Learning Attention Mechanisms and Context: An Investigation into Vision and Emotion

Attention mechanisms for context modelling are becoming ubiquitous in neural architectures in machine learning. The attention mechanism is a technique that filters out information that is irrelevant to a given task and focuses on learning task-dependent fixation points or regions. Furthermore, attention mechanisms suggest a question about a given task, i.e. `what' to learn and `where/how' to learn for task-specific context modelling. The context is the conditional variables instrumental in deciding the categorical distribution for the given data. Also, why is learning task-specific context necessary? In order to answer these questions, context modelling with attention in the vision and emotion domains is explored in this thesis using attention mechanisms with different hierarchical structures. The three main goals of this thesis are building superior classifiers using attention-based deep neural networks~(DNNs), investigating the role of context modelling in the given tasks, and developing a framework for interpreting hierarchies and attention in deep attention networks. In the vision domain, gesture and posture recognition tasks in diverse environments, are chosen. In emotion, visual and speech emotion recognition tasks are chosen. These tasks are selected for their sequential properties for modelling a spatiotemporal context. One of the key challenges from a machine learning standpoint is to extract patterns which bear maximum correlation with the information encoded in its signal while being as insensitive as possible to other types of information carried by the signal. A possible way to overcome this problem is to learn task-dependent representations. In order to achieve that, novel spatiotemporal context modelling networks and the mixture of multi-view attention~(MOMA) networks are proposed using bidirectional long-short-term memory network (BLSTM), convolutional neural network~(CNN), Capsule and attention networks. A framework has been proposed to interpret the internal attention states with respect to the given task. The results of the classifiers in the assigned tasks are compared with the \textit{state-of-the-art} DNNs, and the proposed classifiers achieve superior results. The context in speech emotion recognition is explored deeply with the attention interpretation framework, and it shows that the proposed model can assign word importance based on acoustic context. Furthermore, it has been observed that the internal states of the attention bear correlation with human perception of acoustic cues for speech emotion recognition. Overall, the results demonstrate superior classifiers and context learning models with interpretable frameworks. The findings are very important for speech emotion recognition systems. In this thesis, not only better models are produced, but also the interpretability of those models are explored, and their internal states are analysed. The phones and words are aligned with the attention vectors, and it is seen that the vowel sounds are more important for defining emotion acoustic cues than the consonants, and the model can assign word importance based on acoustic context. Also, how these approaches for emotion recognition using word importance for predicting emotions are demonstrated by the attention weight visualisation over the words. In a broader perspective, the findings from the thesis about gesture, posture and emotion recognition may be helpful in tasks like human-robot interaction~(HRI) and conversational artificial agents (such as Siri, Alexa). The communication is grounded with the symbolic and sub-symbolic cues of intent either from visual, audio or haptics. The understanding of intent is much dependent on the reasoning about the situational context. Emotion, i.e.\ speech and visual emotion, provides context to a situation, and it is a deciding factor in the response generation. Emotional intelligence and information from vision, audio and other modalities are essential for making human-human and human-robot communication more natural and feedback-driven

Proceedings of the 7th Sound and Music Computing Conference

Proceedings of the SMC2010 - 7th Sound and Music Computing Conference, July 21st - July 24th 2010

