A case of surgical treatment for recurrence of right ventricular metastasis due to renal cell carcinoma after molecular targeted therapy.

BACKGROUND: Cardiac metastasis including the right ventricle from renal cell carcinoma is rare. No standard treatment for cardiac metastasis and recurrence in renal cell carcinoma has been established. CASE PRESENTATION: We present the case of a 61-year-old man who underwent the resection of recurrent right ventricular metastasis caused by renal cell carcinoma following molecular targeted therapy. The first cardiac operation was performed for right ventricular metastasis due to renal cell carcinoma. The patient had a good postoperative course. Two years after the first operation, however, follow-up computed tomography revealed the recurrence of the right ventricular tumor and metastases in both lungs. Molecular targeted therapy was carried out and effectively controlled the lung metastasis but the right ventricular lesion remained unchanged, leading to reoperation. The recurrent right ventricular tumor was completely resected through a redo median sternotomy assisted by cardiopulmonary bypass. The patient had an uneventful postoperative course and was discharged on the 13th postoperative day. Follow-ups at 2 years showed no cardiac recurrence. CONCLUSION: Surgical intervention was considered useful in managing the recurrence of right ventricular metastasis from renal cell carcinoma after molecular targeted therapy.

Predictability of combining Technetium-99m-galactosyl human serum albumin single-photon emission computed tomography/computed tomography and indocyanine green clearance test for posthepatectomy liver failure.

PURPOSE: To evaluate the predictive ability of combining Technetium-99m-galactosyl human serum albumin (99mTc­GSA) single-photon emission computed tomography (SPECT)/computed tomography (CT) volume and plasma clearance rate of indocyanine green (ICGK) for posthepatectomy liver failure (PHLF). MATERIALS AND METHODS: Fifty patients who underwent 99mTc-GSA scintigraphy as a preoperative examination for segmentectomy or more from July 2021 to June 2023 were evaluated prospectively. Patients were divided into two groups according to the presence or absence of posthepatectomy liver failure (PHLF). Total functional liver volume (t-FLV) and remnant FLV (r-FLV) were measured from 99mTc-GSA SPECT/CT image. Future liver remnant ICGK (ICGK-F) was calculated by ICGK and remnant liver volume from CT. Area under the curve (AUC) of ICGK-F, r-FLV, r-FLV/t-FLV, ICGK × r-FLV, ICGK × r-FLV/t-FLV was calculated to evaluate predictive ability of each parameter for PHLF. RESULTS: PHLF was occurred in 7 patients. AUC of ICGK × r-FLV was significantly higher than that of ICGK-F (0.99; 95% confidence interval [CI]: 0.96-1 vs 0.82; 95%CI: 0.64-0.96; p = 0.036). There was no significant difference between the AUC of r-FLV, r-FLV/t-FLV, ICGK × r-FLV/t-FLV and that of ICGK-F, respectively. CONCLUSION: The combination of 99mTc­GSA SPECT/CT volume and ICGK can predict PHLF more accurately than ICGK-F.

Modeling of cell cultivation for monoclonal antibody production processes considering lactate metabolic shifts.

Demand for monoclonal antibodies (mAbs) is rapidly increasing. To achieve higher productivity, there have been improvements to cell lines, operating modes, media, and cultivation conditions. Representative mathematical models are needed to narrow down the growing number of process alternatives. Previous studies have proposed mechanistic models to depict cell metabolic shifts (e.g., lactate production to consumption). However, the impacts of variations of some operating conditions have not yet been fully incorporated in such models. This paper offers a new mechanistic model considering variations in dissolved oxygen and glutamine depletion on cell metabolism applied to a novel Chinese hamster ovary (CHO) cell line. Expressions for the specific rates of lactate production, glutamine consumption, and mAb production were formulated for stirred and shaken-tank reactors. A deeper understanding of lactate metabolic shifts was obtained under different combinations of experimental conditions. Lactate consumption was more pronounced in conditions with higher DO and low glutamine concentrations. The model offers mechanistic insights that are useful for designing advanced operation strategies. It can be used in design space generation and process optimization for better productivity and product quality.

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.

Effect of the Relationship between Respiratory Interval and Temporal Resolution on Image Quality in Free-breathing Abdominal MR Imaging.

