The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights.

Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking.

Early treatment of type II SMA slows rate of progression of scoliosis.

BACKGROUND: Type II spinal muscular atrophy (SMA) often leads to scoliosis in up to 90% of cases. While pharmacological treatments have shown improvements in motor function, their impact on scoliosis progression remains unclear. This study aims to evaluate potential differences in scoliosis progression between treated and untreated SMA II patients. METHODS: Treatment effect on Cobb's angle annual changes and on reaching a 50° Cobb angle was analysed in treated and untreated type II SMA patients with a minimum 1.5-year follow-up. A sliding cut-off approach identified the optimal treatment subpopulation based on age, Cobb angle and Hammersmith Functional Motor Scale Expanded at the initial visit. Mann-Whitney U-test assessed statistical significance. RESULTS: There were no significant differences in baseline characteristics between the untreated (n=46) and treated (n=39) populations. The mean Cobb angle variation did not significantly differ between the two groups (p=0.4). Optimal cut-off values for a better outcome were found to be having a Cobb angle <26° or an age <4.5 years. When using optimal cut-off, the treated group showed a lower mean Cobb variation compared with the untreated group (5.61 (SD 4.72) degrees/year vs 10.05 (SD 6.38) degrees/year; p=0.01). Cox-regression analysis indicated a protective treatment effect in reaching a 50° Cobb angle, significant in patients <4.5 years old (p=0.016). CONCLUSION: This study highlights that pharmacological treatment, if initiated early, may slow down the progression of scoliosis in type II SMA patients. Larger studies are warranted to further investigate the effectiveness of individual pharmacological treatment on scoliosis progression in this patient population.

A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model.

BACKGROUND: The 30-day hospital re-admission rate is a quality measure of hospital care to monitor the efficiency of the healthcare system. The hospital re-admission of acute stroke (AS) patients is often associated with higher mortality rates, greater levels of disability and increased healthcare costs. The aim of our study was to identify predictors of unplanned 30-day hospital re-admissions after discharge of AS patients and define an early re-admission risk score (RRS). METHODS: This observational, retrospective study was performed on AS patients who were discharged between 2014 and 2019. Early re-admission predictors were identified by machine learning models. The performances of these models were assessed by receiver operating characteristic curve analysis. RESULTS: Of 7599 patients with AS, 3699 patients met the inclusion criteria, and 304 patients (8.22%) were re-admitted within 30 days from discharge. After identifying the predictors of early re-admission by logistic regression analysis, RRS was obtained and consisted of seven variables: hemoglobin level, atrial fibrillation, brain hemorrhage, discharge home, chronic obstructive pulmonary disease, one and more than one hospitalization in the previous year. The cohort of patients was then stratified into three risk categories: low (RRS = 0-1), medium (RRS = 2-3) and high (RRS >3) with re-admission rates of 5%, 8% and 14%, respectively. CONCLUSIONS: The identification of risk factors for early re-admission after AS and the elaboration of a score to stratify at discharge time the risk of re-admission can provide a tool for clinicians to plan a personalized follow-up and contain healthcare costs.

Radiomics-enhanced early regression index for predicting treatment response in rectal cancer: a multi-institutional 0.35 T MRI-guided radiotherapy study.

PURPOSE: The accurate prediction of treatment response in locally advanced rectal cancer (LARC) patients undergoing MRI-guided radiotherapy (MRIgRT) is essential for optimising treatment strategies. This multi-institutional study aimed to investigate the potential of radiomics in enhancing the predictive power of a known radiobiological parameter (Early Regression Index, ERITCP) to evaluate treatment response in LARC patients treated with MRIgRT. METHODS: Patients from three international sites were included and divided into training and validation sets. 0.35 T T2*/T1-weighted MR images were acquired during simulation and at each treatment fraction. The biologically effective dose (BED) conversion was used to account for different radiotherapy schemes: gross tumour volume was delineated on the MR images corresponding to specific BED levels and radiomic features were then extracted. Multiple logistic regression models were calculated, combining ERITCP with other radiomic features. The predictive performance of the different models was evaluated on both training and validation sets by calculating the receiver operating characteristic (ROC) curves. RESULTS: A total of 91 patients was enrolled: 58 were used as training, 33 as validation. Overall, pCR was observed in 25 cases. The model showing the highest performance was obtained combining ERITCP at BED = 26 Gy with a radiomic feature (10th percentile of grey level histogram, 10GLH) calculated at BED = 40 Gy. The area under ROC curve (AUC) of this combined model was 0.98 for training set and 0.92 for validation set, significantly higher (p = 0.04) than the AUC value obtained using ERITCP alone (0.94 in training and 0.89 in validation set). CONCLUSION: The integration of the radiomic analysis with ERITCP improves the pCR prediction in LARC patients, offering more precise predictive models to further personalise 0.35 T MRIgRT treatments of LARC patients.