MANIFOLD REPRESENTATIONS OF MUSICAL SIGNALS AND GENERATIVE SPACES

Tra i diversi campi di ricerca nell\u2019ambito dell\u2019informatica musicale, la sintesi e la generazione di segnali audio incarna la pluridisciplinalita\u300 di questo settore, nutrendo insieme le pratiche scientifiche e musicale dalla sua creazione. Inerente all\u2019informatica dalla sua creazione, la generazione audio ha ispirato numerosi approcci, evolvendo colle pratiche musicale e gli progressi tecnologici e scientifici. Inoltre, alcuni processi di sintesi permettono anche il processo inverso, denominato analisi, in modo che i parametri di sintesi possono anche essere parzialmente o totalmente estratti dai suoni, dando una rappresentazione alternativa ai segnali analizzati. Per di piu\u300, la recente ascesa dei algoritmi di l\u2019apprendimento automatico ha vivamente interrogato il settore della ricerca scientifica, fornendo potenti data-centered metodi che sollevavano diversi epistemologici interrogativi, nonostante i sui efficacia. Particolarmente, un tipo di metodi di apprendimento automatico, denominati modelli generativi, si concentrano sulla generazione di contenuto originale usando le caratteristiche che hanno estratti dei dati analizzati. In tal caso, questi modelli non hanno soltanto interrogato i precedenti metodi di generazione, ma anche sul modo di integrare questi algoritmi nelle pratiche artistiche. Mentre questi metodi sono progressivamente introdotti nel settore del trattamento delle immagini, la loro applicazione per la sintesi di segnali audio e ancora molto marginale. In questo lavoro, il nostro obiettivo e di proporre un nuovo metodo di audio sintesi basato su questi nuovi tipi di generativi modelli, rafforazti dalle nuove avanzati dell\u2019apprendimento automatico. Al primo posto, facciamo una revisione dei approcci esistenti nei settori dei sistemi generativi e di sintesi sonore, focalizzando sul posto di nostro lavoro rispetto a questi disciplini e che cosa possiamo aspettare di questa collazione. In seguito, studiamo in maniera piu\u300 precisa i modelli generativi, e come possiamo utilizzare questi recenti avanzati per l\u2019apprendimento di complesse distribuzione di suoni, in un modo che sia flessibile e nel flusso creativo del utente. Quindi proponiamo un processo di inferenza / generazione, il quale rifletta i processi di analisi/sintesi che sono molto usati nel settore del trattamento del segnale audio, usando modelli latenti, che sono basati sull\u2019utilizzazione di un spazio continuato di alto livello, che usiamo per controllare la generazione. Studiamo dapprima i risultati preliminari ottenuti con informazione spettrale estratte da diversi tipi di dati, che valutiamo qualitativamente e quantitativamente. Successiva- mente, studiamo come fare per rendere questi metodi piu\u300 adattati ai segnali audio, fronteggiando tre diversi aspetti. Primo, proponiamo due diversi metodi di regolarizzazione di questo generativo spazio che sono specificamente sviluppati per l\u2019audio : una strategia basata sulla traduzione segnali / simboli, e una basata su vincoli percettivi. Poi, proponiamo diversi metodi per fronteggiare il aspetto temporale dei segnali audio, basati sull\u2019estrazione di rappresentazioni multiscala e sulla predizione, che permettono ai generativi spazi ottenuti di anche modellare l\u2019aspetto dinamico di questi segnali. Per finire, cambiamo il nostro approccio scientifico per un punto di visto piu\u301 ispirato dall\u2019idea di ricerca e creazione. Primo, descriviamo l\u2019architettura e il design della nostra libreria open-source, vsacids, sviluppata per permettere a esperti o non-esperti musicisti di provare questi nuovi metodi di sintesi. Poi, proponiamo una prima utilizzazione del nostro modello con la creazione di una performance in real- time, chiamata \ue6go, basata insieme sulla nostra libreria vsacids e sull\u2019uso di une agente di esplorazione, imparando con rinforzo nel corso della composizione. Finalmente, tramo dal lavoro presentato alcuni conclusioni sui diversi modi di migliorare e rinforzare il metodo di sintesi proposto, nonche\u301 eventuale applicazione artistiche.Among the diverse research fields within computer music, synthesis and generation of audio signals epitomize the cross-disciplinarity of this domain, jointly nourishing both scientific and artistic practices since its creation. Inherent in computer