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Kifjak D, Hochmair M, Sobotka D, Haug AR, Ambros R, Prayer F, Heidinger BH, Roehrich S, Milos RI, Wadsak W, Fuereder T, Krenbek D, Fazekas A, Meilinger M, Mayerhoefer ME, Langs G, Herold C, Prosch H, Beer L. Metabolic tumor volume and sites of organ involvement predict outcome in NSCLC immune-checkpoint inhibitor therapy. Eur J Radiol 2024; 170:111198. [PMID: 37992608 DOI: 10.1016/j.ejrad.2023.111198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 10/13/2023] [Accepted: 11/13/2023] [Indexed: 11/24/2023]
Abstract
PURPOSE The purpose of this study was to assess the ability of pretreatment PET parameters and peripheral blood biomarkers to predict progression-free survival (PFS) and overall survival (OS) in NSCLC patients treated with ICIT. METHODS We prospectively included 87 patients in this study who underwent pre-treatment [18F]-FDG PET/CT. Organ-specific and total metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured using a semiautomatic software. Sites of organ involvement (SOI) were assessed by PET/CT. The log-rank test and Cox-regression analysis were used to assess associations between clinical, laboratory, and imaging parameters with PFS and OS. Time dependent ROC were calculated and model performance was evaluated in terms of its clinical utility. RESULTS MTV increased with the number of SOI and was correlated with neutrophil and lymphocyte cell count (Spearman's rho = 0.27 or 0.32; p =.02 or 0.003; respectively). Even after adjustment for known risk factors, such as PD-1 expression and neutrophil cell count, the MTV and the number of SOI were independent risk factors for progression (per 100 cm3; adjusted hazard ratio [aHR]: 1.13; 95% confidence interval [95%CI]: 1.01-1.28; p =.04; single SOI vs. ≥ 4 SOI: aHR: 2.26, 95%CI: 1.04-4.94; p =.04). MTV and the number of SOI were independent risk factors for overall survival (per 100 cm3 aHR: 1.11, 95%CI: 1.01-1.23; p =.03; single SOI vs. ≥ 4 SOI: aHR: 4.54, 95%CI: 1.64-12.58; p =.04). The combination of MTV and the number of SOI improved the risk stratification for PFS and OS (log-rank test p <.001; C-index: 0.64 and 0.67). CONCLUSION The MTV and the number of SOI are simple imaging markers that provide complementary information to facilitate risk stratification in NSCLC patients scheduled for ICIT.
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Affiliation(s)
- Daria Kifjak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Department of Radiology, UMass Memorial Medical Center and University of Massachusetts Chan Medical School, Worcester, MA, USA; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
| | - Maximilian Hochmair
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alexander R Haug
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Raphael Ambros
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Florian Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Benedikt H Heidinger
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Sebastian Roehrich
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Ruxandra-Iulia Milos
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Wadsak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Biomarker Research in Medicine, CBmed, Graz, Austria
| | - Thorsten Fuereder
- Department of Internal Medicine I & Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Dagmar Krenbek
- Department of Pathology and Bacteriology, Klinik Floridsdorf, Brünner Strasse 68, 1210 Vienna, Austria
| | - Andreas Fazekas
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Michael Meilinger
- Department of Respiratory and Critical Care Medicine, Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria
| | - Marius E Mayerhoefer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Christian Herold
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Helmut Prosch
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria.
| | - Lucian Beer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision, Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
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Kifjak D, Hochmair MJ, Krenbek D, Milos RI, Heidinger BH, Prayer F, Röhrich S, Watzenboeck ML, Oberndorfer F, Klikovits T, Aigner C, Sinn K, Hoda MA, Hoetzenecker K, Haug AR, Prosch H, Beer L. Neoadjuvant immune-checkpoint inhibitors in lung cancer - a primer for radiologists. Eur J Radiol 2023; 161:110732. [PMID: 36804313 DOI: 10.1016/j.ejrad.2023.110732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 02/03/2023] [Indexed: 02/11/2023]
Abstract
The introduction of neoadjuvant immune checkpoint inhibitors plus platinum-based chemotherapy has changed treatment regimens of patient's early-stage lung cancer. This treatment combination induces high rates of complete pathologic response and improves clinical endpoints. Imaging plays a fundamental role in assessment of treatment response, monitoring of (immune-related) adverse events and enables both the surgeon and pathologist optimal treatment and diagnostic workup of the resected tumor samples. Knowledge of the strengths and weaknesses of diagnostic imaging in this setting are essential for radiologists to provide valuable input in multidisciplinary team decisions.
