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

Chiloiro, G.; Cusumano, D.; Franco, P. De; Lenkowicz, Jacopo; Boldrini, Luca; Carano, Davide; Barbaro, Brunella; Corvari, Barbara; Dinapoli, N.; Giraffa, Martina; Meldolesi, Elisa; Manfredi, Riccardo; Valentini, Vincenzo; Gambacorta, Maria Antonietta

doi:10.1007/s11547-021-01421-0

Cited by 35 publications

(21 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, as studies on radionomic analysis to improve the prediction of pCR have recently been reported, further imaging methods may help select high-risk patients. 20 21 22 …”

Section: Discussionmentioning

confidence: 99%

Benefits of Adjuvant Chemotherapy for Clinical T3-4N0 Rectal Cancer After Preoperative Chemoradiotherapy

et al. 2023

View full text Add to dashboard Cite

While the guidelines for adjuvant chemotherapy (AC) for colon cancer are relatively standardized, those for early rectal cancer are still lacking. We therefore evaluated the role of AC in clinical stage II rectal cancer treatment after preoperative chemoradiotherapy (CRT). Patients diagnosed with early rectal cancer (defined by clinical stage T3/4, N0) who completed CRT followed by surgery were enrolled in this retrospective study. To evaluate the role of AC, we analyzed the risk of recurrence and survival based on clinicopathologic parameters and adjuvant chemotherapy. Of the 112 patients, 11 patients (9.8%) experienced recurrence and five patients (4.8%) died. In a multivariate analysis, circumferential resection margin involvement (CRM+) on magnetic resonance imaging at diagnosis, CRM involvement following neoadjuvant therapy (ypCRM+), tumor regression grade (≤G1) and no-AC were considered poor prognostic factors for recurrence free survival (RFS). In addition, ypCRM+ and no-AC were associated with poor overall survival (OS) in the multivariate analysis. AC including 5-FU monotherapy demonstrated the benefits of reduced recurrence and prolonged survival in clinical stage II rectal cancer, even in pathologic stage following neoadjuvant therapy (ypStage) 0-I. Further prospective studies are needed to verify the benefit of each regimen of AC and the development of a method that can accurately predict CRM status before surgery, and a vigorous treatment that can induce CRM non-involvement (CRM-) should be considered even in early stages of rectal cancer.

show abstract

“…In addition, as studies on radionomic analysis to improve the prediction of pCR have recently been reported, further imaging methods may help select high-risk patients. 20 21 22 …”

Section: Discussionmentioning

confidence: 99%

Benefits of Adjuvant Chemotherapy for Clinical T3-4N0 Rectal Cancer After Preoperative Chemoradiotherapy

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Beyond familial pancreatic cancer, the most well-recognized risk factor for pancreatic tumor is smoking, followed by chronic pancreatitis, diabetes, and obesity, specifically high body-mass index (BMI) and centralized fat distribution [105][106][107][108][109][110][111][112][113][114].…”

Section: Risk Factorsmentioning

confidence: 99%

“…In addition, another subgroup of familial pancreatic tumor is due to germline mutations in ATM [94][95][96][97][98][99][100][101][102][103][104]. Beyond familial pancreatic cancer, the most well-recognized risk factor for pancreatic tumor is smoking, followed by chronic pancreatitis, diabetes, and obesity, specifically high body-mass index (BMI) and centralized fat distribution [105][106][107][108][109][110][111][112][113][114].…”

Section: Risk Factorsmentioning

confidence: 99%

Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence

Granata

Fusco

Setola

et al. 2023

Cancers

View full text Add to dashboard Cite

Pancreatic cancer (PC) is one of the deadliest cancers, and it is responsible for a number of deaths almost equal to its incidence. The high mortality rate is correlated with several explanations; the main one is the late disease stage at which the majority of patients are diagnosed. Since surgical resection has been recognised as the only curative treatment, a PC diagnosis at the initial stage is believed the main tool to improve survival. Therefore, patient stratification according to familial and genetic risk and the creation of screening protocol by using minimally invasive diagnostic tools would be appropriate. Pancreatic cystic neoplasms (PCNs) are subsets of lesions which deserve special management to avoid overtreatment. The current PC screening programs are based on the annual employment of magnetic resonance imaging with cholangiopancreatography sequences (MR/MRCP) and/or endoscopic ultrasonography (EUS). For patients unfit for MRI, computed tomography (CT) could be proposed, although CT results in lower detection rates, compared to MRI, for small lesions. The actual major limit is the incapacity to detect and characterize the pancreatic intraepithelial neoplasia (PanIN) by EUS and MR/MRCP. The possibility of utilizing artificial intelligence models to evaluate higher-risk patients could favour the diagnosis of these entities, although more data are needed to support the real utility of these applications in the field of screening. For these motives, it would be appropriate to realize screening programs in research settings.

