Portal Venous Thrombosis after Percutaneous Cryoablation for Renal Cell Carcinoma.

A 50-year-old man with von Hippel-Lindau disease underwent cryoablation (CRA) for two adjacent renal cell carcinomas in the upper pole of his right kidney. Although computed tomography (CT) immediately after CRA revealed involvement of part of the liver parenchyma in the ice-ball, the treatment was completed without complications. Contrast-enhanced CT on day 2 post-CRA revealed a thrombus in the portal vein of segment 6 near the ablated liver parenchyma, prompting the initiation of oral anticoagulation. The patient was discharged on day 4 after CRA without any sequelae, and a follow-up contrast-enhanced CT done 6 weeks later demonstrated resolution of the portal vein thrombus.

Climate change and artificial intelligence in healthcare: Review and recommendations towards a sustainable future.

The rapid advancement of artificial intelligence (AI) in healthcare has revolutionized the industry, offering significant improvements in diagnostic accuracy, efficiency, and patient outcomes. However, the increasing adoption of AI systems also raises concerns about their environmental impact, particularly in the context of climate change. This review explores the intersection of climate change and AI in healthcare, examining the challenges posed by the energy consumption and carbon footprint of AI systems, as well as the potential solutions to mitigate their environmental impact. The review highlights the energy-intensive nature of AI model training and deployment, the contribution of data centers to greenhouse gas emissions, and the generation of electronic waste. To address these challenges, the development of energy-efficient AI models, the adoption of green computing practices, and the integration of renewable energy sources are discussed as potential solutions. The review also emphasizes the role of AI in optimizing healthcare workflows, reducing resource waste, and facilitating sustainable practices such as telemedicine. Furthermore, the importance of policy and governance frameworks, global initiatives, and collaborative efforts in promoting sustainable AI practices in healthcare is explored. The review concludes by outlining best practices for sustainable AI deployment, including eco-design, lifecycle assessment, responsible data management, and continuous monitoring and improvement. As the healthcare industry continues to embrace AI technologies, prioritizing sustainability and environmental responsibility is crucial to ensure that the benefits of AI are realized while actively contributing to the preservation of our planet.

Treatment-resistant hiccups during general anesthesia possibly caused by remimazolam: a case report.

BACKGROUND: Previous reports have described hiccups during general anesthesia that were possibly induced by drugs, including benzodiazepines. However, there are few reports of hiccups caused by remimazolam. Case presentation A 75-year-old woman underwent corneal transplantation under general anesthesia with remimazolam. She presented with hiccups once the effects of muscle relaxants used during induction wore off, which persisted even after various treatments, such as the administration of antipsychotic drugs. However, when remimazolam administration was terminated after surgery to awaken the patient, the hiccups stopped and did not recur after extubation. Evaluation of predicted blood levels of remimazolam suggests that higher levels of remimazolam might cause hiccups. CONCLUSION: Remimazolam might induce hiccups during general anesthesia. Anesthesiologists should consider administering muscle relaxants or changing the anesthetic in cases of refractory hiccups under general anesthesia.

Is cryoablation a valid option for renal cell carcinomas in direct contact with critical organs?

PURPOSE: This study aimed to assess the outcomes of percutaneous cryoablation (PCA) for renal cell carcinomas (RCCs) contacting critical organs without intervening fat tissue. MATERIAL AND METHODS: Twenty-three patients with 24 RCCs (mean size, 28.8 mm) contacting critical organs on preprocedural images were included. The organ displacement techniques, technical success, efficacy, and adverse events per Clavien-Dindo classification were retrospectively reviewed. RESULTS: The organs contacting the RCCs included the colon (n = 16), pancreas (n = 3), duodenum (n = 3), small intestine (n = 1), and stomach (n = 1). In all procedures, hydrodissection was conducted, and probe traction was additionally utilized in one to displace organs. Two procedures were terminated with an insufficient ice-ball margin (<6 mm) due to recurring proximity of the colon or thermal sink effect by renal hilar vessels, yielding a technical success rate of 91.6% (22/24). No severe adverse events were noted. All patients were alive without any metastases during a median follow-up of 34.4 months. The primary and secondary technical efficacy rates were 91.6% (22/24) and 95.8% (23/24) of tumors, respectively. CONCLUSION: PCA can be a valid option for RCCs contacting critical organs with a good safety profile and sufficient technical efficacy.

