Seminars in Radiation Oncology最新文献

Imaging plays an important role in bladder cancer (BCa) diagnostic work-up. Ultrasound achieves an intermediate sensitivity in detecting urinary tract alterations and is considered a suboptimal imaging technique in diagnosis of BCa. CT urography accurately detects BCa in patients presenting with hematuria Multiparametric MRI achieves a very high rate of BCa detection and helps with accurate staging of patients; however, this modality is still not widely supported by international guidelines. The main applications of MRI are local tumor staging and differentiation between non-muscle-invasive BCa and muscle-invasive BCa. These applications led to development of Vesical Imaging-Reporting and Data System (VI-RADS) scoring system. The VI-RADS scoring system was developed in the setting of post-resection of primary bladder tumor and instillation of intravesical Bacillus Calmette-Guerin therapy; however validation of this system in the post-treatment setting showed promising results. The high risk of BCa recurrence leads to its application in the assessment of response to therapy and for disease surveillance after treatment. MRI is rapidly becoming a leading imaging modality in BCa diagnostic workup, assessment of response to therapies and for longitudinal surveillance, and plays an important role in BCa surgical and radiation therapy treatment planning.

Radical cystectomy is long considered as the "gold standard" in the management of localized muscle-invasive bladder cancer (MIBC), and curative intent radiotherapy is relegated to those with either inoperable tumors or with multiple co-morbidities precluding surgery. This is despite a large volume of data showing equal survival between the two modalities of treatment in this setting. In this work we seek to dispel some common myths surrounding curative intent radiotherapy as part of a bladder preservation strategy in MIBC. Baseless claims of inferior outcomes and perceived contraindications for bladder preservation are debunked along with unfounded doubts relating to hypofractionation. Finally, we caution against using response to neoadjuvant chemotherapy as a predictive biomarker for treatment selection and conclude by recommending that trimodality bladder preservation be offered as a therapeutic option that is in clinical equipoise with radical cystectomy.

Machine learning (ML) and artificial intelligence (AI) have demonstrated potential to improve the care of radiation oncology patients. Here we review recent advances applicable to the care of bladder cancer, with an eye towards studies that may suggest next steps in clinical implementation. Algorithms have been applied to clinical records, pathology, and radiology data to generate accurate predictive models for prognosis and clinical outcomes. AI has also shown increasing utility for auto-contouring and efficient creation of workflows involving multiple treatment plans. As technologies progress towards routine clinical use for bladder cancer patients, we also discuss emerging methods to improve interpretability and reliability of algorithms.

For muscle-invasive bladder cancer, the historical, gold standard treatment was radical cystectomy. However, the notion of organ preservation using trimodality therapy (TMT, consisting of maximal transurethral resection of bladder tumor followed by chemoradiation) has been established as a viable treatment alternative to complete removal of the bladder. Despite the lack of direct head-to-head randomized comparisons of TMT to radical cystectomy, the Radiation Therapy Oncology Group (RTOG)/NRG has spearheaded the use of radiation therapy as part of bladder preservation for years, with prospective data demonstrating similar long-term clinical outcomes to cystectomy series, particularly with contemporary treatment. We summarize these trials and discuss the evolution of bladder preservation throughout the decades, culminating in our current TMT protocols. We further discuss the future of organ-preservation therapy in MIBC, with continued improvement in radiation techniques, incorporation of novel therapies, and personalization of treatment to optimize benefit for bladder cancer patients.

For decades, the antineoplastic potential of hyperthermia alone or in combination with radiotherapy and/or chemotherapy has been subject of intensive preclinical and clinical research in various tumor entities. The clinical evidence on the beneficial effects of additional hyperthermia in combination with intravesical Mitomycin C for superficial non-muscle-invasive bladder cancer as well as for deep regional microwave hyperthermia techniques applied during an external beam radiotherapy or chemoradiation treatment for more advanced tumors are summarized. In some series, deep regional hyperthermia in combination with an initial transurethral resection and Cisplatin-based chemoradiation increased the 5-year overall survival rates up to 20%. The presented data justifies a fresh irrespective chance for mild regional hyperthermia in the context of new progressive prospective trials on multimodality treatment for bladder preservation.

A growing body of evidence has shown bladder-preservation with chemo-radiotherapy achieves comparable survival to Radical Cystectomy (5-year OS 50%-70%) and superior quality of life outcomes for patients with muscle-invasive urothelial carcinoma of the bladder (UC). However, up to 55% of patients harbor variant histology and in this review we aim to clarify the role of bladder-preservation for this group. We first draw the distinction between urothelial carcinoma with divergent differentiation (UCDD) and non-urothelial carcinoma (NUC). UCDD is common, increasing in prevalence, and whilst each subtype may have its own characteristics current evidence suggests comparable outcomes with radical cystectomy and bladder-preservation.

Non-urothelial carcinoma is a collection of distinct pathologies each deserving of its own management strategy. However, these tumors are rare, and evidence is generated from retrospective studies with significant inherent bias. Small cell carcinoma of the bladder has good evidence for bladder-preservation; however, other pathologies such as Squamous Cell Carcinoma and Adenocarcinoma are not well supported. We recommend careful multidisciplinary appraisal of the evidence for each subtype and honest patient discussion about the limited evidence before reaching management decisions. As we look to the future molecular-profiling may help better characterize these tumors and aid in treatment selection.

There are limited data regarding the optimal management of patients with pelvic node-positive, but non-metastatic, bladder cancer. Increasing data demonstrate that this is a distinct clinical entity with outcomes bridging between bladder-confined muscle-invasive bladder cancer and metastatic advanced bladder cancer. Guidelines and staging systems have formalized the need to incorporate the unique considerations of management of pelvic node-positive bladder cancer. However, there remains an absence of a definite standard of care. Treatment options include systemic therapy alone, neoadjuvant chemotherapy followed by radical cystectomy, or bladder-preserving trimodality therapy. Furthermore, ongoing studies aim to determine the benefit of incorporating immunotherapy into these treatment paradigms. In this review article, we will discuss the key considerations for management of patients with pelvic node-positive bladder cancer.

Artificial intelligence (AI) has exceptional potential to positively impact the field of radiation oncology. However, large curated datasets - often involving imaging data and corresponding annotations - are required to develop radiation oncology AI models. Importantly, the recent establishment of Findable, Accessible, Interoperable, Reusable (FAIR) principles for scientific data management have enabled an increasing number of radiation oncology related datasets to be disseminated through data repositories, thereby acting as a rich source of data for AI model building. This manuscript reviews the current and future state of radiation oncology data dissemination, with a particular emphasis on published imaging datasets, AI data challenges, and associated infrastructure. Moreover, we provide historical context of FAIR data dissemination protocols, difficulties in the current distribution of radiation oncology data, and recommendations regarding data dissemination for eventual utilization in AI models. Through FAIR principles and standardized approaches to data dissemination, radiation oncology AI research has nothing to lose and everything to gain.

In recent years, Artificial intelligence (AI), specifically deep-learning (DL) based methods, have been employed extensively to solve various problems in brachytherapy. This paper presents a comprehensive literature review on recent developments and applications of AI/DL technologies for different areas in brachytherapy, including image enhancement, registration, segmentation, treatment planning, quality assurance, outcome prediction, etc. The review will emphasize studies addressing unique challenges in brachytherapy, as compared to external beam radiotherapy. Meanwhile, despite exciting achievements, it is also noted that we are still at the early stage of employing AI/DL-technologies to enhance brachytherapy clinical practice. Hence, this paper will also present challenges and future directions. We hope this review will inspire discussions on this topic and trigger future impactful studies to transform technology advancements into healthcare benefits.