PURPOSE: To evaluate how the relationship between respiratory interval (RI) and temporal resolution (TR) impacts image quality in free-breathing abdominal MRI (FB-aMRI) using golden-angle radial sparse parallel (GRASP). METHODS: Ten healthy volunteers (25.9 ± 2.5 years, four women) underwent 2 mins free-breathing fat-suppression T1-weighted imaging using GRASP at RIs of 3 and 5s (RI3 and RI5, respectively) and retrospectively reconstructed at TR of 1.8, 2.9, 4.8, and 7.7s (TR1.8, TR2.9, TR4.8, and TR7.7, respectively) in each patient. The standard deviation (SD) under the diaphragm was measured using SD maps showing the discrepancy for each horizontal section at all TRs. Two radiologists evaluated image quality (visualization of the right hepatic vein at the confluence of the inferior vena cava, posterior segment branch of portal vein, pancreas, left kidney, and artifacts) at all TRs using a 5-point scale. RESULTS: The SD was significantly higher at TR1.8 compared to TR4.8 (P < 0.01) and TR7.7 (P < 0.001), as well as at TR2.9 compared to TR7.7 (P < 0.01) for both RIs. The SD between TR4.8 and TR7.7 did not differ for both RIs. For all visual assessment metrics, the TR1.8 scores were significantly lower than the TR4.8 and TR7.7 scores for both RIs. The pancreas and left kidney scores at TR2.9 were significantly lower than those at TR7.7 (P < 0.05) for RI5. Additionally, the left kidney score at TR1.8 was lower than that at TR2.9 (P < 0.05) for RI3. All scores at TR2.9, TR4.8, and TR7.7 were similar for RI3, while those at TR4.8 and TR7.7 were similar for RI5. CONCLUSION: Prolonging the TRs compared to RIs enhances image quality in FB-aMRI using GRASP.

Validating a New Surgical Gouge for Autogenous Ear Reconstruction During Simulated Microtia Workshops.

Autologous ear reconstruction remains a gold standard surgical technique for the treatment of external ear deformities. This highly technical procedure requires experience, an understanding of aesthetic principles, and a surgical approach that can consistently produce optimal results. As an experienced microtia surgeon having trained under Dr Satoru Nagata, the senior author has emphasized the importance of appropriate surgical tools during this procedure. Here, we present results of a novel surgical handle and gouge meant to optimize complex cartilage carving. The senior author regularly holds microtia workshops to help train individuals around the United States. During 2 of such workshops held in 2022, participants were given access to both the standard, commercially available surgical gouge as well as a prototype of a novel surgical gouge developed by the authors. Participants were then given a Likert-scale survey to assess their subjective feedback for both tools. Twenty-seven total participants completed the postworkshop survey. Cumulatively, the results demonstrated that participants rated the custom gouge significantly higher than its counterpart (4.2 versus 3.2, P<0.001). They also had a significantly higher likelihood of using the custom gouge again (4.1 versus 3.2, P=0.023). The custom gouge designed by the senior author demonstrated higher subjective ratings when compared with what is currently available on the market. This serves as a primary validation study that demonstrates feasibility for further assessment in a true operative setting.

Assessing the Current State of Microtia Reconstruction in the United States.

OBJECTIVE: Microtia is a congenital ear deformity with variability in surgical techniques and tools across surgeons pursuing an autologous reconstruction. Different techniques have emerged over time, and surgeons opt for various tools to aid in creating the complex three-dimensional cartilaginous ear framework. The purpose of this study was to understand the current state of microtia reconstruction in the United States. METHODS: Microtia surgeons affiliated with the nonprofit, Ear Community, were invited to complete a 20-item survey. Data were collected on demographic information regarding surgeons, considerations when approaching microtia repair in patients, and techniques and comfort levels. Additional data were collected on materials, tools, flaps, and skin grafts used for reconstruction. RESULTS: Twenty-two surgeons responded to the survey reporting 3 different techniques learned and utilized in practice including the Brent, Nagata, and Firmin techniques. About two-thirds of surgeons were "extremely comfortable" with their techniques and one-third were "extremely uncomfortable" or "somewhat uncomfortable." Most respondents reported using a tunneled temporoparietal fascial flap or a posterior fascial flap along with a full-thickness skin graft for the second stage (ear elevation). Most surgeons utilized a combination of scalpels and gouges when carving the ear framework along with sutures or wire. CONCLUSIONS: This study highlights the current state of autogenous microtia reconstruction underscoring the variability in approaches and preferences. These data may guide future directions that aim to improve patient outcomes. Surgeons may gain insight into different practices and choose to adopt different aspects to enhance their surgical approach.

Three-dimensional Hemifacial Microsomia Classification with New Subtypes Based on the Pruzansky and Kaban Classification.

