ABSTRACT
Ultrasound guidance is not in widespread use in prostate cancer radiotherapy workflows. This can be partially attributed to the need for image interpretation by a trained operator during ultrasound image acquisition. In this work, a one-class regressor, based on DenseNet and Gaussian processes, was implemented to automatically assess the quality of transperineal ultrasound images of the male pelvic region. The implemented deep learning approach was tested on 300 transperineal ultrasound images and it achieved a scoring accuracy of 94%, a specificity of 95% and a sensitivity of 92% with respect to the majority vote of 3 experts, which was comparable with the results of these experts. This is the first step toward a fully automatic workflow, which could potentially remove the need for ultrasound image interpretation and make real-time volumetric organ tracking in the radiotherapy environment using ultrasound more appealing.
Subject(s)
Deep Learning , Pelvis/diagnostic imaging , Adult , Aged , Aged, 80 and over , Humans , Male , Middle Aged , Perineum , Ultrasonography/methods , Ultrasonography/standardsABSTRACT
BACKGROUND: A multifactorial decision support system (mDSS) is a tool designed to improve the clinical decision-making process, while using clinical inputs for an individual patient to generate case-specific advice. The study provides an overview of the literature to analyze current available mDSS focused on prostate cancer (PCa), in order to better understand the availability of decision support tools as well as where the current literature is lacking. METHODS: We performed a MEDLINE literature search in July 2018. We divided the included studies into different sections: diagnostic, which aids in detection or staging of PCa; treatment, supporting the decision between treatment modalities; and patient, which focusses on informing the patient. We manually screened and excluded studies that did not contain an mDSS concerning prostate cancer and study proposals. RESULTS: Our search resulted in twelve diagnostic mDSS; six treatment mDSS; two patient mDSS; and eight papers that could improve mDSS. CONCLUSIONS: Diagnosis mDSS is well represented in the literature as well as treatment mDSS considering external-beam radiotherapy; however, there is a lack of mDSS for other treatment modalities. The development of patient decision aids is a new field of research, and few successes have been made for PCa patients. These tools can improve personalized medicine but need to overcome a number of difficulties to be successful and require more research.
Subject(s)
Decision Support Systems, Clinical , Prostatic Neoplasms/therapy , Humans , Male , Patient Participation , Prostatic Neoplasms/diagnosisABSTRACT
The current standard of care for locally advanced inoperable non-small cell lung cancer is high dose radiotherapy with concurrent chemotherapy. We report on a patient with stage IIIA NSCLC treated with concurrent chemoradiotherapy on the primary tumor and the 18-fluorodeoxyglucose positron emission tomography ((18)FDG-PET) positive hilar and mediastinal lymph nodes. Six months after treatment this patient developed a single isolated contralateral mediastinal nodal relapse outside but in the proximity of the irradiated target volume. This patient was successfully re-irradiated to this isolated nodal relapse after reconstruction of the dose given to the localisation of this regional recurrence. This case describes the clinical problem of a regional recurrence after involved field radiotherapy that occasionally occurs. A possible explanation for those regional recurrences is an under staging of extension of the disease because the time-interval between the staging (18)FDG-PET-CT scan and the start of the irradiation was too long. If the time-interval is 4 weeks or more, we strongly recommend a new (18)FDG-PET-CT because of the possibility of upstaging of the disease.