music since its genesis, audio generation has inspired numerous approaches, evolving both with musical practices and scientific/technical advances. Moreover, some syn- thesis processes also naturally handle the reverse process, named analysis, such that synthesis parameters can also be partially or totally extracted from actual sounds, and providing an alternative representation of the analyzed audio signals. On top of that, the recent rise of machine learning algorithms earnestly questioned the field of scientific research, bringing powerful data-centred methods that raised several epistemological questions amongst researchers, in spite of their efficiency. Especially, a family of machine learning methods, called generative models, are focused on the generation of original content using features extracted from an existing dataset. In that case, such methods not only questioned previous approaches in generation, but also the way of integrating this methods into existing creative processes. While these new generative frameworks are progressively introduced in the domain of image generation, the application of such generative techniques in audio synthesis is still marginal. In this work, we aim to propose a new audio analysis-synthesis framework based on these modern generative models, enhanced by recent advances in machine learning. We first review existing approaches, both in sound synthesis and in generative machine learning, and focus on how our work inserts itself in both practices and what can be expected from their collation. Subsequently, we focus a little more on generative models, and how modern advances in the domain can be exploited to allow us learning complex sound distributions, while being sufficiently flexible to be integrated in the creative flow of the user. We then propose an inference / generation process, mirroring analysis/synthesis paradigms that are natural in the audio processing domain, using latent models that are based on a continuous higher-level space, that we use to control the generation. We first provide preliminary results of our method applied on spectral information, extracted from several datasets, and evaluate both qualitatively and quantitatively the obtained results. Subsequently, we study how to make these methods more suitable for learning audio data, tackling successively three different aspects. First, we propose two different latent regularization strategies specifically designed for audio, based on and signal / symbol translation and perceptual constraints. Then, we propose different methods to address the inner temporality of musical signals, based on the extraction of multi-scale representations and on prediction, that allow the obtained generative spaces that also model the dynamics of the signal. As a last chapter, we swap our scientific approach to a more research & creation-oriented point of view: first, we describe the architecture and the design of our open-source library, vsacids, aiming to be used by expert and non-expert music makers as an integrated creation tool. Then, we propose an first musical use of our system by the creation of a real-time performance, called aego, based jointly on our framework vsacids and an explorative agent using reinforcement learning to be trained during the performance. Finally, we draw some conclusions on the different manners to improve and reinforce the proposed generation method, as well as possible further creative applications.A\u300 travers les diffe\u301rents domaines de recherche de la musique computationnelle, l\u2019analysie et la ge\u301ne\u301ration de signaux audio sont l\u2019exemple parfait de la trans-disciplinarite\u301 de ce domaine, nourrissant simultane\u301ment les pratiques scientifiques et artistiques depuis leur cre\u301ation. Inte\u301gre\u301e a\u300 la musique computationnelle depuis sa cre\u301ation, la synthe\u300se sonore a inspire\u301 de nombreuses approches musicales et scientifiques, e\u301voluant de pair avec les pratiques musicales et les avance\u301es technologiques et scientifiques de son temps. De plus, certaines me\u301thodes de synthe\u300se sonore permettent aussi le processus inverse, appele\u301 analyse, de sorte que les parame\u300tres de synthe\u300se d\u2019un certain ge\u301ne\u301rateur peuvent e\u302tre en partie ou entie\u300rement obtenus a\u300 partir de sons donne\u301s, pouvant ainsi e\u302tre conside\u301re\u301s