{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T06:15:45Z","timestamp":1788329745141,"version":"build-2803163510"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T00:00:00Z","timestamp":1788307200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T00:00:00Z","timestamp":1788307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    This paper presents the design, development and evaluation of a novel robotic platform for endoscopic ultrasound-guided fine-needle biopsy of liver lesions. The system combines a four degrees-of-freedom (DoF) two-segment tendon-driven continuum robot (TDCR) endoscope with a two DoF superelastic nickel\u2013titanium bevel-tip steerable needle. Needle path planning is achieved using NeedleNav, a soft actor\u2013critic (SAC) deep reinforcement learning (DRL) model that generates collision-free trajectories to deep-seated lesions. This represents one of the first integrated systems combining a TDCR, steerable needle and DRL-based navigation, and the first application of a SAC to liver lesion targeting. Evaluation of the TDCR through tip tracking of circular, diamond-shaped and arc trajectories demonstrated a mean absolute error (MAE) of 13.19 mm. NeedleNav converged to obstacle avoidance trajectories in\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$\\sim $$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mo>\u223c<\/mml:mo>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    2500 training episodes. Needle curvature was augmented by hand-fabricating notches on its distal section. Two needles with a 3-cm and 8-cm notched section were evaluated in a gelatine liver phantom, achieving an MAE of 21.78 mm and 14.86 mm, respectively, for obstacle avoidance trajectories. The system demonstrated observable path deflection compared to obstacle-free trajectories for the same targets. Together, these findings suggest the feasibility of our proposed solution, expanding the reach of endoscopic needle interventions to deep-seated lesions in the right lobe.\n                  <\/jats:p>","DOI":"10.1007\/s11548-026-03779-w","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T05:49:54Z","timestamp":1788328194000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Design and development of an endoscopic robotic system and deep reinforcement learning path planning algorithm for fine-needle biopsy of liver lesions"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-7021-5978","authenticated-orcid":false,"given":"Raghav","family":"Khanna","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikola","family":"Fischer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenting","family":"Du","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christos","family":"Bergeles","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,2]]},"reference":[{"issue":"2","key":"3779_CR1","doi-asserted-by":"publisher","first-page":"516","DOI":"10.1016\/j.jhep.2023.03.017","volume":"79","author":"H Devarbhavi","year":"2023","unstructured":"Devarbhavi H, Asrani SK, Arab JP, Nartey YA, Pose E, Kamath PS (2023) Global burden of liver disease: update. J Hepatol 79(2):516\u2013537. https:\/\/doi.org\/10.1016\/j.jhep.2023.03.017","journal-title":"J Hepatol"},{"issue":"8","key":"3779_CR2","doi-asserted-by":"publisher","first-page":"1382","DOI":"10.1136\/gutjnl-2020-321299","volume":"69","author":"J Neuberger","year":"2020","unstructured":"Neuberger J, Patel J, Caldwell H, Davies S, Hebditch V, Hollywood C et al (2020) Guidelines on the use of liver biopsy in clinical practice from the british society of gastroenterology, the royal college of radiologists and the royal college of pathology. Gut 69(8):1382\u20131403. https:\/\/doi.org\/10.1136\/gutjnl-2020-321299","journal-title":"Gut"},{"key":"3779_CR3","doi-asserted-by":"publisher","DOI":"10.1007\/s11894-019-0675-8","author":"SR Mok","year":"2019","unstructured":"Mok SR, Diehl DL (2019) The role of eus in liver biopsy. 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