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Affiliation(s)
- Daria Kifjak
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision Imaging, Medical University of Vienna, Vienna, Austria; Department of Radiology, UMass Memorial Medical Center and University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Maximilian J Hochmair
- Karl Landsteiner Institute of Lung Research and Pulmonary Oncology, Klinik Floridsdorf, Vienna, Austria; Department of Respiratory and Critical Care Medicine, Klinik Floridsdorf, Vienna Healthcare Group, Vienna, Austria
| | - Dagmar Krenbek
- Department of Pathology, Klinik Floridsdorf, Vienna Healthcare Group, Vienna, Austria
| | - Ruxandra-Iulia Milos
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision Imaging, Medical University of Vienna, Vienna, Austria
| | - Benedikt H Heidinger
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision Imaging, Medical University of Vienna, Vienna, Austria
| | - Florian Prayer
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision Imaging, Medical University of Vienna, Vienna, Austria
| | - Sebastian Röhrich
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision Imaging, Medical University of Vienna, Vienna, Austria
| | - Martin L Watzenboeck
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision Imaging, Medical University of Vienna, Vienna, Austria
| | | | - Thomas Klikovits
- Department of Thoracic Surgery, Klinik Floridsdorf, Vienna Healthcare Group, Vienna, Austria
| | - Clemens Aigner
- Department of Thoracic Surgery, Klinik Floridsdorf, Vienna Healthcare Group, Vienna, Austria
| | - Katharina Sinn
- Department of Thoracic Surgery, Medical University of Vienna, Vienna, Austria
| | - Mir Alireza Hoda
- Department of Thoracic Surgery, Medical University of Vienna, Vienna, Austria
| | - Konrad Hoetzenecker
- Department of Thoracic Surgery, Medical University of Vienna, Vienna, Austria
| | - Alexander R Haug
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Helmut Prosch
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision Imaging, Medical University of Vienna, Vienna, Austria
| | - Lucian Beer
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Machine Learning Driven Precision Imaging, Medical University of Vienna, Vienna, Austria.
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Milanese G, Mazzaschi G, Ledda RE, Balbi M, Lamorte S, Caminiti C, Colombi D, Tiseo M, Silva M, Sverzellati N. The radiological appearances of lung cancer treated with immunotherapy. Br J Radiol 2023; 96:20210270. [PMID: 36367539 PMCID: PMC10078868 DOI: 10.1259/bjr.20210270] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 09/29/2022] [Accepted: 10/06/2022] [Indexed: 11/13/2022] Open
Abstract
Therapy and prognosis of several solid and hematologic malignancies, including non-small cell lung cancer (NSCLC), have been favourably impacted by the introduction of immune checkpoint inhibitors (ICIs). Their mechanism of action relies on the principle that some cancers can evade immune surveillance by expressing surface inhibitor molecules, known as "immune checkpoints". ICIs aim to conceal tumoural checkpoints on the cell surface and reinvigorate the ability of the host immune system to recognize tumour cells, triggering an antitumoural immune response.In this review, we will focus on the imaging patterns of different responses occurring in patients treated by ICIs. We will also discuss imaging findings of immune-related adverse events (irAEs), along with current and future perspectives of metabolic imaging. Finally, we will explore the role of radiomics in the setting of ICI-treated patients.
