric prostate MRI (mpMRI) sequences-T2W, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), and dynamic contrast-enhanced (DCE)-in assessing prostate cancer (PCa) index lesion volume using whole-mount pathology as the ground-truth; to assess the impact of an endorectal coil (ERC) on the measurements.

Materials And Methods: We retrospectively enrolled 72 PCa patients who underwent 3T mpMRI with (n = 39) or without (n = 33) an ERC. A pathologist drew the index lesion borders on whole-mount pathology using planimetry (whole-mount).

A Review on Cutaneous and Musculoskeletal Manifestations of CLOVES Syndrome.

CLOVES syndrome is a novel sporadic mosaic segmental overgrowth syndrome, currently categorized under the canopy of PROS (-related overgrowth spectrum) disorders. All PROS disorders harbor heterozygous postzygotic activating somatic mutations involving the gene. As an upstream regulator of the signal transduction pathway, activating mutations of gene commence in uncontrolled growth of cutaneous, vascular (capillaries, veins, and lymphatics), adipose, neural, and musculoskeletal tissues.

Performance of apparent diffusion coefficient values and ratios for the prediction of prostate cancer aggressiveness across different MRI acquisition settings.

Purpose: In this study, we assessed the performance of apparent diffusion coefficient (ADC) and diffusion-weighted imaging (DWI) metrics and their ratios across different magnetic resonance imaging (MRI) acquisition settings, with or without an endorectal coil (ERC), for the evaluation of prostate cancer (PCa) aggressiveness using whole-mount specimens as a reference.

Methods: We retrospectively reviewed the data of prostate carcinoma patients with a Gleason score (GS) of 3+4 or higher who underwent prostate MRI using a 3T unit at our institution. They were divided into two groups based on the use of ERC for MRI acquisition, and patients who underwent prostate MRI with an ERC constituted the ERC (n = 55) data set, while the remaining patients accounted for the non-ERC data set (n = 41).

A joint convolutional-recurrent neural network with an attention mechanism for detecting intracranial hemorrhage on noncontrast head CT.

To investigate the performance of a joint convolutional neural networks-recurrent neural networks (CNN-RNN) using an attention mechanism in identifying and classifying intracranial hemorrhage (ICH) on a large multi-center dataset; to test its performance in a prospective independent sample consisting of consecutive real-world patients. All consecutive patients who underwent emergency non-contrast-enhanced head CT in five different centers were retrospectively gathered. Five neuroradiologists created the ground-truth labels.

Prevalence of benign bone lesions of the lower extremity in the pediatric spinal disorders: a whole-body imaging study.

There is a paucity of knowledge about benign bone lesions. The advances in imaging methods can screen bone lesions incidentally, and missing information can be provided. The aim of the study is to collect information about the prevalence and natural history of benign bone lesions with the use of whole-body biplanar slot-scanning imaging (EOS).

Third-Generation Dual-Source Computed Tomography for Coronary Angiography With Individually Tailored Scan Protocols Can Achieve a Low Radiation Dose With Good Image Quality in Unselected Patients.

Objective: To explore the image quality and radiation exposure associated with coronary angiography obtained with a third-generation dual-source computed tomography, using body mass index (BMI)- and heart rate (HR)-adapted protocols in real-world patients.

Methods: Three scan protocols were implemented with regard to HR: prospective turbo high-pitch spiral, sequential, and retrospective spiral modes. We adapted the reference kilovoltage value according to BMI.

Risk of symptomatic radiation necrosis in patients treated with stereotactic radiosurgery for brain metastases.

Introductio: Stereotactic radiosurgery (SRS) is a treatment option in the initial management of patients with brain metastases. While its efficacy has been demonstrated in several prior studies, treatment-related complications, particularly symptomatic radiation necrosis (RN), remains as an obstacle for wider implementation of this treatment modality. We thus examined risk factors associated with the development of symptomatic RN in patients treated with SRS for brain metastases.

Evaluation of the radiopacity of restorative materials with different structures and thicknesses using a digital radiography system.

Purpose: The aim of this study was to evaluate the radiopacities of various types of restorative materials with different thicknesses compared with enamel, dentin, and aluminum.

Materials And Methods: Four bulk-fill resins, 2 hybrid ceramics, 2 micro-hybrid resin composites, 6 glass ionomer-based materials, 2 zinc phosphate cements, and an amalgam were used in the study. Twelve disk-shaped specimens were prepared from each of 17 restorative materials with thicknesses of 1 mm, 2 mm, and 4 mm (n=4).

Inter-vendor performance of deep learning in segmenting acute ischemic lesions on diffusion-weighted imaging: a multicenter study.

There is little evidence on the applicability of deep learning (DL) in the segmentation of acute ischemic lesions on diffusion-weighted imaging (DWI) between magnetic resonance imaging (MRI) scanners of different manufacturers. We retrospectively included DWI data of patients with acute ischemic lesions from six centers. Dataset A (n = 2986) and B (n = 3951) included data from Siemens and GE MRI scanners, respectively.

The visibility of prostate cancer concerning underlying histopathological variances: A single-center multiparametric magnetic resonance imaging study.

Purpose: To investigate whether prostate cancer (PCa) lesions regarding histopathological composition exhibit different morphological features on multiparametric prostate MRI (mpMRI).

Methods: We investigated men with PCa with available mpMRI and whole-mount specimens between June 2015 to December 2020.The acquisition protocol consistent with the Prostate Imaging Reporting and Data System (PI-RADS).

Does vertebral body tethering cause disc and facet joint degeneration? A preliminary MRI study with minimum two years follow-up.

Background Context: Vertebral body tethering (VBT), a flexible compression-based growth modulation technique, was claimed to prevent disc degeneration due to its less rigid nature compared to other growth-friendly techniques. Yet, the consequences of VBT surgery on discs and facet joints have not been precisely acknowledged.

Purpose: The purpose of this study was to determine the changes in the intermediate and adjacent levels at least 2 years after surgery.

Does Employing a Flowchart Improve the Diagnostic Performance of Cardiac Magnetic Resonance Imaging in Left Ventricular Noncompaction?

Background: To test the hypothesis that making a diagnosis of left ventricular noncompaction (LVNC) on cardiac magnetic resonance imaging (CMRI) using a noncompacted-to-compacted (NC/C) myocardium ratio > 2.3 would yield significant errors, and also to test a diagnostic flowchart in patients who undergo CMRI and have clinical and echocardiographic findings suggesting LVNC could improve the diagnosis of LVNC.

Methods: A total of 84 patients with LVNC and 162 controls consisting of patients with other diseases and healthy participants who had CMRI and echocardiograms were selected.

Association between left ventricular strain and cardiac iron load in beta-thalassaemia major: a cardiac magnetic resonance study.

Objective: To evaluate the utility of cardiac magnetic resonance feature tracking-derived left ventricular strain in assessing cardiac dysfunction and investigate the correlation between left ventricular strain and myocardial T2* in patients with beta-thalassaemia major.

Methods: Forty-two patients with beta-thalassaemia major, having a mean age of 22.49 ± 8.