Delphi Initiative for Early-Onset Colorectal Cancer (DIRECt) International Management Guidelines.

BACKGROUND & AIMS: Patients with early-onset colorectal cancer (eoCRC) are managed according to guidelines that are not age-specific. A multidisciplinary international group (DIRECt), composed of 69 experts, was convened to develop the first evidence-based consensus recommendations for eoCRC. METHODS: After reviewing the published literature, a Delphi methodology was used to draft and respond to clinically relevant questions. Each statement underwent 3 rounds of voting and reached a consensus level of agreement of ≥80%. RESULTS: The DIRECt group produced 31 statements in 7 areas of interest: diagnosis, risk factors, genetics, pathology-oncology, endoscopy, therapy, and supportive care. There was strong consensus that all individuals younger than 50 should undergo CRC risk stratification and prompt symptom assessment. All newly diagnosed eoCRC patients should receive germline genetic testing, ideally before surgery. On the basis of current evidence, endoscopic, surgical, and oncologic treatment of eoCRC should not differ from later-onset CRC, except for individuals with pathogenic or likely pathogenic germline variants. The evidence on chemotherapy is not sufficient to recommend changes to established therapeutic protocols. Fertility preservation and sexual health are important to address in eoCRC survivors. The DIRECt group highlighted areas with knowledge gaps that should be prioritized in future research efforts, including age at first screening for the general population, use of fecal immunochemical tests, chemotherapy, endoscopic therapy, and post-treatment surveillance for eoCRC patients. CONCLUSIONS: The DIRECt group produced the first consensus recommendations on eoCRC. All statements should be considered together with the accompanying comments and literature reviews. We highlighted areas where research should be prioritized. These guidelines represent a useful tool for clinicians caring for patients with eoCRC.

Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study.

BACKGROUND: The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients. METHODS: The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive models for lung cancer diagnosis and histological characterization; (ii) to set up personalized predictive models for individual-specific treatments; iii) to enable feedback data loops for preventive healthcare strategies and quality of life management. DISCUSSION: The LANTERN project will develop a predictive platform based on integration of multi-omics data. This will enhance the generation of important and valuable information assets, in order to identify new biomarkers that can be used for early detection, improved tumor diagnosis and personalization of treatment protocols. ETHICS COMMITTEE APPROVAL NUMBER: 5420 - 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS - Università Cattolica del Sacro Cuore Ethics Committee. TRIAL REGISTRATION: clinicaltrial.gov - NCT05802771.

The Italian version of the Pediatric Quality of Life Inventory™ (PEDSQL™) 3.0 healthcare satisfaction hematology/oncology module: reliability and validity in radiation oncology.

BACKGROUND: Health-related quality of life (HRQOL) measurement has become an important health care outcome even in oncological pediatric scenario. During radiation therapy care path, pediatric patients and their relatives may suffer from emotional and psychosocial distress not only related to cancer diagnosis, but also due to the procedure and the required daily routine. Despite the high prevalence of psychosocial consequences in this setting, instruments that inquire pediatric HRQOL and healthcare satisfaction have rarely been studied in Italy. Purpose of this study was to investigate reliability and linguistic validation of the PedsQL™ healthcare satisfaction Hematology/Oncology module from its original English version to Italian language. METHODS: Three phases standard procedure of cross-culture adaptation were used to create Italian version of PedsQL™ healthcare satisfaction Hematology/Oncology module. Forward translations and backward translations were performed. Finally, a pilot-testing for understandability of the 'pre-final' version was conducted with parents of children attending our Radiotherapy Center using two methodologies of Cognitive Interviewing ("Think-aloud Interviews" and "Respondent Debriefing"), in order to obtain the final Italian version of the PedsQL™ healthcare satisfaction Hematology/Oncology module. RESULTS: Twenty-five parents (2 father, 23 mothers) were recruited during their children's radiotherapy treatment and the grammatically and conceptually acceptable pre-final version of the PedsQL™ Healthcare Satisfaction Hematology/Oncology Module was administered. The questionnaire was well understood reflecting its linguistic adaptation. Compliance with questionnaire administration was optimal. All subjects stated that the questions were interesting to express their opinion, most of them reported that all the questions of each section were clearly comprehensible and easy to understand, suggesting minimal changes that were double-checked with back translation. Furthermore, six of them spontaneously asked to complete the questionnaire in order to review the assistance received during radiotherapy. CONCLUSION: Our Italian version of the PedsQL™ 3.0 Healthcare Satisfaction Hematology/Oncology Module seems to be a valid and functional instrument to indagate Healthcare Satisfaction.