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Affiliation(s)
- Gianluca Milanese
- Department of Medicine and Surgery, Unit of Radiological Sciences, University of Parma, Parma, Italy
| | - Giulia Mazzaschi
- Department of Medicine and Surgery, Unit of Medical Oncology, University of Parma, Parma, Italy
| | - Roberta Eufrasia Ledda
- Department of Medicine and Surgery, Unit of Radiological Sciences, University of Parma, Parma, Italy
| | - Maurizio Balbi
- Department of Medicine and Surgery, Unit of Radiological Sciences, University of Parma, Parma, Italy
| | - Sveva Lamorte
- Department of Medicine and Surgery, Unit of Radiological Sciences, University of Parma, Parma, Italy
| | - Caterina Caminiti
- Unit of Research and Innovation, University Hospital of Parma, Parma, Italy
| | - Davide Colombi
- Department of Radiological Functions, Radiology Unit, Guglielmo da Saliceto Hospital, Piacenza, Italy
| | - Marcello Tiseo
- Department of Medicine and Surgery, Unit of Medical Oncology, University of Parma, Parma, Italy
| | - Mario Silva
- Department of Medicine and Surgery, Unit of Radiological Sciences, University of Parma, Parma, Italy
| | - Nicola Sverzellati
- Department of Medicine and Surgery, Unit of Radiological Sciences, University of Parma, Parma, Italy
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When artificial intelligence meets PD-1/PD-L1 inhibitors: Population screening, response prediction and efficacy evaluation. Comput Biol Med 2022; 145:105499. [DOI: 10.1016/j.compbiomed.2022.105499] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/26/2022] [Accepted: 04/03/2022] [Indexed: 02/07/2023]
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Lin Y, Zhu W, Wu B, Lan H. Case Report: Hepatic Sarcoid-Like Reaction Associated With Checkpoint Inhibition in a NSCLC Patient and a Literature Review. Front Oncol 2022; 12:824308. [PMID: 35359368 PMCID: PMC8960956 DOI: 10.3389/fonc.2022.824308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 02/15/2022] [Indexed: 12/24/2022] Open
Abstract
Immune checkpoint inhibitor (ICI) treatment has dramatically revolutionized the landscape of therapeutic approaches in multiple cancers, particularly, non-small-cell lung cancer (NSCLC). With the increasing use of programmed death-1 (PD-1) inhibitors in the clinic, the emerging toxicity profile presents a novel learning curve for clinicians. Here we report the first case of an NSCLC patient displaying sarcoid/granulomatous-like reaction (SLR, also known as GLR) in the liver during an anti-PD-1 therapy which showed efficacious response of complete regression. Also, this is the first report describing the SLR induced by toripalimab, a novel PD-1 inhibitor. Given this kind of hepatic findings can be easily mistaken as metastasis, even resulting in premature use of second-line treatments. In particular, we briefly review the clinical features of all those cases reporting sarcoidosis and SLRs manifested on different organs during anti-PD-(L)1 therapy. We anticipate that these clinical cases would help to alert the attention of clinicians that SLRs, as a rare immune-related adverse event (irAE), is manageable and that histopathological analysis is necessary before interpreting it as disease progression.