Energy landscape analysis and time-series clustering analysis of patient state multistability related to rheumatoid arthritis drug treatment: The KURAMA cohort study.

Rheumatoid arthritis causes joint inflammation due to immune abnormalities, resulting in joint pain and swelling. In recent years, there have been considerable advancements in the treatment of this disease. However, only approximately 60% of patients achieve remission. Patients with multifactorial diseases shift between states from day to day. Patients may remain in a good or poor state with few or no transitions, or they may switch between states frequently. The visualization of time-dependent state transitions, based on the evaluation axis of stable/unstable states, may provide useful information for achieving rheumatoid arthritis treatment goals. Energy landscape analysis can be used to quantitatively determine the stability/instability of each state in terms of energy. Time-series clustering is another method used to classify transitions into different groups to identify potential patterns within a time-series dataset. The objective of this study was to utilize energy landscape analysis and time-series clustering to evaluate multidimensional time-series data in terms of multistability. We profiled each patient's state transitions during treatment using energy landscape analysis and time-series clustering. Energy landscape analysis divided state transitions into two patterns: "good stability leading to remission" and "poor stability leading to treatment dead-end." The number of patients whose disease status improved increased markedly until approximately 6 months after treatment initiation and then plateaued after 1 year. Time-series clustering grouped patients into three clusters: "toward good stability," "toward poor stability," and "unstable." Patients in the "unstable" cluster are considered to have clinical courses that are difficult to predict; therefore, these patients should be treated with more care. Early disease detection and treatment initiation are important. The evaluation of state multistability enables us to understand a patient's current state in the context of overall state transitions related to rheumatoid arthritis drug treatment and to predict future state transitions.

Evaluating Desk-Assisted Standing Techniques for Simulated Pregnant Conditions: An Experimental Study Using a Maternity-Simulation Jacket.

Lower back pain, a common issue among pregnant women, often complicates daily activities like standing up from a chair. Therefore, research into the standing motion of pregnant women is important, and many research studies have already been conducted. However, many of these studies were conducted in highly controlled environments, overlooking everyday scenarios such as using a desk for support when standing up, and their effects have not been adequately tested. To address this gap, we measured multimodal signals for a sit-to-stand (STS) movement with hand assistance and verified the changes using a t-test. To avoid imposing strain on pregnant women, we used 10 non-diseased young adults who wore jackets designed to simulate pregnancy conditions, thus allowing for more comprehensive and rigorous experimentation. We attached surface electromyography (sEMG) sensors to the erector spinae muscles of participants and measured changes in muscle activity, skeletal positioning, and center of pressure both before and after wearing a Maternity-Simulation Jacket. Our analysis showed that the jacket successfully mimicked key aspects of the movement patterns typical in pregnant women. These results highlight the possibility of developing practical strategies that more accurately mirror the real-life scenarios met by pregnant women, enriching the current research on their STS movement.

Photon-Counting Detector CT: Potential for 75% Reduction in Contrast Medium Amount: A Phantom Study.

