Accurate,robust and harmonized implementation of morpho-functional imaging in treatment planning for personalized radiotherapy

In this work we present a methodology able to use harmonized PET/CT imaging in dose painting by number (DPBN) approach by means of a robust and accurate treatment planning system. Image processing and treatment planning were performed by using a Matlab-based platform, called CARMEN, in which a full Monte Carlo simulation is included. Linear programming formulation was developed for a voxel-by-voxel robust optimization and a specific direct aperture optimization was designed for an efficient adaptive radiotherapy implementation. DPBN approach with our methodology was tested to reduce the uncertainties associated with both, the absolute value and the relative value of the information in the functional image. For the same H&N case, a single robust treatment was planned for dose prescription maps corresponding to standardized uptake value distributions from two different image reconstruction protocols: One to fulfill EARL accreditation for harmonization of [18F]FDG PET/CT image, and the other one to use the highest available spatial resolution. Also, a robust treatment was planned to fulfill dose prescription maps corresponding to both approaches, the dose painting by contour based on volumes and our voxel-by-voxel DPBN. Adaptive planning was also carried out to check the suitability of our proposal. Different plans showed robustness to cover a range of scenarios for implementation of harmonizing strategies by using the highest available resolution. Also, robustness associated to discretization level of dose prescription according to the use of contours or numbers was achieved. All plans showed excellent quality index histogram and quality factors below 2%. Efficient solution for adaptive radiotherapy based directly on changes in functional image was obtained. We proved that by using voxel-by-voxel DPBN approach it is possible to overcome typical drawbacks linked to PET/CT images, providing to the clinical specialist confidence enough for routinely implementation of functional imaging for personalized radiotherapy.Junta de Andalucía (FISEVI, reference project CTS 2482)European Regional Development Fund (FEDER

A Novel Deep Learning Framework for Internal Gross Target Volume Definition from 4D Computed Tomography of Lung Cancer Patients

In this paper, we study the reliability of a novel deep learning framework for internal gross target volume (IGTV) delineation from four-dimensional computed tomography (4DCT), which is applied to patients with lung cancer treated by Stereotactic Body Radiation Therapy (SBRT). 77 patients who underwent SBRT followed by 4DCT scans were incorporated in a retrospective study. The IGTV_DL was delineated using a novel deep machine learning algorithm with a linear exhaustive optimal combination framework, for the purpose of comparison, three other IGTVs base on common methods was also delineated, we compared the relative volume difference (RVI), matching index (MI) and encompassment index (EI) for the above IGTVs. Then, multiple parameter regression analysis assesses the tumor volume and motion range as clinical influencing factors in the MI variation. Experimental results demonstrated that the deep learning algorithm with linear exhaustive optimal combination framework has a higher probability of achieving optimal MI compared with other currently widely used methods. For patients after simple breathing training by keeping the respiratory frequency in 10 BMP, the four phase combinations of 0%, 30%, 50% and 90% can be considered as a potential candidate for an optimal combination to synthesis IGTV in all respiration amplitudes

Measuring the response of human head and neck squamous cell carcinoma to irradiation in a microfluidic model allowing customized therapy

Radiotherapy is the standard treatment for head and neck squamous cell carcinoma (HNSCC), however, radioresistance remains a major clinical problem despite significant improvements in treatment protocols. Therapeutic outcome could potentially be improved if a patient's tumour response to irradiation could be predicted ex vivo before clinical application. The present study employed a bespoke microfluidic device to maintain HNSCC tissue whilst subjecting it to external beam irradiation and measured the responses using a panel of cell death and proliferation markers. HNSCC biopsies from five newly-presenting patients [2 lymph node (LN); 3 primary tumour (PT)] were divided into parallel microfluidic devices and replicates of each tumour were subjected to single-dose irradiation (0, 5, 10, 15 and 20 Gy). Lactate dehydrogenase (LDH) release was measured and tissue sections were stained for cytokeratin (CK), cleaved-CK18 (cCK18), phosphorylated-H2AX (λH2AX) and Ki.67 by immunohistochemistry. In addition, fragmented DNA was detected using terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL). Compared with non.irradiated controls, higher irradiation doses resulted in elevated CK18-labelling index in two lymph nodes [15 Gy; 34.8% on LN1 and 31.7% on LN2 (p=0.006)] and a single laryngeal primary tumour (20 Gy; 31.5%; p=0.014). Significantly higher levels of DNA fragmentation were also detected in both lymph node samples and one primary tumour but at varying doses of irradiation, i.e., LN1 (20 Gy; 27.6%; p=0.047), LN2 (15 Gy; 15.3%; p=0.038) and PT3 (10 Gy; 35.2%; p=0.01). The λH2AX expression was raised but not significantly in the majority of samples. The percentage of Ki.67 positive nuclei reduced dose-dependently following irradiation. In contrast no significant difference in LDH release was observed between irradiated groups and controls. There is clear interand intra-patient variability in response to irradiation when measuring a variety of parameters, which offers the potential for the approach to provide clinically valuable information

Intensity modulated radiation therapy and arc therapy: validation and evolution as applied to tumours of the head and neck, abdominal and pelvic regions