comme une repre\u301sentation alternative des signaux analyse\u301s. Paralle\u300lement, l\u2019inte\u301re\u302t croissant souleve\u301 par les algorithmes d\u2019apprentissage automatique a vivement questionne\u301 le monde scientifique, apportant de puissantes me\u301thodes d\u2019analyse de donne\u301es suscitant de nombreux questionnements e\u301piste\u301mologiques chez les chercheurs, en de\u301pit de leur effectivite\u301 pratique. En particulier, une famille de me\u301thodes d\u2019apprentissage automatique, nomme\u301e mode\u300les ge\u301ne\u301ratifs, s\u2019inte\u301ressent a\u300 la ge\u301ne\u301ration de contenus originaux a\u300 partir de caracte\u301ristiques extraites directement des donne\u301es analyse\u301es. Ces me\u301thodes n\u2019interrogent pas seulement les approches pre\u301ce\u301dentes, mais aussi sur l\u2019inte\u301gration de ces nouvelles me\u301thodes dans les processus cre\u301atifs existants. Pourtant, alors que ces nouveaux processus ge\u301ne\u301ratifs sont progressivement inte\u301gre\u301s dans le domaine la ge\u301ne\u301ration d\u2019image, l\u2019application de ces techniques en synthe\u300se audio reste marginale. Dans cette the\u300se, nous proposons une nouvelle me\u301thode d\u2019analyse-synthe\u300se base\u301s sur ces derniers mode\u300les ge\u301ne\u301ratifs, depuis renforce\u301s par les avance\u301es modernes dans le domaine de l\u2019apprentissage automatique. Dans un premier temps, nous examinerons les approches existantes dans le domaine des syste\u300mes ge\u301ne\u301ratifs, sur comment notre travail peut s\u2019inse\u301rer dans les pratiques de synthe\u300se sonore existantes, et que peut-on espe\u301rer de l\u2019hybridation de ces deux approches. Ensuite, nous nous focaliserons plus pre\u301cise\u301ment sur comment les re\u301centes avance\u301es accomplies dans ce domaine dans ce domaine peuvent e\u302tre exploite\u301es pour l\u2019apprentissage de distributions sonores complexes, tout en e\u301tant suffisamment flexibles pour e\u302tre inte\u301gre\u301es dans le processus cre\u301atif de l\u2019utilisateur. Nous proposons donc un processus d\u2019infe\u301rence / g\ue9n\ue9ration, refle\u301tant les paradigmes d\u2019analyse-synthe\u300se existant dans le domaine de ge\u301ne\u301ration audio, base\u301 sur l\u2019usage de mode\u300les latents continus que l\u2019on peut utiliser pour contro\u302ler la ge\u301ne\u301ration. Pour ce faire, nous e\u301tudierons de\u301ja\u300 les re\u301sultats pre\u301liminaires obtenus par cette me\u301thode sur l\u2019apprentissage de distributions spectrales, prises d\u2019ensembles de donne\u301es diversifie\u301s, en adoptant une approche a\u300 la fois quantitative et qualitative. Ensuite, nous proposerons d\u2019ame\u301liorer ces me\u301thodes de manie\u300re spe\u301cifique a\u300 l\u2019audio sur trois aspects distincts. D\u2019abord, nous proposons deux strate\u301gies de re\u301gularisation diffe\u301rentes pour l\u2019analyse de signaux audio : une base\u301e sur la traduction signal/ symbole, ainsi qu\u2019une autre base\u301e sur des contraintes perceptives. Nous passerons par la suite a\u300 la dimension temporelle de ces signaux audio, proposant de nouvelles me\u301thodes base\u301es sur l\u2019extraction de repre\u301sentations temporelles multi-e\u301chelle et sur une ta\u302che supple\u301mentaire de pre\u301diction, permettant la mode\u301lisation de caracte\u301ristiques dynamiques par les espaces ge\u301ne\u301ratifs obtenus. En dernier lieu, nous passerons d\u2019une approche scientifique a\u300 une approche plus oriente\u301e vers un point de vue recherche & cre\u301ation. Premie\u300rement, nous pre\u301senterons notre librairie open-source, vsacids, visant a\u300 e\u302tre employe\u301e par des cre\u301ateurs experts et non-experts comme un outil inte\u301gre\u301. Ensuite, nous proposons une premie\u300re utilisation musicale de notre syste\u300me par la cre\u301ation d\u2019une performance temps re\u301el, nomme\u301e \ue6go, base\u301e a\u300 la fois sur notre librarie et sur un agent d\u2019exploration appris dynamiquement par renforcement au cours de la performance. Enfin, nous tirons les conclusions du travail accompli jusqu\u2019a\u300 maintenant, concernant les possibles ame\u301liorations et de\u301veloppements de la me\u301thode de synthe\u300se propose\u301e, ainsi que sur de possibles applications cre\u301atives