show abstract

“…Several works in the last few decades suggest the feasibility of a wait-and-see approach in patients with very high surgical risk or trans-anal rectal excision approach if a significant response to CRT is assessed [ 1 , 10 , 12 , 13 ]. In this regard, magnetic Resonance Imaging (MRI) seems to be helpful to provide morphological and functional pieces of information that can be used to predict prognosis in pre-treatment patients [ 14 , 15 , 16 , 17 , 18 , 19 ], but its value in the pre- and post-CRT response assessment is still debated [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

“…This innovative analysis is currently investigated in several fields and requires a computer quantification of both gray-level intensity and the position of pixels [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 ]. Several authors are investigating a possible application in the monitoring and research of biomarkers in cancer patients, including those with LARC [ 27 , 50 , 51 , 52 ]. In this context, Antunes et al accurately described, in a retrospective multisite study on radiomic features of rectal cancer for Neoadjuvant C-RT response, how a limited number of four radiomic features extracted from T2w MRI scans allows one to achieve good performance for predicting pCR using Laws and CoLIAgE operators to quantify fluctuations in local image heterogeneity.…”

Section: Introductionmentioning

confidence: 99%

Ability of Delta Radiomics to Predict a Complete Pathological Response in Patients with Loco-Regional Rectal Cancer Addressed to Neoadjuvant Chemo-Radiation and Surgery

Nardone

Reginelli

Grassi

et al. 2022

Cancers

View full text Add to dashboard Cite

We performed a pilot study to evaluate the use of MRI delta texture analysis (D-TA) as a methodological item able to predict the frequency of complete pathological responses and, consequently, the outcome of patients with locally advanced rectal cancer addressed to neoadjuvant chemoradiotherapy (C-RT) and subsequently, to radical surgery. In particular, we carried out a retrospective analysis including 100 patients with locally advanced rectal adenocarcinoma who received C-RT and then radical surgery in three different oncological institutions between January 2013 and December 2019. Our experimental design was focused on the evaluation of the gross tumor volume (GTV) at baseline and after C-RT by means of MRI, which was contoured on T2, DWI, and ADC sequences. Multiple texture parameters were extracted by using a LifeX Software, while D-TA was calculated as percentage of variations in the two time points. Both univariate and multivariate analysis (logistic regression) were, therefore, carried out in order to correlate the above-mentioned TA parameters with the frequency of pathological responses in the examined patients’ population focusing on the detection of complete pathological response (pCR, with no viable cancer cells: TRG 1) as main statistical endpoint. ROC curves were performed on three different datasets considering that on the 21 patients, only 21% achieved an actual pCR. In our training dataset series, pCR frequency significantly correlated with ADC GLCM-Entropy only, when univariate and binary logistic analysis were performed (AUC for pCR was 0.87). A confirmative binary logistic regression analysis was then repeated in the two remaining validation datasets (AUC for pCR was 0.92 and 0.88, respectively). Overall, these results support the hypothesis that D-TA may have a significant predictive value in detecting the occurrence of pCR in our patient series. If confirmed in prospective and multicenter trials, these results may have a critical role in the selection of patients with locally advanced rectal cancer who may benefit form radical surgery after neoadjuvant chemoradiotherapy.

show abstract

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

Cited by 35 publications

References 52 publications

Benefits of Adjuvant Chemotherapy for Clinical T3-4N0 Rectal Cancer After Preoperative Chemoradiotherapy

Benefits of Adjuvant Chemotherapy for Clinical T3-4N0 Rectal Cancer After Preoperative Chemoradiotherapy

Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence

Ability of Delta Radiomics to Predict a Complete Pathological Response in Patients with Loco-Regional Rectal Cancer Addressed to Neoadjuvant Chemo-Radiation and Surgery

Contact Info

Product

Resources

About