Human papillomavirus independent status on pathologic response and outcomes in locally advanced cervical cancer managed with chemoradiotherapy followed by surgery.

OBJECTIVE: While human papillomavirus (HPV) has been shown to play a significant role in cervical cancer carcinogenesis (HPV associated cases), a considerable percentage of cervical cancers occur independently of HPV status (HPV independent). METHODS: In this retrospective study of 254 locally advanced cervical cancer patients treated with chemoradiotherapy and radical surgery, HPV genotypes were determined using the Anyplex II HPV28 kit that uses multiplex, real time polymerase chain reaction technology. The primary endpoints of this study were to evaluate the complete response to chemoradiotherapy (pathologic complete response), the presence of microscopic (<3 mm, pathologic micro partial response, group 1) and macroscopic (>3 mm, pathologic macro partial response, group 2) residual carcinoma in the cervix, and the persistence of metastatic lymph nodes (group 3) in HPV independent cervical cancers. Secondary endpoints were evaluation of disease-free survival and overall survival. RESULTS: Of 254 patients studied, 21 cases (8.3%) of cervical cancer were determined to be HPV independent. The percentage of pathologic complete response was found to be higher in the HPV associated group compared with the HPV independent group (p<0.001). In the HPV associated cervical cancer group, 5 year disease free survival was found to be 80.8% versus 59.9% in the HPV independent group (p=0.014). Overall survival was also higher in the HPV associated group (87.9%) compared with the HPV independent patients (69.4%) (p=0.023). In the multivariate analysis, the International Federation of Gynecology and Obstetrics (FIGO) stage and HPV genotypes maintained their relevant impact on pathologic complete response to chemoradiotherapy: FIGO stages IIIC1 and IIIC2 were associated with a 13-fold increased risk for the presence of metastatic lymph nodes compared with group 1 (p<0.001). HPV independent cervical cancers showed the highest risk for the development of macroscopic/stable disease (p=0.007), and persistence of metastatic lymph nodes (p=0.004) versus group 1, respectively. CONCLUSIONS: This study showed that HPV status at diagnosis could be a relevant factor for clinical outcomes in locally advanced cervical cancer patients.

Clinical Impact of Pathologic Residual Tumor in Locally Advanced Cervical Cancer Patients Managed by Chemoradiotherapy Followed by Radical Surgery: A Large, Multicenter, Retrospective Study.

BACKGROUND: Exclusive chemoradiation (E-CT/RT) represents the standard of treatment for locally advanced cervical cancer (LACC). Chemoradiation (CT/RT) followed by radical surgery (RS) may play a role for patients with a suboptimal response to CT/RT or in low-income countries with limited access to radiotherapy. Histologic assessment of residual tumor after CT/RT and RS allows accurate definition of prognostic categories. METHODS: Data on patients with FIGO stages 1B2 to 4A cervical cancer managed by CT/RT and RS from June 1996 to March 2020 were retrospectively analyzed. Pathologic response on the cervix was defined as complete (pCR), microscopic (persistent tumor foci ≤ 3 mm) (pmicroR), or macroscopic (persistent tumor foci > 3 mm) (pmacroR). Lymph node (LN) residual tumor was classified as absent or present. RESULTS: The 701 patients in this study underwent CT/RT and RS. Of the 701 patients, 293 (41.8%) had pCR, 188 (26.8%) had pmicroR, and 220 (31.4%) had pMacroR. Residual tumor was found in the pelvic lymph nodes of 66 (9.4%) patients and the aortic lymph nodes of 29 (4.1%) patients. The 5-year DFS and OS were respectively 86.6% and 92.5% in the pCR cases, 80.3% and 89.1% in the pmicroR cases, and 56.2% and 68.8% in the pmacroR cases. Among the patients with lymph node residual tumor, the 5-year DFS and OS were respectively 16.7% and 40% in the pCR cases, 35.4% and 53.3% in the pmicroR cases, and 31.7% and 31.1% in the pmacroR cases. Cervical residual tumor,, positive pelvic LNs, and positive aortic LNs were associated with worse DFS and OS in both the uni- and multivariate analyses. CONCLUSIONS: Persistence of pathologic residual tumor on the cervix and LNs after CT/RT are reliable predictors of survival for LACC patients undergoing CT/RT and adjuvant surgery.

Automated hybrid volumetric modulated arc therapy (HVMAT) for whole-breast irradiation with simultaneous integrated boost to lumpectomy area : A treatment planning study.