Surgery After Neoadjuvant Stereotactic MRI Guided Adaptive Radiation in Pancreatic Cancer: Multi-institutional Toxicity and Survival Outcomes

Background: Favorable toxicity and survival outcomes after dose escalated stereotactic MR guided adaptive radiation therapy (SMART) have been recently published for locally advanced (LA) and borderline resectable (BR) pancreatic cancer. Perioperative morbidity and mortality are not well understood after ablative radiation therapy, which may temper enthusiasm for offering surgery. Objectives: The purpose of this study was to investigate survival and toxicity in resected pancreas cancer patients after neoadjuvant ablative SMART. Methods: In this IRB approved analysis, we retrospectively reviewed 33 consecutive patients with resectable, BR, and LA pancreatic cancer based on NCCN 2.2021 staging criteria who were treated at 2 institutions from 2017-2020 with neoadjuvant SMART 50 Gy in 5 fractions on a 0.35T MR Linac and later underwent definitive surgical resection. Overall survival (OS) and locoregional control (LRC) were evaluated by Kaplan-Meier method. Results: Median follow up was 22.4 months from diagnosis and 17.8 months from last day of RT. Most had BR (55%), otherwise initially resectable (33%) or LA (12%) pancreatic cancer. Median duration of induction chemotherapy was 3.5 (SD 1.6) months with most common regimens being FOLFIRINOX (74%), gemcitabine/abraxane (24%) and FOLFOX (3%). Performance status was ECOG 0, 1, 2 in 16 (48.5%), 12 (36.4%), and 5 (15.2%), respectively. Whipple was performed in 27 (82%) of patients, distal pancreatectomy in 4 (12%), and total pancreatectomy in 2 (6%). The median duration from SMART completion to surgery was 6.9 weeks (4.7-44.1). R0 resections were achieved in 28 (84.8%) of patients with the rest being R1, all in BR patients. Vascular resection/reconstruction was performed of the portal vein (PV) in 8 (24.2%) patients, SMV in 4 (12%), SMA in 1 (3%), and common hepatic artery in 2 (6%). Vascular resection/reconstruction was performed in all LA patients. Median OS, 1-year OS, and 2-year OS from diagnosis were 29.6 months, 93.8%, 81.5%, respectively. Median OS from RT was not yet reached; 1-year OS was 90.9%. LRC at 1 and 2 years was 97% and 93%, respectively. Radiation related acute and late grade 3+ gastrointestinal toxicity was seen in 2 (6%) and 2 (6%) patients. Post-op mortality at 30 and 90 days was seen 2 (6%) and 3 (9%) of patients with 1 death from GI bleed attributed to surgery and 1 death from hepatic ischemia related to PV resection. Conclusions: To the best of our knowledge, this is the first report suggesting that surgery for pancreas cancer after dose escalated 5-fraction SMART is feasible. Further clarification is needed with respect to ideal patient selection and timing for surgery, the safety of arterial versus venous resection/reconstruction, and histopathologic response after delivery of ablative versus non-ablative radiation dose

Outcomes of MR-guided Stereotactic Body Radiotherapy (SBRT) or yttrium-90 Transarterial Radioembolization for Hepatocellular Carcinoma Treated at an Urban Liver Transplant Center

Background: There are overlapping indications for both stereotactic body radiotherapy (SBRT) and yttrium-90 (Y90) trans-arterial radioembolization as locoregional treatments for hepatocellular cancer, though most centers preferentially use one modality over the other. MR-guided radiation allows both effective on-table localization and integrated motion management as compared with many traditional linear accelerators, allowing SBRT to be done more easily. Y90 radioembolization has been a well-established modality to deliver highly conformal dose due to the localization of the microspheres to the vascular supply of a tumor. We looked at patient characteristics and treatment outcomes for patients receiving MR-guided SBRT or Y90 at an urban transplant center. Objectives: To compare patient characteristics and treatment outcomes of MR-guided SBRT with Y90 transarterial radioembolization in a liver transplant center. Methods: This retrospective single-institution study analyzed patients with HCC treated with SBRT or Y90 from August 2017 to September 2020. To select a patient population eligible for either treatment modality, any Y90 procedures for lesions \u3e 10 cm or for treatment volumes \u3e 1000 cc were omitted from the cohort. A total of 239 patients were included in the analysis, receiving a total of 98 courses of SBRT and 187 courses of Y90 treatment. Local control (LC), freedom from liver progression (FFLP), and overall survival (OS) rates were measured from treatment completion date to death date or last follow-up. All outcomes were censored at time of loss to follow-up; LC and FFLP were censored at time of liver transplant if applicable. Cox regression models were used for survival, with significant factors on the univariate analysis further analyzed with a multivariate model. Results: Median time to follow-up was 11 months (0-44 mo). The mean size of lesions treated with SBRT were smaller than those treated with Y90 (2.7 cm vs 4.3 cm, P\u3c0.01). The groups of patients differed in liver disease characteristics, with SBRT patients having fewer Child-Pugh A disease (62% vs 80%, P\u3c0.01), more having received locoregional treatments to the liver in the past (81% v 35%, P\u3c0.01), and more disease in previously treated liver (57% vs 25%, P\u3c0.01). Dose of radiation for SBRT was 45-50 Gy administered in 5 fractions; dose of Y90 radiation to tumor was prescribed to a median of 235.2 Gy (range 55.8-512.3 Gy). There was a higher rate of one year LC in the SBRT cohort (77% vs 57%, P\u3c0.01), while median FFLP (9 mo vs 8 mo, P=NS) and median OS were not significantly different (24 mo vs 21 mo, P=NS). Multivariate analysis revealed size of largest lesion (P\u3c0.01) was correlated with decreased local control; a 1 cm increase in tumor size was associated with a 25% increased risk of local failure. Subsequent transplant (P\u3c0.01) was the remaining significant factor. Treatment modality did not remain an independent predictor of LC. Predictors of OS in multivariate analysis included age (P=0.01), prior liver treatments (HR 2.86, P\u3c0.01), size of largest lesion (P\u3c0.01), Child-Pugh stage (P\u3c0.01), portal vein thrombosis (HR 1.6, P=0.04), and subsequent liver transplant (HR 0.08, P\u3c0.01). Conclusions: These findings support the effectiveness of both MR-guided SBRT and Y90 transarterial radioembolization in locoregional management of HCC at a single institution despite clear differences in the patient cohorts. Though survival outcomes were comparable, local control differences favored the cohort treated by SBRT, in large part due to differences in tumor size. This data supports further investigation in a randomized study between SBRT and Y90