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Affiliation(s)
- Yuxin Lin
- Department of Oncology, Hospital of Chinese Medicine of Changxing County, Huzhou, China
| | - Wei Zhu
- Department of Oncology, Hospital of Chinese Medicine of Changxing County, Huzhou, China
| | - Bingchen Wu
- Department of Oncology, Hospital of Chinese Medicine of Changxing County, Huzhou, China
| | - Huiyin Lan
- Department of Thoracic Radiation Oncology, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.,Institute of Cancer and Basic Medicine, Chinese Academy of Sciences, Hangzhou, China
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Gambichler T, Philippou S, Scheel CH, Susok L. Development of thoracic sarcoid reactions associated with complete response to anti-PD-1 therapy in a patient with advanced cutaneous squamous cell carcinoma. J Eur Acad Dermatol Venereol 2021; 36 Suppl 1:35-40. [PMID: 34855255 DOI: 10.1111/jdv.17401] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 04/23/2021] [Indexed: 01/13/2023]
Abstract
In patients with advanced cutaneous squamous cell carcinoma (cSCC), positive efficacy data were reported for anti-PD-1 antibodies. However, anti-PD-1 treatment is associated with a wide range of immune-related adverse events (irAEs). Here, we report on a 78-year-old woman with a huge cSCC on the right cheek spanning from the temporal to the cervical region with evidence for infiltration of the parotid gland, right masseter muscle and right auditory canal. Ultrasound revealed cervical, submandibular and supraclavicular lymph node metastases on patient's right side. On the basis of a medical hardship application, treatment with pembrolizumab was initiated. After two applications, a dramatic regression of the tumour was observed. At this point, the patient was switched to cemiplimab, which, in the meantime, had become available in Germany. After 3 months on cemiplimab, the tumour-related ulcer on the right cheek showed almost complete regression and all previously affected lymph nodes displayed no evidence for malignancy. Thoracic computed tomography (CT) scans revealed enlarged mediastinal and bilateral hilar lymph nodes assessed as primarily reactive. Three months later, however, mediastinal and bilateral hilar lymph nodes further increased in size, accompanied by radiological alterations of the lung parenchyma. Lymph node biopsies revealed sarcoid reactions (SRs) including fibrotic non-caseating epitheloid cell granulomas surrounded by lymphocytes. Since the patient did not display any clinical symptoms, cemiplimab treatment was continued following a 4-week break. Three months later, CT showed significant regression of the described enlarged lymph nodes and parenchymal lung changes. Twenty months after anti-PD-1 treatment, the patient was still in complete remission. In conclusion, we describe, for the first time, the case of a patient with advanced cSCC who developed disseminated thoracic SRs which were associated with dramatic regression of tumour masses. Thus, as with other irAEs, development of SRs might be indicative of an anti-tumour response to anti-PD-1 therapy.
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Affiliation(s)
- T Gambichler
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
| | - S Philippou
- Department of Pathology and Cytology, Augusta Kliniken Bochum Hattingen, Bochum, Germany
| | - C H Scheel
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
| | - L Susok
- Skin Cancer Center, Department of Dermatology, Ruhr-University Bochum, Bochum, Germany
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Reddy R. Imaging diagnosis of bronchogenic carcinoma (the forgotten disease) during times of COVID-19 pandemic: Current and future perspectives. World J Clin Oncol 2021; 12:437-457. [PMID: 34189068 PMCID: PMC8223714 DOI: 10.5306/wjco.v12.i6.437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 04/07/2021] [Accepted: 06/02/2021] [Indexed: 02/06/2023] Open
Abstract
Patients with bronchogenic carcinoma comprise a high-risk group for coronavirus disease 2019 (COVID-19), pneumonia and related complications. Symptoms of COVID-19 related pulmonary syndrome may be similar to deteriorating symptoms encountered during bronchogenic carcinoma progression. These resemblances add further complexity for imaging assessment of bronchogenic carcinoma. Similarities between clinical and imaging findings can pose a major challenge to clinicians in distinguishing COVID-19 super-infection from evolving bronchogenic carcinoma, as the above-mentioned entities require very different therapeutic approaches. However, the goal of bronchogenic carcinoma management during the pandemic is to minimize the risk of exposing patients to COVID-19, whilst still managing all life-threatening events related to bronchogenic carcinoma. The current pandemic has forced all healthcare stakeholders to prioritize per value resources and reorganize therapeutic strategies for timely management of patients with COVID-19 related pulmonary syndrome. Processing of radiographic and computed tomography images by means of artificial intelligence techniques can facilitate triage of patients. Modified and newer therapeutic strategies for patients with bronchogenic carcinoma have been adopted by oncologists around the world for providing uncompromised care within the accepted standards and new guidelines.
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Affiliation(s)
- Ravikanth Reddy
- Department of Radiology, St. John's Hospital, Bengaluru 560034, Karnataka, India
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