Background: Various classifications of hemifacial microsomia (HFM) have been described previously. Although some of these classifications are used widely, others use external outlines of reference organs, even in three-dimensional (3D) images. The purpose of this study was to investigate the 3D characteristics of the mandibular condyle in HFM and to update the Pruzansky and Kaban classification as a 3D classification. Methods: Fifty-three patients with HFM were classified according to the Pruzansky and Kaban classification (type I, IIA, IIB, and III) using computed tomographic scan images. 3D images of the mandible were isolated, and the 3D characteristics were observed; furthermore, the angle of inclination of the mandibular condyle was measured in 3D. Results: Subtypes of retroflexed mandibular condyle in 3D were observed in the Pruzansky and Kaban classification type IIA and IIB, termed as type IIAß (33.3% in type IIA) and type IIBß (100% in type IIB). Although some differences were observed in the inclination of the mandibular condyle between the control and the affected sides in type I and IIAα, multiple differences were observed in type IIAß and IIBß. Conclusions: To the best of our knowledge, this is the first report that identified the retroflexed mandibular condyle as subtypes type IIAß and IIBß. Notably, this could not be identified in the two-dimensional images (lateral cephalogram) yet. We proposed to update the Pruzansky and Kaban classification as a 3D classification with a new 3D subtype. The angle of the retroflexed mandibular condyle may predict mandibular growth in HFM.

Update on Total Auricular Construction.

LEARNING OBJECTIVES: After studying this article, the participant should be able to: 1. Understand principles of preoperative planning for microtia repair. 2. Understand key techniques for flap design, skin envelope dissection, framework creation, and donor-site reconstruction. 3. Describe important components of postoperative management. SUMMARY: Total auricular construction remains a challenge for reconstructive surgeons. This article describes current surgical strategies and advancements for microtia construction. The authors' focus is to describe the several keys for success that are useful for young surgeons who wish to train themselves to create satisfactory results.

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.

Embolization using both n-butyl cyanoacrylate and gelatin sponges in a patient with a posterior superior pancreaticoduodenal artery pseudoaneurysm that ruptured and bled into the drain tube.

Transcatheter arterial embolization is a useful treatment for postpancreatectomy hemorrhage, a severe complication of pancreatic surgery. N-butyl cyanoacrylate is a liquid and permanent embolic material that is widely used in transcatheter arterial embolization. However, its use can lead to the adherence of the catheter to the vessel wall and occlusion of the catheter lumen. This case report presents the case of a 63-year-old man with a postpancreatectomy posterior superior pancreaticoduodenal artery pseudoaneurysm, which ruptured and bled into a drain tube. The patient underwent transcatheter arterial embolization using N-butyl cyanoacrylate and a gelatin sponge without the incidence of adherence or occlusion of the drain tube. Gelatin sponge, which was used as a temporary embolic material, was effective in preventing the drain tube from adhering and occluding.

Usefulness of intratumoral perfusion analysis for assessing biological features of non-functional pancreatic neuroendocrine neoplasm.

PURPOSE: Here, we evaluated the usefulness of intratumoral perfusion analysis using preoperative contrast-enhanced CT (E-CT) to assess biological features of non-functional pancreatic neuroendocrine neoplasms (NF-PanNENs). METHODS: We retrospectively studied 44 patients who underwent curative surgery for NF-PanNENs. We used preoperative E-CT with compartment model analysis to calculate the tumor perfusion parameters K1 (inflow rate constant), 1/k2 (mean transit time), and K1/k2 (distribution volume). We assessed the association between perfusion parameters and biological features of NF-PanNENs, including the WHO classification tumor histopathological grade and prognosis after surgery. RESULTS: Patients in this study had a neuroendocrine tumor (NET) G1 (n = 32) or NET G2 (n = 12). Neither NET G3 or NEC tumors were observed. Among perfusion parameters, K1 was the most accurate predictor of the high-grade tumor (AUC: 0.726). K1-low (< 0.028 s-1) was significantly associated with large tumors (≥ 20 mm) (p = 0.022), high mitotic index (p = 0.017), high Ki-67 index (p = 0.004), and lymphatic invasion (p = 0.025). Synchronous extra-pancreatic metastasis, including lymph node metastasis or liver metastasis, more frequently developed in K1-low patients than in K1-high patients (29% vs 4%, p = 0.025). Disease-free survival of patients with a K1-low tumor was poorer than that of patients with a K1-high tumor (p = 0.005). Furthermore, no patient with a K1-high tumor developed recurrence after initial surgery. CONCLUSION: The perfusion parameters obtained using E-CT were significantly associated with biological features and prognosis of NF-PanNENs.

Assessment of the renal angina index in patients hospitalized in a cardiac intensive care unit.