Stereotactic MRI-guided Adaptive Radiation Therapy for Non-metastatic Pancreatic Cancer; Outcomes and Toxicity Analysis for Patients Treated in an Underserved Urban Center

Background: Stereotactic MRI-guided Adaptive Radiation Therapy (SMART) is an emerging technology for treatment of pancreatic cancer patients. Initial results show favorable survival and toxicity. However, data is still sparse overall, and especially in underserved patient populations. The purpose of this study is to review SMART outcomes at our underserved urban academic cancer. Objectives: Stereotactic MRI-guided Adaptive Radiation Therapy (SMART) is an emerging technology for treatment of pancreatic cancer patients. Initial results show favorable survival and toxicity. However, data is still sparse overall, and especially in underserved patient populations. The purpose of this study is to review SMART outcomes at our underserved urban academic cancer. Methods: In this IRB approved retrospective chart review we reviewed 98 patients with non-metastatic pancreatic cancer, who completed SMART between November 2018-January 2021. All 98 patients were treated with 50 Gy in 5 daily fractions with adaptive technique as deemed appropriate by treating radiation oncologist. The primary endpoints were overall survival (OS), progression free survival (PFS), and both acute and late grade 3+ GI toxicity. OS, PFS, locoregional control and distant control were estimated by Kaplan-Meier method and compared using log-rank test. The effect of clinical features on OS was assessed using univariate and multivariate Cox proportional hazard models. OS and PFS were calculated from completion of radiation. Grade 3+ GI toxicity probably or definitively related to radiation was recorded. All incidences of GI bleeding, regardless of attribution, were also recorded. Results: Median follow up was 20.9 months from time of diagnosis and 14 months from radiation. 21 (21%) patients were borderline resectable, 42 (43%) locally advanced, 22 (22%) medically inoperable and 13 (13%) resectable. Neoadjuvant chemotherapy was given to 86 (88%) patients with a median of 3.5 months of chemotherapy (range 1-12), leaving 11 (12%) patients who did not have systemic chemotherapy. Median overall survival from radiation for the whole group was 15.7 months, and 1-year OS was 58%. There was a statistically significant worsening of overall survival from diagnosis between ECOG 2+ and ECOG 0/1 patients (HR 1.94, 1.05-3.57). 27 (27%) patients went on to have surgical resection with 23 (82%) having R0 resection, and 3 (11%) have an R1 resection. Improved OS was seen in patients with surgical resection (HR 0.06, 0.02-0.23). Acute grade 3+ GI toxicity from radiation was seen in 4 (4%) patients and late toxicity from radiation was seen in 6 (6%) patients. GI bleeding was seen in 16(16%) patients, 10 (62%) of which were on anticoagulation at the time of GI bleed and 5 (19%) of which had surgery. Portal vein complications occurred with 7 (7%) having portal vein thrombosis and 6 (6%) portal vein stenosis. Conclusions: SMART showed durable responses in pancreatic cancer patients with an acceptable toxicity profile. Attention needs to be paid to the moderate incident of GI bleeding, however further work is necessary to determine if bleeding was due to radiation, surgery, or disease progression. Surgical resection as well as performance status of ECOG 0-1 were associated with improved overall survival. Further follow up will be necessary to determine further durability of treatment response and long-term survival in these patients