PURPOSE: To develop an automated treatment planning approach for whole breast irradiation with simultaneous integrated boost using an automated hybrid VMAT class solution (HVMAT). MATERIALS AND METHODS: Twenty-five consecutive patients with left breast cancer received 50 Gy (2 Gy/fraction) to the whole breast and an additional simultaneous 10 Gy (2.4 Gy/fraction) to the tumor cavity. Ipsilateral lung, heart, and contralateral breast were contoured as main organs-at-risk. HVMAT plans were inversely optimized by combining two open fields with a VMAT semi-arc beam. Open fields were setup to include the whole breast with a 2 cm flash region and to carry 80% of beams weight. HVMAT plans were compared with three tangential techniques: conventional wedged-field tangential plans (SWF), field-in-field forward planned tangential plans (FiF), and hybrid-IMRT plans (HMRT). Dosimetric differences among the plans were evaluated using Kruskal-Wallis one-way analysis of variance. Dose accuracy was validated using the PTW Octavius-4D phantom together with the 1500 2D-array. RESULTS: No significant differences were found among the four techniques for both targets coverage. HVMAT plans showed consistently better PTVs dose contrast, conformity, and homogeneity (p < 0.001 for all metrics) and statistically significant reduction of high-dose breast irradiation. V55 and V60 decreased by 30.4, 26.1, and 20.8% (p < 0.05) and 12.3, 9.9, and 6.0% (p < 0.05) for SWF, FIF, and HMRT, respectively. Pretreatment dose verification reported a gamma pass-rate greater than the acceptance threshold of 95% for all HVMAT plans. In addition, HVMAT reduced the time for full planning optimization to about 20 min. CONCLUSIONS: HVMAT plans resulted in superior target dose conformity and homogeneity compared to other tangential techniques. Due to fast planning time HVMAT can be applied for all patients, minimizing the impact on human or departmental resources.

THUNDER 2: THeragnostic Utilities for Neoplastic DisEases of the Rectum by MRI guided radiotherapy.

BACKGROUND: Neoadjuvant chemoradiation therapy (nCRT) is the standard treatment modality in locally advanced rectal cancer (LARC). Since response to radiotherapy (RT) is dose dependent in rectal cancer, dose escalation may lead to higher complete response rates. The possibility to predict patients who will achieve complete response (CR) is fundamental. Recently, an early tumour regression index (ERI) was introduced to predict pathological CR (pCR) after nCRT in LARC patients. The primary endpoints will be the increase of CR rate and the evaluation of feasibility of delta radiomics-based predictive MRI guided Radiotherapy (MRgRT) model. METHODS: Patients affected by LARC cT2-3, N0-2 or cT4 for anal sphincter involvement N0-2a, M0 without high risk features will be enrolled in the trial. Neoadjuvant CRT will be administered using MRgRT. The initial RT treatment will consist in delivering 55 Gy in 25 fractions on Gross Tumor Volume (GTV) plus the corresponding mesorectum and 45 Gy in 25 fractions on the drainage nodes. Chemotherapy with 5-fluoracil (5-FU) or oral capecitabine will be administered continuously. A 0.35 Tesla MRI will be acquired at simulation and every day during MRgRT. At fraction 10, ERI will be calculated: if ERI will be inferior than 13.1, the patient will continue the original treatment; if ERI will be higher than 13.1 the treatment plan will be reoptimized, intensifying the dose to the residual tumor at the 11th fraction to reach 60.1 Gy. At the end of nCRT instrumental examinations are to be performed in order to restage patients. In case of stable disease or progression, the patient will undergo surgery. In case of major or complete clinical response, conservative approaches may be chosen. Patients will be followed up to evaluate toxicity and quality of life. The number of cases to be enrolled will be 63: all the patients will be treated at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome. DISCUSSION: This clinical trial investigates the impact of RT dose escalation in poor responder LARC patients identified using ERI, with the aim of increasing the probability of CR and consequently an organ preservation benefit in this group of patients. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04815694 (25/03/2021).

Current controversies in TNM for the radiological staging of rectal cancer and how to deal with them: results of a global online survey and multidisciplinary expert consensus.

