Clinical trial NCT06779734: Radiomics of Colorectal Liver Metastases: Identification of New Prognostic Biomarkers.
Official title: Radiomic Features of Tumor and of Liver-Tumor Interface in Patients with Colorectal Liver Metastases. Identification of New Prognostic Biomarkers.
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Liver Metastases from Colorectal Cancer (mCRC)
Keywords: radiomics
computed tomography
liver metastases
Lead sponsor: Istituto Clinico Humanitas
Sponsor class: OTHER
Collaborators: name: AIRC (Italian Association for Cancer Research)
First posted: 2025-01-16
Enrollment: 400
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients who underwent liver resection for colorectal liver metastases at the IRCCS Humanitas Research Centre, Milan, Italy between January 2021 and December 2024.

Brief summary: Background: Liver metastases (CLM) affect about half of patients with colorectal cancer and dictate patients' prognosis. Prediction of prognosis is of paramount importance for patients allocation to the most adequate treatment, but available parameters do not adequately fulfil this role. Tumor pathology and molecular data and liver-tumor interface characteristics showed a major prognostic impact, but they are not included in standard prognostic scores and standard imaging modalities are poorly informative about them. Radiomic analyses demonstrated a very good prediction of pathology data and of patients outcome in several tumor, but their application to CLM remains to explore.

Hypothesis The preoperative identification of CLM and liver-tumor interface characteristics would improve prognosis prediction and patients allocation to treatments. As in other tumors, radiomic analyses could allow a major refinement in prediction of pathology data. Radiomic features per se could have a major association with prognosis.

Aims

The study has the following end-points:

* to assess whether radiomic features of tumor and of liver-tumor interface improve prognosis prediction in CLM patients undergoing liver surgery in comparison with standard prognostic scores.
* to explore if radiomic features are associated with pathology data.
* to explore performances of radiomic features in comparison with standard radiologic criteria to assess tumor response to chemotherapy.
* to merge radiomic and detailed pathology data in a single prognostic score.

Experimental Design The study will combine a retrospective (n=300 patients) and a prospective (n=400) series of patients undergoing liver resection at authors institution. Retrospectively collected patients will represent the training dataset for the prognostic model including standard prognostic factors plus radiomic features, while the first half of the prospective cohort (n=200) will be the validation dataset (minimum follow-up 30 months). For the analysis of association of radiomic features with pathology details and tumor response to chemotherapy, the prospective cohort of patients (n=400, ≈800 CLMs) will be used as training and validation dataset (data about liver-tumor interface cannot be reliably assessed in the retrospective series). Finally, all prospectively collected patients with adequate follow-up will contribute to build a composite prognostic score combining radiomic features and detailed pathology data. Per-patient evaluation will be performed in prognostic analyses; per-lesion evaluation will be performed while evaluating the association between radiomic and pathology data. The LifeX ® software will be used to perform radiomic analyses. The volume of interest (VOI) of the tumor will be tracked. An automatic volume expansion will be applied to the tumor VOI to track the liver-tumor interface (expansion of 5 mm).

Expected Results The present study has the solid expectancy to demonstrate that radiomic features of CLM and of liver-tumor interface have a major prognostic role and a good association with pathology data. We further believe that a prognostic score combining radiomic and pathology data may further optimize prognosis prediction.

Impact On Cancer Our analysis aims to improve CLM prognosis prediction by identifying radiomic features that impact prognosis and predict pathology data, and to propose a combined prognostic model of radiomic and pathology data. These are the basis for a precision medicine based on a preoperative prognostic-driven treatment allocation.


Eligibility criteria: Inclusion Criteria:

* Patients undergoing liver surgery for CLM confirmed at final pathology
* At least 1 CLM with diameter \>10 mm
* Preoperative CT imaging available for radiomic analysis.
* Age \>18 years
* No other malignancies in the previous 5 years
* Interval CT-surgery ≤60 days

Exclusion Criteria:

* Loco-regional treatments of CRLM before liver resection
* Inadequate portal phase of the CT or high-density material artifacts affecting the analysis
* Incomplete clinical data