Intensiteitsgemoduleerde radiotherapie (IMRT) laat een betere controle over de dosisdistributie (DD) toe dan meer conventionele bestralingstechnieken. Zo is het met IMRT mogelijk om concave DDs te bereiken en om de risico-organen conformeel uit te sparen. IMRT werd in het UZG klinisch toegepast voor een hele waaier van tumorlocalisaties. De toepassing van IMRT voor de bestraling van hoofd- en halstumoren (HHT) vormt het onderwerp van het eerste deel van deze thesis. De planningsstrategie voor herbestralingen en bestraling van HHT, uitgaande van de keel en de mondholte wordt beschreven, evenals de eerste klinische resultaten hiervan. IMRT voor tumoren van de neus(bij)holten leidt tot minstens even goede lokale controle (LC) en overleving als conventionele bestralingstechnieken, en dit zonder stralingsgeïnduceerde blindheid. IMRT leidt dus tot een gunstiger toxiciteitprofiel maar heeft nog geen bewijs kunnen leveren van een gunstig effect op LC of overleving. De meeste hervallen van HHT worden gezien in het gebied dat tot een hoge dosis bestraald werd, wat erop wijst dat deze “hoge dosis” niet volstaat om alle clonogene tumorcellen uit te schakelen. We startten een studie op, om de mogelijkheid van dosisescalatie op geleide van biologische beeldvorming uit te testen. Naast de toepassing en klinische validatie van IMRT bestond het werk in het kader van deze thesis ook uit de ontwikkeling en het klinisch opstarten van intensiteitgemoduleerde arc therapie (IMAT). IMAT is een rotationele vorm van IMRT (d.w.z. de gantry draait rond tijdens de bestraling), waarbij de modulatie van de intensiteit bereikt wordt door overlappende arcs. IMAT heeft enkele duidelijke voordelen ten opzichte van IMRT in bepaalde situaties. Als het doelvolume concaaf rond een risico-orgaan ligt met een grote diameter, biedt IMAT eigenlijk een oneindig aantal bundelrichtingen aan. Een planningsstrategie voor IMAT werd ontwikkeld, en type-oplossingen voor totaal abdominale bestraling en rectumbestraling werden onderzocht en klinisch toegepast

Integration of patient-reported outcome measures with key clinical outcomes after immediate latissimus dorsi breast reconstruction and adjuvant treatment

Background: linical evidence on patient-reported outcome measures (PROMS) in breast reconstruction is lacking. The aim of this study was to evaluate PROMs in implant-assisted latissimus dorsi (LDI) or tissue-only autologous latissimus dorsi (ALD) flap reconstruction in relation to complications and adjuvant treatments.Methods: this was a prospective cohort study involving six UK centres. Eligible patients had primary early-stage breast cancer. The European Organization for Research and Treatment of Cancer quality-of-life questionnaire (QLQ)-C30 and QLQ-BR23, Functional Assessment of Cancer Therapy—Breast Cancer scale (FACT-B), Body Image Scale, and Hospital Anxiety and Depression Scale were completed before operation and at 3, 6 and 12 months after surgery.Results: a total of 182 patients (82 LDI and 100 ALD) were recruited between 2007 and 2010 with symptomatic (59·9 per cent) or screen-detected (39·6 per cent) cancers. Some 64·3 per cent had lymph node-negative disease; 30 per cent of the LDI group had radiotherapy, compared with 53·0 per cent in the ALD group (P = 0·004). Early complications up to 3 months after surgery were reported in 66 and 51·0 per cent of patients in the LDI and ALD groups respectively (P = 0·062) and long-term complications (4–12 months) in 48 and 45·0 per cent (P = 0·845). Role functioning and pain (P = 0·002 for both) were adversely affected in the ALD group compared with results in the LDI group, with no significant effects of radiotherapy on any health-related quality of life (HRQL). Chemotherapy and early complications adversely affected HRQL, which improved between 3 and 12 months after surgery (P < 0·010 for all).Conclusion: there is evidence of similar HRQL between types of latissimus dorsi breast reconstruction for up to a year after surgery. There appear to be no overarching effects for radiotherapy after mastectomy on the specific HRQL domains studied in the short term. The identification of variables that affect HRQL is important, including their integration into the analysis of PROM

Predicting respiratory motion for real-time tumour tracking in radiotherapy

Purpose. Radiation therapy is a local treatment aimed at cells in and around a tumor. The goal of this study is to develop an algorithmic solution for predicting the position of a target in 3D in real time, aiming for the short fixed calibration time for each patient at the beginning of the procedure. Accurate predictions of lung tumor motion are expected to improve the precision of radiation treatment by controlling the position of a couch or a beam in order to compensate for respiratory motion during radiation treatment. Methods. For developing the algorithmic solution, data mining techniques are used. A model form from the family of exponential smoothing is assumed, and the model parameters are fitted by minimizing the absolute disposition error, and the fluctuations of the prediction signal (jitter). The predictive performance is evaluated retrospectively on clinical datasets capturing different behavior (being quiet, talking, laughing), and validated in real-time on a prototype system with respiratory motion imitation. Results. An algorithmic solution for respiratory motion prediction (called ExSmi) is designed. ExSmi achieves good accuracy of prediction (error $4-9$ mm/s) with acceptable jitter values (5-7 mm/s), as tested on out-of-sample data. The datasets, the code for algorithms and the experiments are openly available for research purposes on a dedicated website. Conclusions. The developed algorithmic solution performs well to be prototyped and deployed in applications of radiotherapy

Computer- and robot-assisted Medical Intervention

Medical robotics includes assistive devices used by the physician in order to make his/her diagnostic or therapeutic practices easier and more efficient. This chapter focuses on such systems. It introduces the general field of Computer-Assisted Medical Interventions, its aims, its different components and describes the place of robots in that context. The evolutions in terms of general design and control paradigms in the development of medical robots are presented and issues specific to that application domain are discussed. A view of existing systems, on-going developments and future trends is given. A case-study is detailed. Other types of robotic help in the medical environment (such as for assisting a handicapped person, for rehabilitation of a patient or for replacement of some damaged/suppressed limbs or organs) are out of the scope of this chapter.Comment: Handbook of Automation, Shimon Nof (Ed.) (2009) 000-00