OBJECTIVES: To identify the main problem areas in the applicability of the current TNM staging system (8th ed.) for the radiological staging and reporting of rectal cancer and provide practice recommendations on how to handle them. METHODS: A global case-based online survey was conducted including 41 image-based rectal cancer cases focusing on various items included in the TNM system. Cases reaching < 80% agreement among survey respondents were identified as problem areas and discussed among an international expert panel, including 5 radiologists, 6 colorectal surgeons, 4 radiation oncologists, and 3 pathologists. RESULTS: Three hundred twenty-one respondents (from 32 countries) completed the survey. Sixteen problem areas were identified, related to cT staging in low-rectal cancers, definitions for cT4b and cM1a disease, definitions for mesorectal fascia (MRF) involvement, evaluation of lymph nodes versus tumor deposits, and staging of lateral lymph nodes. The expert panel recommended strategies on how to handle these, including advice on cT-stage categorization in case of involvement of different layers of the anal canal, specifications on which structures to include in the definition of cT4b disease, how to define MRF involvement by the primary tumor and other tumor-bearing structures, how to differentiate and report lymph nodes and tumor deposits on MRI, and how to anatomically localize and stage lateral lymph nodes. CONCLUSIONS: The recommendations derived from this global survey and expert panel discussion may serve as a practice guide and support tool for radiologists (and other clinicians) involved in the staging of rectal cancer and may contribute to improved consistency in radiological staging and reporting. KEY POINTS: • Via a case-based online survey (incl. 321 respondents from 32 countries), we identified 16 problem areas related to the applicability of the TNM staging system for the radiological staging and reporting of rectal cancer. • A multidisciplinary panel of experts recommended strategies on how to handle these problem areas, including advice on cT-stage categorization in case of involvement of different layers of the anal canal, specifications on which structures to include in the definition of cT4b disease, how to define mesorectal fascia involvement by the primary tumor and other tumor-bearing structures, how to differentiate and report lymph nodes and tumor deposits on MRI, and how to anatomically localize and stage lateral lymph nodes. • These recommendations may serve as a practice guide and support tool for radiologists (and other clinicians) involved in the staging of rectal cancer and may contribute to improved consistency in radiological staging and reporting.

Transanal Endoscopic Microsurgery Versus Total Mesorectal Excision in ypT0-1 Rectal Cancer After Preoperative Radiochemotherapy: Postoperative Morbidity, Functional Results, and Long-term Oncologic Outcome.

BACKGROUND: In patients with locally advanced extraperitoneal rectal cancer, a multidisciplinary approach represents the standard treatment. However, considering the favorable prognosis in patients with major or complete response, radical surgery might represent overtreatment. OBJECTIVE: This study aimed to evaluate postoperative short-term morbidity, functional outcome, and oncologic long-term outcome in patients with rectal cancer treated with local excision by transanal endoscopic microsurgery or radical surgery and to determine who achieved a complete or major pathological response (ypT0-1) after neoadjuvant treatment. DESIGN: This was a retrospective study. SETTING: The study was conducted at a single center. PATIENTS: Patients who had received neoadjuvant treatment by local excision with a major or complete pathological response at histological examination (transanal endoscopic microsurgery group) were compared to patients treated by radical surgery with the same pathological response (total mesorectal excision group). INTERVENTIONS: The interventions included local excision by transanal endoscopic microsurgery and radical surgery with total mesorectal excision. MAIN OUTCOME MEASURES: Postoperative short-term morbidity, functional outcome 1 year after surgery, and oncologic long-term outcome were measured. RESULTS: Ninety-three patients were included in the study (35 in the transanal endoscopic microsurgery group and 58 in the mesorectal excision group). In the total mesorectal excision group, a sphincter-saving approach was possible in 89.7% (vs 100%; p = 0.049); a protective temporary stoma was necessary in 74.1% of radical procedures (vs 0%; p < 0.001), and 13.8% of these became permanent. Short-term postoperative morbidity was lower after local excision (14.3% vs 46.6%; p = 0.002). One year after surgery, the transanal endoscopic microsurgery group recorded better evacuation and continence function than the total mesorectal excision group. Oncologic outcome was similar between the groups. LIMITATIONS: This study had a retrospective design. CONCLUSION: If a major or complete pathological response occurs after neoadjuvant treatment, an organ-sparing approach by local excision seems to offer the same oncologic results as radical surgery, but it has a better postoperative morbidity rate and better functional results. See Video Abstract at http://links.lww.com/DCR/B901 .Microcirugía endoscópica transanal versus escisión total del mesorrecto en cáncer de recto ypT0-1 después de radioquimioterapia preoperatoria: morbilidad posoperatoria, resultados funcionales y resultado oncológico a largo plazo. ANTECEDENTES: En pacientes con cáncer rectal extraperitoneal localmente avanzado, un abordaje multidisciplinario con radioquimioterapia preoperatoria y cirugía con escisión total del mesorrecto representa el tratamiento estándar. En pacientes que obtienen una respuesta mayor o completa, la cirugía radical puede representar un sobretratamiento, considerando el pronóstico favorable de estos casos. OBJETIVO: Evaluar la morbilidad posoperatoria a corto plazo, el resultado funcional y el resultado oncológico a largo plazo en pacientes con cáncer de recto tratados con escisión local mediante microcirugía endoscópica transanal o mediante cirugía radical y que obtuvieron una respuesta patológica completa o mayor (ypT0-1) después del tratamiento neoadyuvante. DISEO: Este fue un estudio retrospectivo. AJUSTE: El estudio se realizó en un solo centro. ESCENARIO: El estudio se realizó en un solo centro. PACIENTES: Se comparó a los pacientes tratados, tras tratamiento neoadyuvante (1996-2016), mediante escisión local con respuesta patológica mayor o completa al examen histológico (grupo de microcirugía endoscópica transanal), con los pacientes tratados mediante cirugía radical con la misma respuesta patológica (grupo de escisión mesorrectal total). INTERVENCIONES: Extirpación local mediante microcirugía endoscópica transanal y cirugía radical con escisión mesorrectal total. PRINCIPALES MEDIDAS DE RESULTADO: Morbilidad posoperatoria a corto plazo, resultado funcional a un año después de la cirugía (evaluado con una puntuación de evacuación y continencia) y resultado oncológico a largo plazo. LIMITACIONES: Las limitaciones de este estudio incluyen su diseño retrospectivo. CONCLUSIN: Si se produce una respuesta patológica mayor o completa después del tratamiento neoadyuvante, un abordaje con preservación de órganos mediante escisión local parece ofrecer los mismos resultados oncológicos que la cirugía radical, pero tiene una menor tasa de morbilidad postoperatoria y mejores resultados funcionales un año después de la cirugía. Consulte Video Resumen en http://links.lww.com/DCR/B901 . (Traducción-Dr. Felipe Bellolio ).

