RESUMEN
PURPOSE OF REVIEW: Management of metastatic head and neck squamous cell cancers (HNSCC) can be challenging. This review gives an insight of current treatment options for patients with synchronous metastatic HNSCC and suggests a therapeutic algorithm. RECENT FINDINGS: With the rise of novel therapeutic techniques and medications, many treatment options for both locoregional and distant metastatic disease have become available. The evolving paradigm of metastatic disease now integrates the concept of oligometastatic disease. On top of systemic treatments, patients with low metastatic burden can benefit from curative approaches such as local therapies (surgery, radiotherapy) directed to either primary tumour and distant metastasis. However, data integrating these considerations in the management of metastatic HNSCC is still lacking. Based on this algorithm, we can provide a tailored treatment to each patient with synchronous metastatic HNSCC, according to their age, general condition and metastatic burden.
Asunto(s)
Neoplasias de Cabeza y Cuello/patología , Neoplasias de Cabeza y Cuello/terapia , Carcinoma de Células Escamosas de Cabeza y Cuello/secundario , Carcinoma de Células Escamosas de Cabeza y Cuello/terapia , Algoritmos , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Terapia Combinada , Neoplasias de Cabeza y Cuello/virología , Humanos , Inmunoterapia , Papillomaviridae/aislamiento & purificación , Pronóstico , Radioterapia , Carcinoma de Células Escamosas de Cabeza y Cuello/virologíaRESUMEN
Radiation oncology is a field that heavily relies on new technology. Data science and artificial intelligence will have an important role in the entire radiotherapy workflow. A new paradigm of routine healthcare data reuse to automate treatments and provide decision support is emerging. This review will discuss the ethical aspects of the use of artificial intelligence (AI) in radiation oncology. More specifically, the review will discuss the evolution of work through the ages, as well as the impact AI will have on it. We will then explain why AI opens a new technical era for the field and we will conclude on the challenges in the years to come.
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Inteligencia Artificial , Oncología por Radiación , Atención a la Salud , Humanos , Flujo de TrabajoRESUMEN
BACKGROUND: Detection rates of [68Ga]Ga-PSMA-11 PET/CT on the restaging of prostate cancer (PCa) patients presenting with biochemical recurrence (BCR) have been well documented, but its performance and impact on patient management have not been evaluated as extensively. METHODS: Retrospective analysis of PCa patients presenting with BCR and referred for [68Ga]Ga-PSMA-11 PET/CT. Pathological foci were classified according to six anatomical sites and evaluated with a three-point scale according to the uptake intensity. The impact of [68Ga]Ga-PSMA-11 PET/CT was defined as any change in management that was triggered by [68Ga]Ga-PSMA-11 PET/CT. The existence of a PCa lesion was established according to a composite standard of truth based on all clinical data available collected during the follow-up period. RESULTS: We included 294 patients. The detection rate was 69%. Per-patient sensitivity and specificity were both 70%. Patient disease management was changed in 68% of patients, and [68Ga]Ga-PSMA-11 PET/CT impacted this change in 86% of patients. The treatment carried out on patient was considered effective in 89% of patients when guided by [68Ga]Ga-PSMA-11 PET/CT versus 61% of patients when not guided by [68Ga]Ga-PSMA-11 PET/CT (p < 0.001). CONCLUSIONS: [68Ga]Ga-PSMA-11 PET/CT demonstrated high performance in locating PCa recurrence sites and impacted therapeutic management in nearly two out of three patients.