Primary outcomes:
measure: Prognosis prediction
timeFrame: 2020-2024
measure: Association with pathology data
timeFrame: 2020-2024
measure: Prognostic score
timeFrame: 2020-2024
Secondary outcomes:
measure: Comparison with radiological criteria
timeFrame: 2020-2024
Other outcomes:
Locations:
city: Rozzano
country: Italy
facility: Humanitas Research Hospital
state: Milan
Study officials:
References:
citation: Fiz F, Costa G, Gennaro N, la Bella L, Boichuk A, Sollini M, Politi LS, Balzarini L, Torzilli G, Chiti A, Vigano L. Contrast Administration Impacts CT-Based Radiomics of Colorectal Liver Metastases and Non-Tumoral Liver Parenchyma Revealing the "Radiological" Tumour Microenvironment. Diagnostics (Basel). 2021 Jun 25;11(7):1162. doi: 10.3390/diagnostics11071162.
citation: Costa G, Cavinato L, Masci C, Fiz F, Sollini M, Politi LS, Chiti A, Balzarini L, Aghemo A, di Tommaso L, Ieva F, Torzilli G, Vigano L. Virtual Biopsy for Diagnosis of Chemotherapy-Associated Liver Injuries and Steatohepatitis: A Combined Radiomic and Clinical Model in Patients with Colorectal Liver Metastases. Cancers (Basel). 2021 Jun 20;13(12):3077. doi: 10.3390/cancers13123077.
citation: Vigano L, Jayakody Arachchige VS, Fiz F. Is precision medicine for colorectal liver metastases still a utopia? New perspectives by modern biomarkers, radiomics, and artificial intelligence. World J Gastroenterol. 2022 Feb 14;28(6):608-623. doi: 10.3748/wjg.v28.i6.608.
citation: Costa G, Cavinato L, Fiz F, Sollini M, Chiti A, Torzilli G, Ieva F, Vigano L. Mapping Tumor Heterogeneity via Local Entropy Assessment: Making Biomarkers Visible. J Digit Imaging. 2023 Jun;36(3):1038-1048. doi: 10.1007/s10278-023-00799-9. Epub 2023 Feb 27.
citation: Laino ME, Fiz F, Morandini P, Costa G, Maffia F, Giuffrida M, Pecorella I, Gionso M, Wheeler DR, Cambiaghi M, Saba L, Sollini M, Chiti A, Savevsky V, Torzilli G, Vigano L. A virtual biopsy of liver parenchyma to predict the outcome of liver resection. Updates Surg. 2023 Sep;75(6):1519-1531. doi: 10.1007/s13304-023-01495-7. Epub 2023 Apr 5.
citation: Vigano L, Ammirabile A, Zwanenburg A. Radiomics in liver surgery: defining the path toward clinical application. Updates Surg. 2023 Sep;75(6):1387-1390. doi: 10.1007/s13304-023-01620-6. Epub 2023 Aug 5. No abstract available.
citation: Ammirabile A, Cavinato L, Ferro CAP, Fiz F, Savino MS, Russolillo N, Balbo Mussetto A, Ragaini EM, Lanza E, Akpinar R, Procopio F, Francone M, Terracciano LM, Gallo T, De Rosa G, Ferrero A, Di Tommaso L, Ieva F, Torzilli G, Vigano L. CT-radiomics and pathological tumor response to systemic therapy: A predictive analysis for colorectal liver metastases. Development and internal validation of a clinical-radiomic model. Eur J Surg Oncol. 2025 Mar;51(3):109557. doi: 10.1016/j.ejso.2024.109557. Epub 2024 Dec 16.
citation: Fiz F, Ragaini EM, Sirchia S, Masala C, Vigano S, Francone M, Cavinato L, Lanzarone E, Ammirabile A, Vigano L. Radiomic Gradient in Peritumoural Tissue of Liver Metastases: A Biomarker for Clinical Practice? Analysing Density, Entropy, and Uniformity Variations with Distance from the Tumour. Diagnostics (Basel). 2024 Jul 18;14(14):1552. doi: 10.3390/diagnostics14141552.