Efficacy and safety of stereotactic body radiotherapy (SBRT) in oligometastatic/persistent/recurrent ovarian cancer: a prospective, multicenter phase II study (MITO-RT3/RAD).

BACKGROUND: Stereotactic body radiotherapy (SBRT) has shown promising results in the clinical setting of oligometastatic, persistent, or recurrent disease in several malignancies including ovarian cancer. PRIMARY OBJECTIVE: The MITO-RT3/RAD trial is a prospective, multicenter phase II study aimed at identifying potential predictors of response and clinical outcome after SBRT treatment. STUDY HYPOTHESIS: Radiotherapy delivered by pre-defined SBRT treatment schedules and shared constraints could improve the rate of complete response. TRIAL DESIGN: All patients accrued will be treated with a radiotherapy dose in the range of 30-50 Gy by 1, 3, or 5 SBRT daily fractions to all sites of active metastatic disease according to diagnostic imaging. Schedules of treatment and dose prescription have been established before considering target sites and healthy organ dose constraints. Follow-up and monitoring of side effects will be carried out every 3 months for the first year with imaging and clinical evalutation, and every 4 months within the second year; thereafter, surveillance will be carried out every 6 months. The best response on a per lesion basis will be evaluated by computed tomographic (CT) scan, positron emission tomography/CT, or magnetic resonance imaging in case of brain lesions, every 3 months. MAJOR INCLUSION/EXCLUSION CRITERIA: The study includes patients with oligometastatic, persistent, or recurrent ovarian cancer for which salvage surgery or other local therapies are not feasible due to any relative contra-indication to further systemic therapy because of serious co-morbidities, previous severe toxicity, unavailability of potentially active systemic therapy, or patient refusal. PRIMARY ENDPOINT: The primary endpoint of the study is the clinical complete response rate to SBRT by imaging on a per lesion basis. SAMPLE SIZE: Approximately 205 lesions will be treated (90 lymph nodes and 115 parenchyma lesions). ESTIMATED DATES FOR COMPLETING ACCRUAL AND PRESENTING RESULTS: Fifty-two centers have expressed their intention to participate. Enrollment should be completed by March 2023 and analysis will be completed in September 2023. TRIAL REGISTRATION: NCT04593381.

Local tuning of radiomics-based model for predicting pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

PURPOSE: This study aims to further enhance a validated radiomics-based model for predicting pathologic complete response (pCR) after chemo­radiotherapy in locally advanced rectal cancer (LARC) for use in clinical practice. METHODS: A generalized linear model (GLM) to predict pCR in LARC patients previously trained in Europe and validated with an external inter-continental cohort (59 patients), was first examined with further 88 intercontinental patient datasets to assess its reproducibility; then new radiomics and clinical features, and validation methods were investigated to build a new model for enhancing the pCR prediction for patients admitted to our department. The patients were divided into training group (75%) and validation group (25%) according to their demographic. The least absolute shrinkage and selection operator (LASSO) logistic regression was used to reduce the dimensionality of the extracted features of the training group and select the optimal ones; the performance of the reference GLM and enhanced models was compared through the area under curve (AUC) of the receiver operating characteristics. RESULTS: The value of AUC of the reference model was 0.831 (95% CI, 0.701-0.961), and 0.828 (95% CI, 0.700-0.956) in the original and new validation cohorts, respectively, showing a reproducibility in the applicability of the GLM model. Eight features were found to be significant with LASSO and used to establish an enhanced model. The AUC of the enhanced model of 0.926 (95% CI, 0.859-0.993) for training, and 0.926 (95% CI, 0.767-1.00) for the validation group shows better performance than the reference model. CONCLUSIONS: The GLM model shows good reproducibility in predicting pCR in LARC; the enhanced model has the potential to improve prediction accuracy and may be a candidate in clinical practice.