Surgery After Neoadjuvant Stereotactic MRI Guided Adaptive Radiation in Pancreatic Cancer: Multi-institutional Toxicity and Survival Outcomes

Background: Favorable toxicity and survival outcomes after dose escalated stereotactic MR guided adaptive radiation therapy (SMART) have been recently published for locally advanced (LA) and borderline resectable (BR) pancreatic cancer. Perioperative morbidity and mortality are not well understood after ablative radiation therapy, which may temper enthusiasm for offering surgery. Objectives: The purpose of this study was to investigate survival and toxicity in resected pancreas cancer patients after neoadjuvant ablative SMART. Methods: In this IRB approved analysis, we retrospectively reviewed 33 consecutive patients with resectable, BR, and LA pancreatic cancer based on NCCN 2.2021 staging criteria who were treated at 2 institutions from 2017-2020 with neoadjuvant SMART 50 Gy in 5 fractions on a 0.35T MR Linac and later underwent definitive surgical resection. Overall survival (OS) and locoregional control (LRC) were evaluated by Kaplan-Meier method. Results: Median follow up was 22.4 months from diagnosis and 17.8 months from last day of RT. Most had BR (55%), otherwise initially resectable (33%) or LA (12%) pancreatic cancer. Median duration of induction chemotherapy was 3.5 (SD 1.6) months with most common regimens being FOLFIRINOX (74%), gemcitabine/abraxane (24%) and FOLFOX (3%). Performance status was ECOG 0, 1, 2 in 16 (48.5%), 12 (36.4%), and 5 (15.2%), respectively. Whipple was performed in 27 (82%) of patients, distal pancreatectomy in 4 (12%), and total pancreatectomy in 2 (6%). The median duration from SMART completion to surgery was 6.9 weeks (4.7-44.1). R0 resections were achieved in 28 (84.8%) of patients with the rest being R1, all in BR patients. Vascular resection/reconstruction was performed of the portal vein (PV) in 8 (24.2%) patients, SMV in 4 (12%), SMA in 1 (3%), and common hepatic artery in 2 (6%). Vascular resection/reconstruction was performed in all LA patients. Median OS, 1-year OS, and 2-year OS from diagnosis were 29.6 months, 93.8%, 81.5%, respectively. Median OS from RT was not yet reached; 1-year OS was 90.9%. LRC at 1 and 2 years was 97% and 93%, respectively. Radiation related acute and late grade 3+ gastrointestinal toxicity was seen in 2 (6%) and 2 (6%) patients. Post-op mortality at 30 and 90 days was seen 2 (6%) and 3 (9%) of patients with 1 death from GI bleed attributed to surgery and 1 death from hepatic ischemia related to PV resection. Conclusions: To the best of our knowledge, this is the first report suggesting that surgery for pancreas cancer after dose escalated 5-fraction SMART is feasible. Further clarification is needed with respect to ideal patient selection and timing for surgery, the safety of arterial versus venous resection/reconstruction, and histopathologic response after delivery of ablative versus non-ablative radiation dose

The Influence of Dosimetric Parameters on Quality of Life for Early Stage Non-small Cell Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy

Background: Lung stereotactic body radiotherapy (SBRT) has become a standard treatment option for early stage non-small cell lung cancer (NSCLC) patients who are medically inoperable. The influence of radiation dose/volume parameters on quality of life is not known. Our hypothesis is that clinically meaningful declines in quality of life over time will be associated with increased radiation lung dose/volume parameters. Objectives: To investigate clinical toxicity and quality of life (QOL) outcomes of stage I NSCLC patients after SBRT as a function of radiation dose/volume parameters. Methods: In this IRB-approved study, 55 stage I NSCLC patients who received SBRT (12 Gy x 4) and completed QOL forms were analyzed. Clinical symptoms and QOL were measured at baseline and at 3, 6, 12, 18, 24, and 36 months post-SBRT. Clinical toxicity was graded using the common terminology criteria for adverse effects (CTCAE v4.0). Quality of life was followed using the validated Functional Assessment of Cancer Therapy-Trial Outcome Index (FACT-TOI) instrument. Dosimetric parameters, including the mean lung radiation dose (MLD), and the volume of normal lung receiving \u3e 5, 10, 13 or 20 Gy (V5, V10, V13, and V20) were measured from the radiation treatment plan. Student\u27s t-test and Pearson correlation analyses were used to examine the relationships between radiation lung metrics and clinically meaningful changes in QOL and/or clinical toxicities. Kaplan-Meier method was used to estimate rates of local control (LC), disease free survival (DFS), and overall survival (OS). Results: With a median follow-up of 24 months, the 3 year LC, DFS, and OS were 93%, 65% and 84%, respectively, with 5.5% grade 3 toxicity and no grade 4 or 5 toxicities. Clinically meaningful declines in patient reported QOL (FACT-TOI, lung cancer subscale, physical well-being, and/or functional well-being) post-treatment significantly correlated with increased dosimetric parameters, such as V10, V13, and V20. Conclusions: While lung SBRT is associated with excellent LC and minimal clinical toxicity for early stage NSCLC, clinically meaningful declines in QOL significantly correlated with increasing lung dose/volume parameters. This suggests that further improvements in the techniques of lung SBRT have the potential to further enhance patients\u27 QOL following this treatment