citation: Blazer DG 3rd, Kishi Y, Maru DM, Kopetz S, Chun YS, Overman MJ, Fogelman D, Eng C, Chang DZ, Wang H, Zorzi D, Ribero D, Ellis LM, Glover KY, Wolff RA, Curley SA, Abdalla EK, Vauthey JN. Pathologic response to preoperative chemotherapy: a new outcome end point after resection of hepatic colorectal metastases. J Clin Oncol. 2008 Nov 20;26(33):5344-51. doi: 10.1200/JCO.2008.17.5299. Epub 2008 Oct 20.
citation: Torzilli G, Procopio F, Vigano L, Cimino M, Costa G, Del Fabbro D, Donadon M. Hepatic vein management in a parenchyma-sparing policy for resecting colorectal liver metastases at the caval confluence. Surgery. 2018 Feb;163(2):277-284. doi: 10.1016/j.surg.2017.09.003. Epub 2017 Nov 21.
citation: Vigano L, Procopio F, Cimino MM, Donadon M, Gatti A, Costa G, Del Fabbro D, Torzilli G. Is Tumor Detachment from Vascular Structures Equivalent to R0 Resection in Surgery for Colorectal Liver Metastases? An Observational Cohort. Ann Surg Oncol. 2016 Apr;23(4):1352-60. doi: 10.1245/s10434-015-5009-y. Epub 2015 Dec 29.
citation: Vigano L, Darwish SS, Rimassa L, Cimino M, Carnaghi C, Donadon M, Procopio F, Personeni N, Del Fabbro D, Santoro A, Torzilli G. Progression of Colorectal Liver Metastases from the End of Chemotherapy to Resection: A New Contraindication to Surgery? Ann Surg Oncol. 2018 Jun;25(6):1676-1685. doi: 10.1245/s10434-018-6387-8. Epub 2018 Feb 27.
citation: Vigano L, Rubbia-Brandt L, De Rosa G, Majno P, Langella S, Toso C, Mentha G, Capussotti L. Nodular Regenerative Hyperplasia in Patients Undergoing Liver Resection for Colorectal Metastases After Chemotherapy: Risk Factors, Preoperative Assessment and Clinical Impact. Ann Surg Oncol. 2015 Dec;22(13):4149-57. doi: 10.1245/s10434-015-4533-0. Epub 2015 Apr 7.
citation: Sollini M, Cozzi L, Antunovic L, Chiti A, Kirienko M. PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology. Sci Rep. 2017 Mar 23;7(1):358. doi: 10.1038/s41598-017-00426-y.
citation: Kirienko M, Cozzi L, Rossi A, Voulaz E, Antunovic L, Fogliata A, Chiti A, Sollini M. Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions. Eur J Nucl Med Mol Imaging. 2018 Sep;45(10):1649-1660. doi: 10.1007/s00259-018-3987-2. Epub 2018 Apr 6.
citation: Kirienko M, Cozzi L, Antunovic L, Lozza L, Fogliata A, Voulaz E, Rossi A, Chiti A, Sollini M. Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery. Eur J Nucl Med Mol Imaging. 2018 Feb;45(2):207-217. doi: 10.1007/s00259-017-3837-7. Epub 2017 Sep 24.
citation: Cozzi L, Dinapoli N, Fogliata A, Hsu WC, Reggiori G, Lobefalo F, Kirienko M, Sollini M, Franceschini D, Comito T, Franzese C, Scorsetti M, Wang PM. Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy. BMC Cancer. 2017 Dec 6;17(1):829. doi: 10.1186/s12885-017-3847-7.
citation: Chun YS, Vauthey JN, Boonsirikamchai P, Maru DM, Kopetz S, Palavecino M, Curley SA, Abdalla EK, Kaur H, Charnsangavej C, Loyer EM. Association of computed tomography morphologic criteria with pathologic response and survival in patients treated with bevacizumab for colorectal liver metastases. JAMA. 2009 Dec 2;302(21):2338-44. doi: 10.1001/jama.2009.1755.
citation: Donadon M, Hudspeth K, Cimino M, Di Tommaso L, Preti M, Tentorio P, Roncalli M, Mavilio D, Torzilli G. Increased Infiltration of Natural Killer and T Cells in Colorectal Liver Metastases Improves Patient Overall Survival. J Gastrointest Surg. 2017 Aug;21(8):1226-1236. doi: 10.1007/s11605-017-3446-6. Epub 2017 May 23.