Role of Peripheral Blood Markers for Detecting Response and Predicting Prognosis in Patients with Non-small-cell Lung Cancer Undergoing Neoadjuvant Therapy and Surgery.

INTRODUCTION: To date, no validated predictors of response before neoadjuvant therapy (NAD) are currently available in locally advanced non-small-cell lung cancer (NSCLC). In this study, different peripheral blood markers were investigated before NAD (pre-NAD) and after NAD/before surgery (post-NAD) to evaluate their influence on the treatment outcomes. METHODS: Patients affected by locally advanced NSCLC (cT1-T4/N0-2/M0) who underwent NAD followed by surgery from January 1996 to December 2019 were considered for this retrospective analysis. The impact of peripheral blood markers on downstaging post-NAD and on overall survival (OS) was evaluated using multivariate logistic and Cox regression models. Time to event analysis was performed by means of Kaplan-Meier survival curves and Log Rank tests at 5 years from surgery. RESULTS: Two hundred and seventy-two consecutive patients were included. Most of the patients had Stage III NSCLC (83.5%). N2 disease was reported in 188 (69.1%) patients. Surgical resection was performed in patients with stable disease or downstaging post-NAD. Nodal downstaging was observed in 80% of clinical N2 (cN2) patients. The median follow-up of the total series was 74 months (range 6-302). Five-year OS in the overall population and in N2 population was 74.6% and 73.5%, respectively. The pre-surgery platelets level (PLT) (p = 0.019) and the variation (pre-NAD/post-NAD) of the neutrophil/lymphocyte ratio (p = 0.024) were identified as independent prognostic factors of OS. The preoperative PLT value (p value = 0.031) was confirmed as the only predictor of NAD response. CONCLUSIONS: The clinical role of peripheral blood markers in locally advanced NSCLC needs to be further investigated. Based on these preliminary results, these factors may be used as auxiliary markers for the prediction of response to neoadjuvant treatment and as prognostic factors for stratification in multimodal approaches.

Radiomics-based prediction of two-year clinical outcome in locally advanced cervical cancer patients undergoing neoadjuvant chemoradiotherapy.

PURPOSE: The aim of this study is to determine if radiomics features extracted from staging magnetic resonance (MR) images could predict 2-year long-term clinical outcome in patients with locally advanced cervical cancer (LACC) after neoadjuvant chemoradiotherapy (NACRT). MATERIALS AND METHODS: We retrospectively enrolled patients with LACC diagnosis who underwent NACRT followed by radical surgery in two different institutions. Radiomics features were extracted from pre-treatment 1.5 T T2w MR images. The predictive performance of each feature was quantified in terms of Wilcoxon-Mann-Whitney test. Among the significant features, Pearson correlation coefficient (PCC) was calculated to quantify the correlation among the different predictors. A logistic regression model was calculated considering the two most significant features at the univariate analysis showing the lowest PCC value. The predictive performance of the model created was quantified out using the area under the receiver operating characteristic curve (AUC). RESULTS: A total of 175 patients were retrospectively enrolled (142 for the training cohort and 33 for the validation one). 1896 radiomic feature were extracted, 91 of which showed significance (p < 0.05) at the univariate analysis. The radiomic model showing the highest predictive value combined the features calculated starting from the gray level co-occurrence-based features. This model achieved an AUC of 0.73 in the training set and 0.91 in the validation set. CONCLUSIONS: The proposed radiomic model showed promising performances in predicting 2-year overall survival before NACRT. Nevertheless, the observed results should be tested in larger studies with consistent external validation cohorts, to confirm their potential clinical use.

Does restaging MRI radiomics analysis improve pathological complete response prediction in rectal cancer patients? A prognostic model development.