This study aimed to evaluate the potential reduction in contrast medium utilization using photon-counting detector computed tomography (PCD-CT). One PCD-CT scan (CT1) and three conventional (non-PCD-CT) CT scans (CT2-CT4) were performed using a multi-energy CT phantom that contained eight rods with different iodine concentrations (0.2, 0.5, 1, 2, 5, 10, 15, and 20 mg/ml). The CT values of the seven groups (CT1 for 40, 50, 60, and 70 keV; and CT2-4) were measured. Noise and contrast-to-noise ratio (CNR) were assessed for the eight rods at various iodine concentrations. CT2 and CT1 (40 keV) respectively required 20 mg/ml and 5 mg/ml of iodine, indicating that a comparable contrast effect could be obtained with approximately one-fourth of the contrast medium amount. The standard deviation values increased at lower energy levels irrespective of the iodine concentration. The CNR exhibited a decreasing trend with lower iodine concentrations, while it remained relatively stable across all iodine levels (40-70 keV). This study demonstrated that virtual monochromatic 40 keV images offer a similar contrast effect with a reduced contrast medium amount when compared to conventional CT systems at 120 kV.

Ablation of Kidney Tumors in Patients with Substantial Kidney Impairment: Current Status.

PURPOSE OF REVIEW: To review the current status of kidney tumor ablation in patients with substantial kidney impairment. RECENT FINDINGS: Few reports of kidney tumor ablation in such patients have recently been published. The reported prevalence of patients with stage 4 or 5 chronic kidney disease (CKD) among patients undergoing ablation is 2.0%-10%. In patients with stage 4 or 5 CKD, local tumor control rates were 88%-100%. The effect of ablation on CKD stage is unclear, and the observed deteriorations in kidney function are consistent with both the effect of cryoablation and the natural course of advanced CKD. According to guidelines, active surveillance may be selected. The goals of treatment are complete tumor removal and maintenance of kidney function, both of which can be met by ablation. Given the limited treatment options, ablation may play a pivotal role in the management of patients with advanced CKD.

BRAFV600E promotes anchorage-independent growth but inhibits anchorage-dependent growth in hTERT/Cdk4-Immortalized normal human bronchial epithelial cells.

Certain oncogenes, including mutant RAS and BRAF, induce a type of senescence known as oncogene-induced senescence (OIS) in normal cells in a cell-type-specific manner. OIS serves as a barrier to transformation by activated oncogenes. Our previous studies showed that mutant KRASV12 did not efficiently induce OIS in an hTERT/Cdk4-immortalized normal human bronchial epithelial cell line (HBEC3), but it did enhance both anchorage-dependent and anchorage-independent growth. In this study, we investigated whether mutant BRAF, a well-known inducer of OIS, could trigger OIS in HBEC3 cells. We also assessed the impact of mutant BRAF on the growth of HBEC3 cells, as no previous studies have examined this using a normal bronchial epithelial cell line model. We established an HBEC3 cell line, designated as HBEC3-BIN, that expresses mutant BRAFV600E in a doxycycline-regulated manner. Unlike our previous finding that KRASV12 upregulated both pERK and pAKT, mutant BRAFV600E upregulated pERK but not pAKT in HBEC3-BIN cells. Similar to KRASV12, BRAFV600E did not efficiently induce OIS. Interestingly, while BRAFV600E inhibited colony formation in anchorage-dependent conditions, it dramatically enhanced colony formation in anchorage-independent conditions in HBEC3-BIN. In HBEC3 cells without BRAFV600E or KRASV12 expression, p21 was only detected in the cytoplasm, and its localization was not altered by the expression of BRAFV600E or KRASV12. Next-generation sequencing analysis revealed an enrichment of gene sets known to be involved in carcinogenesis, including IL3/JAK/STAT3, IL2, STAT5, and the EMT pathway. Our results indicate that, unlike KRASV12, which promoted both, BRAFV600E enhances anchorage-independent growth but inhibits anchorage-dependent growth of HBEC3. This contrast may result from differences in activation signaling in the downstream pathways. Furthermore, HBEC3 cells appear to be inherently resistant to OIS, which may be partly due to the fact that p21 remains localized in the cytoplasm upon expression of BRAFV600E or KRASV12.

Transarterial Embolization for Cystic Artery Pseudoaneurysm Caused by Hepatocellular Carcinoma Rupture in the Gallbladder: A Case Report.