citation: Katz SC, Pillarisetty V, Bamboat ZM, Shia J, Hedvat C, Gonen M, Jarnagin W, Fong Y, Blumgart L, D'Angelica M, DeMatteo RP. T cell infiltrate predicts long-term survival following resection of colorectal cancer liver metastases. Ann Surg Oncol. 2009 Sep;16(9):2524-30. doi: 10.1245/s10434-009-0585-3. Epub 2009 Jul 1.
citation: Wagner P, Koch M, Nummer D, Palm S, Galindo L, Autenrieth D, Rahbari N, Schmitz-Winnenthal FH, Schirrmacher V, Buchler MW, Beckhove P, Weitz J. Detection and functional analysis of tumor infiltrating T-lymphocytes (TIL) in liver metastases from colorectal cancer. Ann Surg Oncol. 2008 Aug;15(8):2310-7. doi: 10.1245/s10434-008-9971-5. Epub 2008 Jun 3.
citation: Halama N, Michel S, Kloor M, Zoernig I, Benner A, Spille A, Pommerencke T, von Knebel DM, Folprecht G, Luber B, Feyen N, Martens UM, Beckhove P, Gnjatic S, Schirmacher P, Herpel E, Weitz J, Grabe N, Jaeger D. Localization and density of immune cells in the invasive margin of human colorectal cancer liver metastases are prognostic for response to chemotherapy. Cancer Res. 2011 Sep 1;71(17):5670-7. doi: 10.1158/0008-5472.CAN-11-0268. Epub 2011 Aug 16.
citation: Halama N, Spille A, Lerchl T, Brand K, Herpel E, Welte S, Keim S, Lahrmann B, Klupp F, Kahlert C, Weitz J, Grabe N, Jaeger D, Zoernig I. Hepatic metastases of colorectal cancer are rather homogeneous but differ from primary lesions in terms of immune cell infiltration. Oncoimmunology. 2013 Apr 1;2(4):e24116. doi: 10.4161/onci.24116.
citation: Pages F, Kirilovsky A, Mlecnik B, Asslaber M, Tosolini M, Bindea G, Lagorce C, Wind P, Marliot F, Bruneval P, Zatloukal K, Trajanoski Z, Berger A, Fridman WH, Galon J. In situ cytotoxic and memory T cells predict outcome in patients with early-stage colorectal cancer. J Clin Oncol. 2009 Dec 10;27(35):5944-51. doi: 10.1200/JCO.2008.19.6147. Epub 2009 Oct 26.
citation: Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pages C, Tosolini M, Camus M, Berger A, Wind P, Zinzindohoue F, Bruneval P, Cugnenc PH, Trajanoski Z, Fridman WH, Pages F. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science. 2006 Sep 29;313(5795):1960-4. doi: 10.1126/science.1129139.
citation: Vigano L, Capussotti L, De Rosa G, De Saussure WO, Mentha G, Rubbia-Brandt L. Liver resection for colorectal metastases after chemotherapy: impact of chemotherapy-related liver injuries, pathological tumor response, and micrometastases on long-term survival. Ann Surg. 2013 Nov;258(5):731-40; discussion 741-2. doi: 10.1097/SLA.0b013e3182a6183e.
citation: Maru DM, Kopetz S, Boonsirikamchai P, Agarwal A, Chun YS, Wang H, Abdalla EK, Kaur H, Charnsangavej C, Vauthey JN, Loyer EM. Tumor thickness at the tumor-normal interface: a novel pathologic indicator of chemotherapy response in hepatic colorectal metastases. Am J Surg Pathol. 2010 Sep;34(9):1287-94. doi: 10.1097/PAS.0b013e3181eb2f7b.
citation: Frentzas S, Simoneau E, Bridgeman VL, Vermeulen PB, Foo S, Kostaras E, Nathan M, Wotherspoon A, Gao ZH, Shi Y, Van den Eynden G, Daley F, Peckitt C, Tan X, Salman A, Lazaris A, Gazinska P, Berg TJ, Eltahir Z, Ritsma L, Van Rheenen J, Khashper A, Brown G, Nystrom H, Sund M, Van Laere S, Loyer E, Dirix L, Cunningham D, Metrakos P, Reynolds AR. Vessel co-option mediates resistance to anti-angiogenic therapy in liver metastases. Nat Med. 2016 Nov;22(11):1294-1302. doi: 10.1038/nm.4197. Epub 2016 Oct 17.
