Is multidisciplinary management possible in the treatment of lung cancer? A report from three Italian meetings

Challenges and controversies in resectable non-small cell lung cancer: a clinician's perspective

The treatment landscape of resectable early-stage non-small cell lung cancer (NSCLC) is transforming due to the approval of novel adjuvant and neoadjuvant systemic treatments. The European Medicines Agency (EMA) recently approved adjuvant osimertinib, adjuvant atezolizumab, adjuvant pembrolizumab, and neoadjuvant nivolumab combined with chemotherapy, and the approval of other agents or new indications may follow soon. Despite encouraging results, many unaddressed questions remain. Moreover, the transformed treatment paradigm in resectable NSCLC can pose major challenges to healthcare systems and magnify existing disparities in care as differences in reimbursement may vary across different European countries. This Viewpoint discusses the challenges and controversies in resectable early-stage NSCLC and how existing inequalities in access to these treatments could be addressed.

Smile InTM Totems in Radiotherapy: Patients’ Satisfaction with Limited Equipment and COVID-19

Background: We report a mono-institutional experience regarding patient-perceived quality regarding the Chieti Radiotherapy Department, through RAMSI (Radiotherapy Amica Mia—SmileINTM(SI)—My Friend RadiotherapySI) project, in critical scenarios of limited equipment and COVID-19. Material and methods: Patient-reported experience measures (PREMs) were assessed as follows: Patient-centric welcome perception (PCWP), Comfort, Professional skills and Punctuality. Patients could give anonymous feedback using HappyOrNot technology through four totems located in strategic areas within the center. An internal benchmark was obtained using the feedback received after a preliminary observation period. The SI Experience Index was collected, analyzed and compared. Weekly and monthly reports were generated. Results: From February 2019 to February 2022, 8924 patients accessed the department; 17,464 daily treatments were recorded and 5830 points of feedback were collected: 896, 1267, 1125 and 2542 for PCWP, Comfort, Professional skills and Punctuality, respectively. A LINAC decommissioning period was analyzed, with decreases in the SI-Index score and Smile-IN approved percentage and an improvement after this period. Additionally, the COVID-19 pandemic was analyzed with a mild evaluations decrease for PREM’s Welcome, Comfort and Punctuality (Δ-value: −9%, −3% and −4%, respectively), while Professional skills were always optimal. Conclusion: The RAMSI project was effective for assessing treatment quality perception, allowing for improving clinical procedures with corrective actions. The RAMSI project is ongoing.

Diffusion weighted imaging and diffusion kurtosis imaging in abdominal oncological setting: why and when

This article provides an overview of diffusion kurtosis (DKI) imaging in abdominal oncology. DKI allows for more data on tissue structures than the conventional diffusion model (DWI). However, DKI requires high quality images at b-values greater than 1000 s/mm² and high signal-to-noise ratio (SNR) that traditionally MRI systems are not able to acquire and therefore there are generally amplified anatomical distortions on the images due to less homogeneity of the field. Advances in both hardware and software on modern MRI scanners have currently enabled ultra-high b-value imaging and offered the ability to apply DKI to multiple extracranial sites. Previous studies have evaluated the ability of DKI to characterize and discriminate tumor grade compared to conventional DWI. Additionally, in several studies the DKI sequences used were based on planar echo (EPI) acquisition, which is susceptible to motion, metal and air artefacts and prone to low SNRs and distortions, leading to low quality images for some small lesions, which may affect the accuracy of the results. Another problem is the optimal b-value of DKI, which remains to be explored and not yet standardized, as well as the manual selection of the ROI, which could affect the accuracy of some parameters.

Unmet needs in the management of unresectable stage III non-small cell lung cancer: a review after the 'Radio Talk' webinars

INTRODUCTION

Stage III non-small cell lung cancer (NSCLC) is a variable entity, encompassing bulky primary tumors, nodal involvement or both. Multidisciplinary evaluation is essential to discuss multiple treatment options, to outline optimal management and to examine the main debated topics and critical issues not addressed by current trials and guidelines that influence daily clinical practice.