We report the rare case of an 80-year-old man with hepatocellular carcinoma that ruptured in the gallbladder, causing a cystic artery pseudoaneurysm and hemobilia. Emergency transarterial embolization (TAE) successfully controlled the bleeding without causing ischemic cholecystitis. Cone-beam computed tomography angiography was useful in identifying the bleeding branch of the selectively embolized cystic artery. Although the patient had poor liver function (Child-Pugh class C) before TAE, it remarkably improved after embolization due to the resolution of coagulopathy and obstructive jaundice caused by hemobilia. TAE was considered useful for this rare clinical condition.

The impact of large language models on radiology: a guide for radiologists on the latest innovations in AI.

The advent of Deep Learning (DL) has significantly propelled the field of diagnostic radiology forward by enhancing image analysis and interpretation. The introduction of the Transformer architecture, followed by the development of Large Language Models (LLMs), has further revolutionized this domain. LLMs now possess the potential to automate and refine the radiology workflow, extending from report generation to assistance in diagnostics and patient care. The integration of multimodal technology with LLMs could potentially leapfrog these applications to unprecedented levels.However, LLMs come with unresolved challenges such as information hallucinations and biases, which can affect clinical reliability. Despite these issues, the legislative and guideline frameworks have yet to catch up with technological advancements. Radiologists must acquire a thorough understanding of these technologies to leverage LLMs' potential to the fullest while maintaining medical safety and ethics. This review aims to aid in that endeavor.

Depiction rate of feeding arteries of renal cell carcinoma on four-dimensional computed tomography angiography.

PURPOSE: To retrospectively evaluate the depiction rate of feeding arteries in biopsy-proven clear cell renal cell carcinoma (CCRCC) on four-dimensional computed tomography angiography (4D-CTA) images. MATERIALS AND METHODS: This study included 22 patients with 22 CCRCC and 30 feeding arteries treated with transcatheter renal artery embolization. The depiction rate of the feeding arteries on preprocedural 4D-CTA was evaluated. Images were acquired by 320-row multi-detector computed tomography (CT) 15‒36 s after starting to inject a contrast agent (600 mg/kg iodine) intravenously into patients at 2.1 s intervals (11 phases). Two board-certified radiologists retrospectively assessed the feeder depiction rate in all 11 phases with reference to the procedural images as the gold standard. Discrepancies were resolved by consultation with a third radiologist. RESULTS: Among the feeders, 11 (36.7%) were segmental or lobar, and 19 (63.3%) were interlobar or arcuate arteries. The feeder depiction rate was the highest (25 [83.3%] of 30) in the 5th phase (delay, 23.4 s) where the gap in contrast enhancement between the renal artery and cortex was the largest. This was followed by the 6th (23 [76.7%] of 30), 4th (22 [73.3%] of 30]), and 7th (21 [70.0%] of 30) phases. The overall rate of depicting feeding arteries in the 11 phases of 4D-CTA was 28 (93.3%) of 30. CONCLUSIONS: The depiction rate of CCRCC feeding arteries including lobar or smaller artery branches by 4D-CTA was favorable. The feeding arteries were optimally visualized during the phase with the largest contrast gap between the renal artery and cortex.

Integrated Systems Analysis Deciphers Transcriptome and Glycoproteome Links in Alzheimer's Disease.

Glycosylation is increasingly recognized as a potential therapeutic target in Alzheimer's disease. In recent years, evidence of Alzheimer's disease-specific glycoproteins has been established. However, the mechanisms underlying their dysregulation, including tissue- and cell-type specificity, are not fully understood. We aimed to explore the upstream regulators of aberrant glycosylation by integrating multiple data sources using a glycogenomics approach. We identified dysregulation of the glycosyltransferase PLOD3 in oligodendrocytes as an upstream regulator of cerebral vessels and found that it is involved in COL4A5 synthesis, which is strongly correlated with amyloid fiber formation. Furthermore, COL4A5 has been suggested to interact with astrocytes via extracellular matrix receptors as a ligand. This study suggests directions for new therapeutic strategies for Alzheimer's disease targeting glycosyltransferases.