PURPOSE: Our study investigated the contribution that the application of radiomics analysis on post-treatment magnetic resonance imaging can add to the assessments performed by an experienced disease-specific multidisciplinary tumor board (MTB) for the prediction of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). MATERIALS AND METHODS: This analysis included consecutively retrospective LARC patients who obtained a complete or near-complete response after nCRT and/or a pCR after surgery between January 2010 and September 2019. A three-step radiomics features selection was performed and three models were generated: a radiomics model (rRM), a multidisciplinary tumor board model (yMTB) and a combined model (CM). The predictive performance of models was quantified using the receiver operating characteristic (ROC) curve, evaluating the area under curve (AUC). RESULTS: The analysis involved 144 LARC patients; a total of 232 radiomics features were extracted from the MR images acquired post-nCRT. The yMTB, rRM and CM predicted pCR with an AUC of 0.82, 0.73 and 0.84, respectively. ROC comparison was not significant (p = 0.6) between yMTB and CM. CONCLUSION: Radiomics analysis showed good performance in identifying complete responders, which increased when combined with standard clinical evaluation; this increase was not statistically significant but did improve the prediction of clinical response.

CT angiography-based radiomics as a tool for carotid plaque characterization: a pilot study.

PURPOSES: Radiomics is a quantitative method able to analyze a high-throughput extraction of minable imaging features. Herein, we aim to develop a CT angiography-based radiomics analysis and machine learning model for carotid plaques to discriminate vulnerable from no vulnerable plaques. MATERIALS AND METHODS: Thirty consecutive patients with carotid atherosclerosis were enrolled in this pilot study. At surgery, a binary classification of plaques was adopted ("hard" vs "soft"). Feature extraction was performed using the R software package Moddicom. Pairwise feature interdependencies were evaluated using the Spearman rank correlation coefficient. A univariate analysis was performed to assess the association between each feature and the plaque classification and chose top-ranked features. The feature predictive value was investigated using binary logistic regression. A stepwise backward elimination procedure was performed to minimize the Akaike information criterion (AIC). The final significant features were used to build the models for binary classification of carotid plaques, including logistic regression (LR), support vector machine (SVM), and classification and regression tree analysis (CART). All models were cross-validated using fivefold cross validation. Class-specific accuracy, precision, recall and F-measure evaluation metrics were used to quantify classifier output quality. RESULTS: A total of 230 radiomics features were extracted from each plaque. Pairwise Spearman correlation between features reported a high level of correlations, with more than 80% correlating with at least one other feature at |ρ|> 0.8. After a stepwise backward elimination procedure, the entropy and volume features were found to be the most significantly associated with the two plaque groups (p < 0.001), with AUCs of 0.92 and 0.96, respectively. The best performance was registered by the SVM classifier with the RBF kernel, with accuracy, precision, recall and F-score equal to 86.7, 92.9, 81.3 and 86.7%, respectively. The CART classification tree model for the entropy and volume features model achieved 86.7% well-classified plaques and an AUC of 0.987. CONCLUSION: This pilot study highlighted the potential of CTA-based radiomics and machine learning to discriminate plaque composition. This new approach has the potential to provide a reliable method to improve risk stratification in patients with carotid atherosclerosis.

Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer.

BRCA 1/2 genes mutation status can already determine the therapeutic algorithm of high grade serous ovarian cancer patients. Nevertheless, its assessment is not sufficient to identify all patients with genomic instability, since BRCA 1/2 mutations are only the most well-known mechanisms of homologous recombination deficiency (HR-d) pathway, and patients displaying HR-d behave similarly to BRCA mutated patients. HRd assessment can be challenging and is progressively overcoming BRCA testing not only for prognostic information but more importantly for drugs prescriptions. However, HR testing is not already integrated in clinical practice, it is quite expensive and it is not refundable in many countries. Selecting patients who are more likely to benefit from this assessment (BRCA 1/2 WT patients) at an early stage of the diagnostic process, would allow an optimization of genomic profiling resources. In this study, we sought to explore whether somatic BRCA1/2 genes status can be predicted using computational pathology from standard hematoxylin and eosin histology. In detail, we adopted a publicly available, deep-learning-based weakly supervised method that uses attention-based learning to automatically identify sub regions of high diagnostic value to accurately classify the whole slide (CLAM). The same model was also tested for progression free survival (PFS) prediction. The model was tested on a cohort of 664 (training set: n = 464, testing set: n = 132) ovarian cancer patients, of whom 233 (35.1%) had a somatic BRCA 1/2 mutation. An area under the curve of 0.7 and 0.55 was achieved in the training and testing set respectively. The model was then further refined by manually identifying areas of interest in half of the cases. 198 images were used for training (126/72) and 87 images for validation (55/32). The model reached a zero classification error on the training set, but the performance was 0.59 in terms of validation ROC AUC, with a 0.57 validation accuracy. Finally, when applied to predict PFS, the model achieved an AUC of 0.71, with a negative predictive value of 0.69, and a positive predictive value of 0.75. Based on these analyses, we have planned further steps of development such as proving a reference classification performance, exploring the hyperparameters space for training optimization, eventually tweaking the learning algorithms and the neural networks architecture for better suiting this specific task. These actions may allow the model to improve performances for all the considered outcomes.