The renal angina index (RAI) is a validated scoring tool for predicting acute kidney injury (AKI). We investigated the efficacy of the RAI in 2436 heterogeneous patients (mean age, 70 years) treated in cardiac intensive care units (CICUs). The RAI was calculated from creatinine and patient condition scores. AKI was diagnosed by the Kidney Disease: Improving Global Outcome criteria. The primary and secondary endpoints were the development of severe AKI and all-cause mortality, respectively. Four hundred thirty-three patients developed AKI, 87 of them severe. In multivariate analyses, the RAI was a significant independent predictor of severe AKI. During the 12-month follow-up period, 210 patients suffered all-cause death. Elevated RAI was independently associated with all-cause mortality, as was NT-proBNP (p < 0.001). The RAI is a potent predictor not only of severe AKI but also of adverse outcomes and substantially improved the 12-month risk stratification of patients hospitalized in CICUs.

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.

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.

Serial assessment of computed tomography angiography for pulmonary and systemic arteries using a reduced contrast agent dose for the diagnosis of systemic artery-to-pulmonary artery shunts.

PURPOSE: To evaluate the diagnostic performance and feasibility of a modified computed tomography (CT) scan protocol, we performed a serial assessment of the computed tomography angiography for pulmonary artery (CTA-P) and systemic artery (CTA-S) (CTA-PS) using a reduced contrast agent dose to diagnose systemic artery-to-pulmonary artery shunts (SPSs). MATERIALS AND METHODS: Twenty-five patients who underwent multiphase contrast-enhanced chest CT and conventional chest angiography were included. Three image sets (CTA-P, CTA-S, and CTA-PS) were evaluated by two board-certified radiologists. The visualization of the CT image findings associated with SPSs, such as filling defects and enhancement in the pulmonary arteries, was evaluated using a 5-point scale. RESULTS: The diagnostic performance (sensitivity, specificity, and accuracy) of CT imaging findings associated with SPSs in CTA-P and CTA-PS were as follows: CTA-P, 57.1%, 87.5%, and 62.0%; CTA-PS, 81.0%, 100.0%, and 84.0%. CT findings associated with SPSs in CTA-P were significantly sensitive to the CTA-PS protocol. There were no significant differences between the CTA-S and CTA-PS protocols. The area under the curve (AUC) of the CT imaging findings associated with SPSs in the CTA-P and CTA-PS groups was 0.835 and 0.911, respectively (P = 0.191). The AUC of the CT imaging findings associated with SPSs in CTA-S and CTA-PS were 0.891 and 0.926, respectively (P = 0.373). CONCLUSION: CTA-PS using a reduced contrast agent dose protocol could improve the overall diagnostic confidence of SPSs, owing to better visualization of CT imaging findings associated with SPSs compared to individual assessments of CTA-P or CTA-S. Therefore, CTA-PS can be used as an alternative preembolization evaluation modality to conventional angiography in patients with hemoptysis suspected of having SPSs.

Resting echocardiographic parameters to detect patients with less symptomatic primary mitral regurgitation who require exercise stress echocardiography.

Objectives: We aimed to identify which resting echocardiographic parameters can detect asymptomatic or mildly symptomatic patients with primary mitral regurgitation (MR) who require exercise stress echocardiography (ESE) to determine their suitability for surgery. Methods: We examined 56 consecutive patients with primary moderate/severe MR who underwent ergometer-based ESE. Patients who met the surgical indications at rest were excluded. Eligible patients were divided into Group I (pulmonary artery systolic pressure [PASP] during exercise >60 mmHg; n=11) and Group II (PASP during exercise ≤60 mmHg; n=30). Results: Forty-one patients were included. Group I was significantly older (65±12 vs. 54±14 years, P=0.042) and had significantly higher serum N-terminal pro-B-type natriuretic peptide concentrations than Group II (351±278 vs. 125±163 pg/mL, P=0.002). The univariate analysis demonstrated that peak E wave velocity (Group I vs. Group II: 125±45 vs. 101±24 cm/sec, P=0.050), left ventricular (LV) end-diastolic diameter index (32±4 vs. 30±3 mm/m2, P=0.035), and left atrial volume index (LAVI; 45±14 vs. 30±11 mL/m2, P=0.008) were predictors of increased PASP during exercise. In the multivariate analysis, resting LAVI best predicted exercise-induced pulmonary hypertension (hazard ratio 1.081 [95% confidence interval 1.009-1.158], P=0.028), with a cutoff value of 37 mL/m2. Conclusions: In asymptomatic or mildly symptomatic patients with primary moderate/severe MR, increased resting LAVI indicates the requirement for ESE, even without LV dilatation.