AREAS COVERED

From March to May 2021, 5 meetings were scheduled in a webinar format titled 'Radio Talk' due to the COVID-19 pandemic; the faculty was composed of 6 radiation oncologists from 6 different Institutions of Italy, all of them were the referring radiation oncologist for lung cancer treatment at their respective departments and were or had been members of AIRO (Italian Association of Radiation Oncology) Thoracic Oncology Study Group. The topics covered included: pulmonary toxicity, cardiac toxicity, radiotherapy dose, fractionation and volumes, unfit/elderly patients, multidisciplinary management.

EXPERT OPINION

The debate was focused on the unmet needs triggered by case reports, personal experiences and questions; the answers were often not univocal, however, the exchange of opinion and the contribution of different centers confirmed the role of multidisciplinary management and the necessity that the most critical issues should be investigated in clinical trials.

Lung Cancer Imaging: Screening Result and Nodule Management

Background: Lung cancer (LC) represents the main cause of cancer-related deaths worldwide, especially because the majority of patients present with an advanced stage of the disease at the time of diagnosis. This systematic review describes the evidence behind screening results and the current guidelines available to manage lung nodules. Methods: This review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The following electronic databases were searched: PubMed, EMBASE, and the Web of Science. Results: Five studies were included in the systematic review. The study cohort included 46,364 patients, and, in this case series, LC was detected in 9028 patients. Among the patients with detected LC, 1261 died of lung cancer, 3153 died of other types of cancers and 4614 died of other causes. Conclusions: This systematic review validates the use of CT in LC screening follow-ups, and bids for future integration and implementation of nodule management protocols to improve LC screening, avoid missed cancers and to reduce the number of unnecessary investigations.

Computed tomography-based radiomic model predicts radiological response following stereotactic body radiation therapy in early-stage non-small-cell lung cancer and pulmonary oligo-metastases

Purpose

Radiomic models elaborate geometric and texture features of tumors extracted from imaging to develop predictors for clinical outcomes. Stereotactic body radiation therapy (SBRT) has been increasingly applied in the ablative treatment of thoracic tumors. This study aims to identify predictors of treatment responses in patients affected by early stage non-small cell lung cancer (NSCLC) or pulmonary oligo-metastases treated with SBRT and to develop an accurate machine learning model to predict radiological response to SBRT.

Materials and Methods

Computed tomography (CT) images of 85 tumors (stage I–II NSCLC and pulmonary oligo-metastases) from 69 patients treated with SBRT were analyzed. Gross tumor volumes (GTV) were contoured on CT images. Patients that achieved complete response (CR) or partial response (PR) were defined as responders. One hundred ten radiomic features were extracted using PyRadiomics module based on the GTV. The association of features with response to SBRT was evaluated. A model using support vector machine (SVM) was then trained to predict response based solely on the extracted radiomics features. Receiver operating characteristic curves were constructed to evaluate model performance of the identified radiomic predictors.

Results

Sixty-nine patients receiving thoracic SBRT from 2008 to 2018 were retrospectively enrolled. Skewness and root mean squared were identified as radiomic predictors of response to SBRT. The SVM machine learning model developed had an accuracy of 74.8%. The area under curves for CR, PR, and non-responder prediction were 0.86 (95% confidence interval [CI], 0.794–0.921), 0.946 (95% CI, 0.873–0.978), and 0.857 (95% CI, 0.789–0.915), respectively.

Conclusion

Radiomic analysis of pre-treatment CT scan is a promising tool that can predict tumor response to SBRT.

Structured Reporting of Lung Cancer Staging: A Consensus Proposal

Background: Structured reporting (SR) in radiology is becoming necessary and has recently been recognized by major scientific societies. This study aimed to build CT-based structured reports for lung cancer during the staging phase, in order to improve communication between radiologists, members of the multidisciplinary team and patients. Materials and Methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi exercise was used to build the structural report and to assess the level of agreement for all the report sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to perform a quality analysis according to the average inter-item correlation. Results: The final SR version was built by including 16 items in the “Patient Clinical Data” section, 4 items in the “Clinical Evaluation” section, 8 items in the “Exam Technique” section, 22 items in the “Report” section, and 5 items in the “Conclusion” section. Overall, 55 items were included in the final version of the SR. The overall mean of the scores of the experts and the sum of scores for the structured report were 4.5 (range 1–5) and 631 (mean value 67.54, STD 7.53), respectively, in the first round. The items of the structured report with higher accordance in the first round were primary lesion features, lymph nodes, metastasis and conclusions. The overall mean of the scores of the experts and the sum of scores for staging in the structured report were 4.7 (range 4–5) and 807 (mean value 70.11, STD 4.81), respectively, in the second round. The Cronbach’s alpha (Cα) correlation coefficient was 0.89 in the first round and 0.92 in the second round for staging in the structured report. Conclusions: The wide implementation of SR is critical for providing referring physicians and patients with the best quality of service, and for providing researchers with the best quality of data in the context of the big data exploitation of the available clinical data. Implementation is complex, requiring mature technology to successfully address pending user-friendliness, organizational and interoperability challenges.

Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment

Simple Summary

This review based on a literature search aims at showing the impact of Texture Analysis in the prediction of response to neoadjuvant radiotherapy and/or chemoradiotherapy. The manuscript explores radiomics approaches in different fields of neoadjuvant radiotherapy, including esophageal cancer, lung cancer, sarcoma and rectal cancer in order to shed a light in the setting of neoadjuvant radiotherapy that can be used to tailor the best subsequent therapeutical strategy.

Abstract

Introduction: Neoadjuvant radiotherapy is currently used mainly in locally advanced rectal cancer and sarcoma and in a subset of non-small cell lung cancer and esophageal cancer, whereas in other diseases it is under investigation. The evaluation of the efficacy of the induction strategy is made possible by performing imaging investigations before and after the neoadjuvant therapy and is usually challenging. In the last decade, texture analysis (TA) has been developed to help the radiologist to quantify and identify the parameters related to tumor heterogeneity, which cannot be appreciated by the naked eye. The aim of this narrative is to review the impact of TA on the prediction of response to neoadjuvant radiotherapy and or chemoradiotherapy. Materials and Methods: Key references were derived from a PubMed query. Hand searching and ClinicalTrials.gov were also used. Results: This paper contains a narrative report and a critical discussion of radiomics approaches in different fields of neoadjuvant radiotherapy, including esophageal cancer, lung cancer, sarcoma, and rectal cancer. Conclusions: Radiomics can shed a light on the setting of neoadjuvant therapies that can be used to tailor subsequent approaches or even to avoid surgery in the future. At the same, these results need to be validated in prospective and multicenter trials.

European Cancer Organisation Essential Requirements for Quality Cancer Care (ERQCC): Lung cancer

European Cancer Organisation Essential Requirements for Quality Cancer Care (ERQCC) are written by experts representing all disciplines involved in cancer care in Europe. They give patients, health professionals, managers and policymakers a guide to essential care throughout the patient journey. Lung cancer is the leading cause of cancer mortality and has a wide variation in treatment and outcomes in Europe. It is a major healthcare burden and has complex diagnosis and treatment challenges. Care must only be carried out in lung cancer units or centres that have a core multidisciplinary team (MDT) and an extended team of health professionals detailed here. Such units are far from universal in European countries. To meet European aspirations for comprehensive cancer control, healthcare organisations must consider the requirements in this paper, paying particular attention to multidisciplinarity and patient-centred pathways from diagnosis, to treatment, to survivorship.

Preoperative staging of the mediastinum is an essential and multidisciplinary task

Mediastinal staging is a crucial step in the management of patients with NSCLC. With the recent development of novel techniques, mediastinal staging has evolved from an activity of interest mainly for thoracic surgeons to a joint effort carried out by many specialists. In this regard, the debate of cases in MDT sessions is crucial for optimal management of patients. Current evidence-based clinical guidelines for preoperative NSCLC staging recommend that mediastinal staging should be performed with increasing invasiveness. Image-based techniques are the first approach, although they have limited accuracy and findings must be confirmed by pathology in almost all cases. In this setting, the advent of radiomics is promising. Invasive staging depends on procedural factors rather than diagnostic performance. The choice between endoscopy-based or surgical procedures should depend on the local expertise of each centre. As the extension of mediastinal disease in terms of number of involved lymph nodes and nodal stations affects prognosis and the choice of treatment, systematic samplings are preferred over random targeted samplings. Following this approach, a diagnosis of single mediastinal nodal involvement can be unreliable if all reachable mediastinal nodal stations have not been assessed. The performance of confirmatory mediastinoscopy after a negative endoscopy-based procedure is controversial but currently recommended. Current indications of invasive staging in patients with radiologically normal mediastinum have to be re-evaluated, especially for central tumour location.