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Article ; Online: In Reply to Gerard.

Spiegel, Daphna Y / Palta, Manisha

International journal of radiation oncology, biology, physics

2019 Volume 104, Issue 5, Page(s) 1181–1182

MeSH term(s)	Chemoradiotherapy ; Humans ; Rectal Neoplasms ; Veterans Health
Language	English
Publishing date	2019-07-21
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	197614-x
ISSN	1879-355X ; 0360-3016
ISSN (online)	1879-355X
ISSN	0360-3016
DOI	10.1016/j.ijrobp.2019.04.029
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Article ; Online: Stereotactic Body Radiation Therapy for Hepatocellular Carcinoma: Current State and Future Opportunities.

Soni, Payal D / Palta, Manisha

Digestive diseases and sciences

2019 Volume 64, Issue 4, Page(s) 1008–1015

Abstract: Hepatocellular carcinoma is a rising cause of morbidity and mortality in the USA and around the world. Surgical resection and liver transplantation are the preferred management strategies; however, less than 30% of patients are eligible for surgery. ... ...

Abstract	Hepatocellular carcinoma is a rising cause of morbidity and mortality in the USA and around the world. Surgical resection and liver transplantation are the preferred management strategies; however, less than 30% of patients are eligible for surgery. Stereotactic body radiation therapy is a promising local treatment option for non-surgical candidates. Local control rates between 95 and 100% have been reported at 1-2 years post-treatment, and classical radiation-induced liver disease described with conventional radiation is an unlikely complication from stereotactic radiotherapy. Enrollment in randomized trials will be essential in establishing the role of stereotactic radiation in treatment paradigms for hepatocellular carcinoma.
MeSH term(s)	Carcinoma, Hepatocellular/radiotherapy ; Humans ; Liver Neoplasms/radiotherapy ; Radiosurgery
Language	English
Publishing date	2019-03-13
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	304250-9
ISSN	1573-2568 ; 0163-2116
ISSN (online)	1573-2568
ISSN	0163-2116
DOI	10.1007/s10620-019-05539-0
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Article ; Online: The Treatment of Hepatocellular Carcinoma With Portal Vein Tumor Thrombosis.

Qadan, Motaz / Kothary, Nishita / Sangro, Bruno / Palta, Manisha

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting

2020 Volume 40, Page(s) 1–8

Abstract: Hepatocellular carcinoma (HCC) is the sixth most common cancer and third leading cause of cancer-related death worldwide. HCC is also is a tumor with a distinct ability to invade and grow within the hepatic vasculature. Approximately 20% of patients with ...

Abstract	Hepatocellular carcinoma (HCC) is the sixth most common cancer and third leading cause of cancer-related death worldwide. HCC is also is a tumor with a distinct ability to invade and grow within the hepatic vasculature. Approximately 20% of patients with HCC have macrovascular invasion (MVI) at the time of diagnosis. MVI is associated with dismal prognosis, with median survival ranging from 2 to 5 months. Current staging systems designate MVI as advanced disease. Recent advances in multimodal approaches, including systemic therapies, radiation therapy, liver-directed therapies, and surgical approaches, in the treatment of HCC with MVI have rendered this disease process more treatable with improved outcomes and are discussed here.
MeSH term(s)	Carcinoma, Hepatocellular/complications ; Carcinoma, Hepatocellular/therapy ; Female ; Humans ; Liver Neoplasms/complications ; Liver Neoplasms/therapy ; Male ; Portal Vein/abnormalities ; Thrombosis/etiology ; Treatment Outcome
Language	English
Publishing date	2020-03-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	2431126-1
ISSN	1548-8756 ; 1548-8748
ISSN (online)	1548-8756
ISSN	1548-8748
DOI	10.1200/EDBK_280811
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Article ; Online: Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study.

Hong, Julian C / Eclov, Neville C W / Stephens, Sarah J / Mowery, Yvonne M / Palta, Manisha

BMC bioinformatics

2022 Volume 23, Issue Suppl 12, Page(s) 408

Abstract: Background: Artificial intelligence (AI) and machine learning (ML) have resulted in significant enthusiasm for their promise in healthcare. Despite this, prospective randomized controlled trials and successful clinical implementation remain limited. One ...