Arterial embolization via retrograde approach using steerable microcatheter and triaxial system.

We report a case of postoperative pseudoaneurysm, successfully treated with selective arterial embolization, using a steerable microcatheter and triaxial system via retrograde approach. A pseudoaneurysm was detected in the dorsal pancreatic artery, a severely narrow and steeply inverted branch of the superior mesenteric artery, making microcatheter insertion via the antegrade approach challenging. However, a steerable microcatheter was advanced beyond the orifice and the tip was reversed, changing the route to retrograde allowing for easy insertion of the microguidewire. Subsequently, a small microcatheter was advanced beyond the pseudoaneurysm into the dorsal pancreatic artery, and arterial embolization was successfully completed without complications.

Evaluation of the ear ossicles with photon-counting detector CT.

Recently, computed tomography with photon-counting detector (PCD-CT) has been developed to enable high-resolution imaging at a lower radiation dose. PCD-CT employs a photon-counting detector that can measure the number of incident X-ray photons and their energy. The newly released PCD-CT (NAEOTOM Alpha, Siemens Healthineers, Forchheim, Germany) has been in clinical use at our institution since December 2022. The PCD-CT offers several advantages over current state-of-the-art energy-integrating detector CT (EID-CT). The PCD-CT does not require septa to create a detector channel, while EID-CT does. Therefore, downsizing the anode to achieve higher resolution does not affect the dose efficiency of the PCD-CT. CT is an indispensable modality for evaluating ear ossicles. The ear ossicles and joints are clearly depicted by PCD-CT. In particular, the anterior and posterior legs of the stapes, which are sometimes unclear on conventional CT scans, can be clearly visualized. We present cases of congenital anomalies of the ossicular chain, ossicular chain dislocation, tympanosclerosis, and cholesteatoma in which PCD-CT was useful. This short article reports the usefulness of PCD-CT in the 3D visualization of the ear ossicles.

Fairness of artificial intelligence in healthcare: review and recommendations.

In this review, we address the issue of fairness in the clinical integration of artificial intelligence (AI) in the medical field. As the clinical adoption of deep learning algorithms, a subfield of AI, progresses, concerns have arisen regarding the impact of AI biases and discrimination on patient health. This review aims to provide a comprehensive overview of concerns associated with AI fairness; discuss strategies to mitigate AI biases; and emphasize the need for cooperation among physicians, AI researchers, AI developers, policymakers, and patients to ensure equitable AI integration. First, we define and introduce the concept of fairness in AI applications in healthcare and radiology, emphasizing the benefits and challenges of incorporating AI into clinical practice. Next, we delve into concerns regarding fairness in healthcare, addressing the various causes of biases in AI and potential concerns such as misdiagnosis, unequal access to treatment, and ethical considerations. We then outline strategies for addressing fairness, such as the importance of diverse and representative data and algorithm audits. Additionally, we discuss ethical and legal considerations such as data privacy, responsibility, accountability, transparency, and explainability in AI. Finally, we present the Fairness of Artificial Intelligence Recommendations in healthcare (FAIR) statement to offer best practices. Through these efforts, we aim to provide a foundation for discussing the responsible and equitable implementation and deployment of AI in healthcare.

Automated Feeder-Detection Software for Renal Cell Carcinoma Embolization: A Retrospective Evaluation of Detection Rate Using Transarterial Time-Resolved Computed Tomography Angiography.