Racial Differences in Treatments and Toxicity in Non-Small Cell Lung Cancer Patients Treated with Thoracic Radiation Therapy

Background: Racial disparities are of particular concern for lung cancer patients given historical differences in surgery rates for African-American lung cancer patients that resulted in lower overall survival and higher recurrence rates compared with rates in White patients. Objectives: The overall objective of this study was to examine racial differences in thoracic radiation therapy (RT) treatments and toxicities in a large cohort of patients from a multi-institutional consortium database of non-small cell lung cancer (NSCLC) patients. Methods: A large multi-institutional statewide prospectively collected patient-level database of locally advanced (stage II or III) NSCLC patients who received thoracic RT from March 2012 to November 2019 was analyzed to assess the associations between race and treatment and toxicity variables. Race (White or African-American) was defined by patient self-report or if not available then by the electronic medical record system classification. Race categories other than White or African-American comprised a small minority of patients and were excluded from this analysis. Patient-reported toxicity was determined by validated tools including the Functional Assessment of Cancer Therapy-Lung (FACT-L) quality of life instrument. Provider-reported toxicity was determined by the Common Terminology Criteria for Adverse Events (CTCAE) version 4.0. Uni-variable and multi-variable regression models were then fitted to assess relationships between primary outcomes by race and indicators of high-quality treatment and secondary analysis of symptoms. Spearman rank correlation coefficients were calculated between provider reported toxicity and similar patient reported outcomes for each race category. Results: A total of 1441 patients from 24 institutions with mean age of 68 years (range 38-94) were evaluated; 226 patients were African-American, of whom 61% were treated at three facilities. Race was not significantly associated with RT treatment approach, use of concurrent chemotherapy, or the dose to the planning target volume (PTV) or organs at risk including the heart and lungs. However, there was increased patient-reported general pain in African-American patients (compared with White patients) at several time points including pre-RT (22% (vs 15%), P=0.02) and at the end of RT (30% (vs 17%), P=0.001). African-American patients were significantly less likely to have provider-reported grade 2+ radiation pneumonitis (odds ratio (OR) 0.36, P=0.03), despite similar levels of patient-reported respiratory toxicities such as cough and shortness of breath and even after controlling for known patient and treatment-related factors. Correlation coefficients between provider- and patient-reported toxicities were generally similar across race categories. Conclusions: In this large multi-institutional observational study, we reassuringly found no evidence of differences in radiation treatment or chemotherapy approaches by race, in contrast to historical differences by race in surgical care that led to worse survival and outcomes in minority race patients. However, we did unexpectedly find that African-American race was associated with lower odds of provider-reported grade 2+ radiation pneumonitis despite similar patient-reported toxicities of shortness of breath and cough. There are several possibilities for this finding including that pneumonitis is a multifactorial diagnosis that relies on clinical as well as radiologic information and clinical information alone may be insufficient. The Spearman correlation analysis also revealed stronger correlations between patient- and provider-reported toxicities in White patients compared with African-American patients, particularly for trouble swallowing/esophagitis. These findings together for pneumonitis and esophagitis discouragingly suggest possible under-recognition of symptoms in black patients. Further investigation is now warranted to better understand how these findings impact the care of racially diverse lung cancer patients