Abstract	Background: Artificial intelligence (AI) and machine learning (ML) have resulted in significant enthusiasm for their promise in healthcare. Despite this, prospective randomized controlled trials and successful clinical implementation remain limited. One clinical application of ML is mitigation of the increased risk for acute care during outpatient cancer therapy. We previously reported the results of the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) study (NCT04277650), which was a prospective, randomized quality improvement study demonstrating that ML based on electronic health record (EHR) data can direct supplemental clinical evaluations and reduce the rate of acute care during cancer radiotherapy with and without chemotherapy. The objective of this study is to report the workflow and operational challenges encountered during ML implementation on the SHIELD-RT study. Results: Data extraction and manual review steps in the workflow represented significant time commitments for implementation of clinical ML on a prospective, randomized study. Barriers include limited data availability through the standard clinical workflow and commercial products, the need to aggregate data from multiple sources, and logistical challenges from altering the standard clinical workflow to deliver adaptive care. Conclusions: The SHIELD-RT study was an early randomized controlled study which enabled assessment of barriers to clinical ML implementation, specifically those which leverage the EHR. These challenges build on a growing body of literature and may provide lessons for future healthcare ML adoption. Trial registration: NCT04277650. Registered 20 February 2020. Retrospectively registered quality improvement study.
MeSH term(s)	Artificial Intelligence ; Electronic Health Records ; Humans ; Machine Learning ; Neoplasms/radiotherapy ; Prospective Studies ; Randomized Controlled Trials as Topic
Language	English
Publishing date	2022-09-30
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-022-04940-3
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Article ; Online: Advances in the treatment of intrahepatic cholangiocarcinoma: An overview of the current and future therapeutic landscape for clinicians.

Moris, Dimitrios / Palta, Manisha / Kim, Charles / Allen, Peter J / Morse, Michael A / Lidsky, Michael E

CA: a cancer journal for clinicians

2022 Volume 73, Issue 2, Page(s) 198–222

Abstract: Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver tumor and remains a fatal malignancy in the majority of patients. Approximately 20%-30% of patients are eligible for resection, which is considered the only potentially ... ...

Abstract	Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver tumor and remains a fatal malignancy in the majority of patients. Approximately 20%-30% of patients are eligible for resection, which is considered the only potentially curative treatment; and, after resection, a median survival of 53 months has been reported when sequenced with adjuvant capecitabine. For the 70%-80% of patients who present with locally unresectable or distant metastatic disease, systemic therapy may delay progression, but survival remains limited to approximately 1 year. For the past decade, doublet chemotherapy with gemcitabine and cisplatin has been considered the most effective first-line regimen, but results from the recent use of triplet regimens and even immunotherapy may shift the paradigm. More effective treatment strategies, including those that combine systemic therapy with locoregional therapies like radioembolization or hepatic artery infusion, have also been developed. Molecular therapies, including those that target fibroblast growth factor receptor and isocitrate dehydrogenase, have recently received US Food and Drug Administration approval for a defined role as second-line treatment for up to 40% of patients harboring these actionable genomic alterations, and whether they should be considered in the first-line setting is under investigation. Furthermore, as the oncology field seeks to expand indications for immunotherapy, recent data demonstrated that combining durvalumab with standard cytotoxic therapy improved survival in patients with ICC. This review focuses on the current and future strategies for ICC treatment, including a summary of the primary literature for each treatment modality and an algorithm that can be used to drive a personalized and multidisciplinary approach for patients with this challenging malignancy.
MeSH term(s)	Humans ; Cholangiocarcinoma/drug therapy ; Cholangiocarcinoma/genetics ; Cholangiocarcinoma/surgery ; Treatment Outcome ; Antineoplastic Agents/therapeutic use ; Bile Ducts, Intrahepatic/pathology ; Bile Duct Neoplasms/drug therapy ; Bile Duct Neoplasms/genetics
Chemical Substances	Antineoplastic Agents
Language	English
Publishing date	2022-10-19
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	603553-x
ISSN	1542-4863 ; 0007-9235
ISSN (online)	1542-4863
ISSN	0007-9235
DOI	10.3322/caac.21759
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Article ; Online: Healthcare provider evaluation of machine learning-directed care: reactions to deployment on a randomised controlled study.