PURPOSE: To evaluate the detection rate of feeding arteries in renal cell carcinoma with automated feeder-detection software and determine the optimal imaging phase for accurate feeder detection with transarterial time-resolved computed tomography angiography. MATERIALS AND METHODS: The performance of automated feeder-detection software was retrospectively evaluated using transarterial renal time-resolved computed tomography angiography images of 15 renal cell carcinomas (mean size, 22.1 mm); the images were obtained via the renal artery using a hybrid angio-CT system with 320-row computed tomography, across nine phases with 0.5-s intervals over a contrast delay time of 1.0-5.0 s. Automated feeder-detection software was applied to each phase in all tumors (135 image series in total). The feeder-detection rate (i.e., sensitivity) in each phase was evaluated, and the number of false feeders demonstrated by the software was counted for each tumor. RESULTS: A total of 22 feeders were identified. The feeder-detection rate was the highest (95.5% [21/22]) at delay times of 1.5 s and 2.0 s and lower in later phases. At delay times of 1.0 s and 1.5 s, the software demonstrated no or only a few (≤ 3) false feeders in 93.3% (14/15) of the tumors. In later phases, however, many (≥ 4) false feeders were observed in > 50% of tumors. CONCLUSION: The automated feeder-detection software showed a favorable feeder-detection rate and may be useful in transarterial embolization for renal cell carcinoma. The optimal delay time to avoid the demonstration of false feeders and achieve a high detection accuracy was 1.5 s. LEVEL OF EVIDENCE IV: Case Series.

Time course of complications after small renal mass biopsy: evaluation of initial follow-up images.

PURPOSE: To retrospectively assess the time course of complications after image-guided small renal mass biopsy using initial follow-up imaging. MATERIALS AND METHODS: A total of 190 masses (mean, 2.1 ± 0.70 cm; range, 0.6-3.8 cm) were assessed using initial computed tomography (43 non-enhanced and 141 enhanced) or magnetic resonance imaging (five non-enhanced and one enhanced) after biopsy. Initial follow-up imaging was classified into two groups (i.e., with or without hematoma) and various factors were compared. RESULTS: The masses were histologically diagnosed in all patients except one. Post-procedural complications included 129 Grade I hematomas, 1 Grade I hemothorax, 9 Grade II hematomas, and 1 Grade IIIa pneumothorax. Residual 28 Grade I and 6 Grade II hematomas and 8 new complications (6 small hematomas, 1 pseudoaneurysm, and 1 arteriovenous fistula) were observed on the initial follow-up imaging obtained at a median of 21 days (3-90 days) after the biopsy. On the initial follow-up imaging, the groups with and without hematoma differed significantly in the following factors: age (P = 0.04), size (P = 0.02), guided images (P < 0.01), hematoma at the end of the procedure (P < 0.01), and days after biopsy (P < 0.01). Although three masses exhibited > 25% shrinkage, no significant change was observed in mass diameter on initial follow-up imaging (mean, 2.1 ± 0.71 cm; P = 0.90). CONCLUSION: Initial follow-up imaging after a biopsy revealed improvements in most of the complications, a few new complications, and an unchanged mass diameter.

Revolutionizing radiation therapy: the role of AI in clinical practice.

This review provides an overview of the application of artificial intelligence (AI) in radiation therapy (RT) from a radiation oncologist's perspective. Over the years, advances in diagnostic imaging have significantly improved the efficiency and effectiveness of radiotherapy. The introduction of AI has further optimized the segmentation of tumors and organs at risk, thereby saving considerable time for radiation oncologists. AI has also been utilized in treatment planning and optimization, reducing the planning time from several days to minutes or even seconds. Knowledge-based treatment planning and deep learning techniques have been employed to produce treatment plans comparable to those generated by humans. Additionally, AI has potential applications in quality control and assurance of treatment plans, optimization of image-guided RT and monitoring of mobile tumors during treatment. Prognostic evaluation and prediction using AI have been increasingly explored, with radiomics being a prominent area of research. The future of AI in radiation oncology offers the potential to establish treatment standardization by minimizing inter-observer differences in segmentation and improving dose adequacy evaluation. RT standardization through AI may have global implications, providing world-standard treatment even in resource-limited settings. However, there are challenges in accumulating big data, including patient background information and correlating treatment plans with disease outcomes. Although challenges remain, ongoing research and the integration of AI technology hold promise for further advancements in radiation oncology.