citation: van Dam PJ, van der Stok EP, Teuwen LA, Van den Eynden GG, Illemann M, Frentzas S, Majeed AW, Eefsen RL, Coebergh van den Braak RRJ, Lazaris A, Fernandez MC, Galjart B, Laerum OD, Rayes R, Grunhagen DJ, Van de Paer M, Sucaet Y, Mudhar HS, Schvimer M, Nystrom H, Kockx M, Bird NC, Vidal-Vanaclocha F, Metrakos P, Simoneau E, Verhoef C, Dirix LY, Van Laere S, Gao ZH, Brodt P, Reynolds AR, Vermeulen PB. International consensus guidelines for scoring the histopathological growth patterns of liver metastasis. Br J Cancer. 2017 Nov 7;117(10):1427-1441. doi: 10.1038/bjc.2017.334. Epub 2017 Oct 5.
citation: Vigano L, Capussotti L, Barroso E, Nuzzo G, Laurent C, Ijzermans JN, Gigot JF, Figueras J, Gruenberger T, Mirza DF, Elias D, Poston G, Letoublon C, Isoniemi H, Herrera J, Sousa FC, Pardo F, Lucidi V, Popescu I, Adam R. Progression while receiving preoperative chemotherapy should not be an absolute contraindication to liver resection for colorectal metastases. Ann Surg Oncol. 2012 Sep;19(9):2786-96. doi: 10.1245/s10434-012-2382-7. Epub 2012 May 24.
citation: Rubbia-Brandt L, Giostra E, Brezault C, Roth AD, Andres A, Audard V, Sartoretti P, Dousset B, Majno PE, Soubrane O, Chaussade S, Mentha G, Terris B. Importance of histological tumor response assessment in predicting the outcome in patients with colorectal liver metastases treated with neo-adjuvant chemotherapy followed by liver surgery. Ann Oncol. 2007 Feb;18(2):299-304. doi: 10.1093/annonc/mdl386. Epub 2006 Oct 23.
citation: Adam R, Pascal G, Castaing D, Azoulay D, Delvart V, Paule B, Levi F, Bismuth H. Tumor progression while on chemotherapy: a contraindication to liver resection for multiple colorectal metastases? Ann Surg. 2004 Dec;240(6):1052-61; discussion 1061-4. doi: 10.1097/01.sla.0000145964.08365.01.
citation: Yamashita S, Chun YS, Kopetz SE, Vauthey JN. Biomarkers in colorectal liver metastases. Br J Surg. 2018 May;105(6):618-627. doi: 10.1002/bjs.10834. Epub 2018 Mar 26.
citation: Zakaria S, Donohue JH, Que FG, Farnell MB, Schleck CD, Ilstrup DM, Nagorney DM. Hepatic resection for colorectal metastases: value for risk scoring systems? Ann Surg. 2007 Aug;246(2):183-91. doi: 10.1097/SLA.0b013e3180603039.
citation: Gregoire E, Hoti E, Gorden DL, de la Serna S, Pascal G, Azoulay D. Utility or futility of prognostic scoring systems for colorectal liver metastases in an era of advanced multimodal therapy. Eur J Surg Oncol. 2010 Jun;36(6):568-74. doi: 10.1016/j.ejso.2010.03.009. Epub 2010 Apr 21.
citation: Fong Y, Fortner J, Sun RL, Brennan MF, Blumgart LH. Clinical score for predicting recurrence after hepatic resection for metastatic colorectal cancer: analysis of 1001 consecutive cases. Ann Surg. 1999 Sep;230(3):309-18; discussion 318-21. doi: 10.1097/00000658-199909000-00004.
citation: Nordlinger B, Guiguet M, Vaillant JC, Balladur P, Boudjema K, Bachellier P, Jaeck D. Surgical resection of colorectal carcinoma metastases to the liver. A prognostic scoring system to improve case selection, based on 1568 patients. Association Francaise de Chirurgie. Cancer. 1996 Apr 1;77(7):1254-62.