Hong, Julian C / Patel, Pranalee / Eclov, Neville C W / Stephens, Sarah J / Mowery, Yvonne M / Tenenbaum, Jessica D / Palta, Manisha

BMJ health & care informatics

2023 Volume 30, Issue 1

Abstract: Objectives: Clinical artificial intelligence and machine learning (ML) face barriers related to implementation and trust. There have been few prospective opportunities to evaluate these concerns. System for High Intensity EvaLuation During Radiotherapy ( ...

Abstract	Objectives: Clinical artificial intelligence and machine learning (ML) face barriers related to implementation and trust. There have been few prospective opportunities to evaluate these concerns. System for High Intensity EvaLuation During Radiotherapy (NCT03775265) was a randomised controlled study demonstrating that ML accurately directed clinical evaluations to reduce acute care during cancer radiotherapy. We characterised subsequent perceptions and barriers to implementation. Methods: An anonymous 7-question Likert-type scale survey with optional free text was administered to multidisciplinary staff focused on workflow, agreement with ML and patient experience. Results: 59/71 (83%) responded. 81% disagreed/strongly disagreed their workflow was disrupted. 67% agreed/strongly agreed patients undergoing intervention were high risk. 75% agreed/strongly agreed they would implement the ML approach routinely if the study was positive. Free-text feedback focused on patient education and ML predictions. Conclusions: Randomised data and firsthand experience support positive reception of clinical ML. Providers highlighted future priorities, including patient counselling and workflow optimisation.
MeSH term(s)	Humans ; Artificial Intelligence ; Prospective Studies ; Surveys and Questionnaires ; Health Personnel ; Machine Learning
Language	English
Publishing date	2023-02-10
Publishing country	England
Document type	Randomized Controlled Trial ; Journal Article
ISSN	2632-1009
ISSN (online)	2632-1009
DOI	10.1136/bmjhci-2022-100674
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Article ; Online: Seeing is believing: A roadmap for implementing bolus-tracked multiphasic CT simulation for ablative radiotherapy of abdominal malignancies.

Godfrey, Devon J / Stephens, Sarah Jo / Marin, Daniele / Moravan, Michael J / Salama, Joseph K / Palta, Manisha

Journal of radiosurgery and SBRT

2021 Volume 7, Issue 3, Page(s) 253–255

Language	English
Publishing date	2021-04-23
Publishing country	United States
Document type	Journal Article
ISSN	2156-4647
ISSN (online)	2156-4647
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Article ; Online: Healthcare provider evaluation of machine learning-directed care

Julian C Hong / Sarah J Stephens / Pranalee Patel / Neville C W Eclov / Yvonne M Mowery / Jessica D Tenenbaum / Manisha Palta

BMJ Health & Care Informatics, Vol 30, Iss

reactions to deployment on a randomised controlled study

2023 Volume 1

Abstract: Objectives Clinical artificial intelligence and machine learning (ML) face barriers related to implementation and trust. There have been few prospective opportunities to evaluate these concerns. System for High Intensity EvaLuation During Radiotherapy ( ... ...

Abstract	Objectives Clinical artificial intelligence and machine learning (ML) face barriers related to implementation and trust. There have been few prospective opportunities to evaluate these concerns. System for High Intensity EvaLuation During Radiotherapy (NCT03775265) was a randomised controlled study demonstrating that ML accurately directed clinical evaluations to reduce acute care during cancer radiotherapy. We characterised subsequent perceptions and barriers to implementation.Methods An anonymous 7-question Likert-type scale survey with optional free text was administered to multidisciplinary staff focused on workflow, agreement with ML and patient experience.Results 59/71 (83%) responded. 81% disagreed/strongly disagreed their workflow was disrupted. 67% agreed/strongly agreed patients undergoing intervention were high risk. 75% agreed/strongly agreed they would implement the ML approach routinely if the study was positive. Free-text feedback focused on patient education and ML predictions.Conclusions Randomised data and firsthand experience support positive reception of clinical ML. Providers highlighted future priorities, including patient counselling and workflow optimisation.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	610
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	BMJ Publishing Group
Document type	Article ; Online
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Article ; Online: The Next Chapter in Immunotherapy and Radiation Combination Therapy: Cancer-Specific Perspectives.

