Despite existing curative options like surgical removal,tissue destruction techniques,and liver transplantation for early-stage hepatocellular carcinoma(HCC),the rising incidence and mortality rates of this global hea...Despite existing curative options like surgical removal,tissue destruction techniques,and liver transplantation for early-stage hepatocellular carcinoma(HCC),the rising incidence and mortality rates of this global health burden necessitate continuous exploration of novel therapeutic strategies.This review critically assesses the dynamic treatment panorama for HCC,focusing specifically on the burgeoning role of immunotherapy in two key contexts:early-stage HCC and downstaging advanced HCC to facilitate liver transplant candidacy.It delves into the unique immunobiology of the liver and HCC,highlighting tumor-mediated immune evasion mechanisms.Analyzing the diverse immunothera-peutic approaches including checkpoint inhibitors,cytokine modulators,vaccines,oncolytic viruses,antigen-targeting antibodies,and adoptive cell therapy,this review acknowledges the limitations of current diagnostic markers alpha-fetoprotein and glypican-3 and emphasizes the need for novel biomarkers for patient selection and treatment monitoring.Exploring the rationale for neoadjuvant and adjuvant immunotherapy in early-stage HCC,current research is actively exploring the safety and effectiveness of diverse immunothera-peutic approaches through ongoing clinical trials.The review further explores the potential benefits and challenges of combining immunotherapy and liver transplant,highlighting the need for careful patient selection,meticulous monitoring,and novel strategies to mitigate post-transplant complications.Finally,this review delves into the latest findings from the clinical research landscape and future directions in HCC management,paving the way for optimizing treatment strategies and improving long-term survival rates for patients with this challenging malignancy.展开更多
The diagnosis and prognosis of Prostate cancer(PCa)have undergone a significant transformation with the advent of prostate-specific membrane antigen(PSMA)-targeted positron emission tomography(PET)imaging.PSMAPET imag...The diagnosis and prognosis of Prostate cancer(PCa)have undergone a significant transformation with the advent of prostate-specific membrane antigen(PSMA)-targeted positron emission tomography(PET)imaging.PSMAPET imaging has demonstrated superior performance compared to conventional imaging methods by detecting PCa,its biochemical recurrence,and sites of metastasis with higher sensitivity and specificity.That transformation now intersects with rapid advances in artificial intelligence(AI)–including the emergence of generative AI.However,there are unique clinical challenges associated with PSMA-PET imaging that still need to be addressed to ensure its continued widespread integration into clinical care and research trials.Some of those challenges are the very wide dynamic range of lesion uptake,benign uptake in organs that may be adjacent to sites of disease,insufficient large datasets for training AI models,as well as artifacts in the images.Generative AI models,e.g.,generative adversarial networks,variational autoencoders,diffusion models,and large language models have played crucial roles in overcoming many such challenges across various imaging modalities,including PET,computed tomography,magnetic resonance imaging,ultrasound,etc.In this review article,we delve into the potential role of generative AI in enhancing the robustness and widespread utilization of PSMA-PET imaging and image analysis,drawing insights from existing literature while also exploring current limitations and future directions in this domain.展开更多
文摘Despite existing curative options like surgical removal,tissue destruction techniques,and liver transplantation for early-stage hepatocellular carcinoma(HCC),the rising incidence and mortality rates of this global health burden necessitate continuous exploration of novel therapeutic strategies.This review critically assesses the dynamic treatment panorama for HCC,focusing specifically on the burgeoning role of immunotherapy in two key contexts:early-stage HCC and downstaging advanced HCC to facilitate liver transplant candidacy.It delves into the unique immunobiology of the liver and HCC,highlighting tumor-mediated immune evasion mechanisms.Analyzing the diverse immunothera-peutic approaches including checkpoint inhibitors,cytokine modulators,vaccines,oncolytic viruses,antigen-targeting antibodies,and adoptive cell therapy,this review acknowledges the limitations of current diagnostic markers alpha-fetoprotein and glypican-3 and emphasizes the need for novel biomarkers for patient selection and treatment monitoring.Exploring the rationale for neoadjuvant and adjuvant immunotherapy in early-stage HCC,current research is actively exploring the safety and effectiveness of diverse immunothera-peutic approaches through ongoing clinical trials.The review further explores the potential benefits and challenges of combining immunotherapy and liver transplant,highlighting the need for careful patient selection,meticulous monitoring,and novel strategies to mitigate post-transplant complications.Finally,this review delves into the latest findings from the clinical research landscape and future directions in HCC management,paving the way for optimizing treatment strategies and improving long-term survival rates for patients with this challenging malignancy.
文摘The diagnosis and prognosis of Prostate cancer(PCa)have undergone a significant transformation with the advent of prostate-specific membrane antigen(PSMA)-targeted positron emission tomography(PET)imaging.PSMAPET imaging has demonstrated superior performance compared to conventional imaging methods by detecting PCa,its biochemical recurrence,and sites of metastasis with higher sensitivity and specificity.That transformation now intersects with rapid advances in artificial intelligence(AI)–including the emergence of generative AI.However,there are unique clinical challenges associated with PSMA-PET imaging that still need to be addressed to ensure its continued widespread integration into clinical care and research trials.Some of those challenges are the very wide dynamic range of lesion uptake,benign uptake in organs that may be adjacent to sites of disease,insufficient large datasets for training AI models,as well as artifacts in the images.Generative AI models,e.g.,generative adversarial networks,variational autoencoders,diffusion models,and large language models have played crucial roles in overcoming many such challenges across various imaging modalities,including PET,computed tomography,magnetic resonance imaging,ultrasound,etc.In this review article,we delve into the potential role of generative AI in enhancing the robustness and widespread utilization of PSMA-PET imaging and image analysis,drawing insights from existing literature while also exploring current limitations and future directions in this domain.