Wisdom, Amy J / Barker, Christopher A / Chang, Joe Y / Demaria, Sandra / Formenti, Silvia / Grassberger, Clemens / Gregucci, Fabiana / Hoppe, Bradford S / Kirsch, David G / Marciscano, Ariel E / Mayadev, Jyoti / Mouw, Kent W / Palta, Manisha / Wu, Cheng-Chia / Jabbour, Salma K / Schoenfeld, Jonathan D

International journal of radiation oncology, biology, physics

2024 Volume 118, Issue 5, Page(s) 1404–1421

Abstract: Immunotherapeutic agents have revolutionized cancer treatment over the past decade. However, most patients fail to respond to immunotherapy alone. A growing body of preclinical studies highlights the potential for synergy between radiation therapy and ... ...

Abstract	Immunotherapeutic agents have revolutionized cancer treatment over the past decade. However, most patients fail to respond to immunotherapy alone. A growing body of preclinical studies highlights the potential for synergy between radiation therapy and immunotherapy, but the outcomes of clinical studies have been mixed. This review summarizes the current state of immunotherapy and radiation combination therapy across cancers, highlighting existing challenges and promising areas for future investigation.
MeSH term(s)	Humans ; Neoplasms/radiotherapy ; Neoplasms/drug therapy ; Immunotherapy ; Combined Modality Therapy
Language	English
Publishing date	2024-01-05
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	197614-x
ISSN	1879-355X ; 0360-3016
ISSN (online)	1879-355X
ISSN	0360-3016
DOI	10.1016/j.ijrobp.2023.12.046
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Article ; Online: The Selective Use of Radiation Therapy in Rectal Cancer Patients.

Martella, Andrew / Willett, Christopher / Palta, Manisha / Czito, Brian

Current oncology reports

2018 Volume 20, Issue 6, Page(s) 43

Abstract: Purpose of review: Colorectal cancer has a high global incidence, and standard treatment employs a multimodality approach. In addition to cure, minimizing treatment-related toxicity and improving the therapeutic ratio is a common goal. The following ... ...

Abstract	Purpose of review: Colorectal cancer has a high global incidence, and standard treatment employs a multimodality approach. In addition to cure, minimizing treatment-related toxicity and improving the therapeutic ratio is a common goal. The following article addresses the potential of omitting radiotherapy in select rectal cancer patients. Recent findings: Omission of radiotherapy in rectal cancer is analyzed in the context of historical findings, as well as more recent data describing risk stratification of stage II-III disease, surgical optimization, imaging limitations, improvement in systemic chemotherapeutic agents, and contemporary studies evaluating selective omission of radiotherapy. A subset of rectal cancer patients exists that may be considered low to intermediate risk for locoregional recurrence. With appropriate staging, surgical technique, and possibly improved systemic therapy, it may be feasible to selectively omit radiotherapy in these patients. Current imaging limitations as well as evidence of increased locoregional recurrence following radiotherapy omission lend us to continue supporting the standard treatment of approach of neoadjuvant chemoradiation therapy followed by surgical resection until additional improvements and prospective evidence can support otherwise.
MeSH term(s)	Chemoradiotherapy ; Combined Modality Therapy ; Fluorouracil/therapeutic use ; Humans ; Neoplasm Recurrence, Local/pathology ; Neoplasm Recurrence, Local/radiotherapy ; Neoplasm Staging ; Rectal Neoplasms/drug therapy ; Rectal Neoplasms/pathology ; Rectal Neoplasms/radiotherapy
Chemical Substances	Fluorouracil (U3P01618RT)
Language	English
Publishing date	2018-04-11
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2057359-5
ISSN	1534-6269 ; 1523-3790
ISSN (online)	1534-6269
ISSN	1523-3790
DOI	10.1007/s11912-018-0689-7
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