Five Years, One Bunker:
From Nervous Fresher to Senior RTT

Starting in the Middle of a Pandemic

I joined Amrita Institute of Medical Sciences in November 2020 - right in the middle of the COVID-19 pandemic. Masks, shields, constant sanitising, and a hospital running at a very different rhythm than normal: that was the backdrop to my very first day as a Radiation Therapist.

CT Simulation: Where It All Began

My first posting was CT Simulation - the rotation most students try to skip during training, and the one I ended up starting my career on. I remember the uncertainty clearly: not always knowing what to do or how to do it, and that quiet fear every fresher knows, of getting something wrong with a patient in front of you.

What carried me through it was the seniors around me - patient, step-by-step guidance rather than being thrown in at the deep end. I started as an observer only, watching before touching anything. Slowly I was trusted with CT QA and calibration checks, then the part that actually tested me: fiducial tattoo placement, the toughest skill to get comfortable with. From there I moved on to plain CT scans, and eventually brachytherapy scans on Oncentra.

Learning the Linac: Elekta Precise to Synergy

From CT Sim I moved onto the linear accelerators - starting on the Elekta Precise, then onto the Synergy. This is where the technical range of the job really opened up: cutout preparation, photon block preparation, matching and treatment delivery, port matching, CBCT, fluoroscopy, TBI (total body irradiation), blood irradiation, and image registration.

I learned to work across MOSAIQ, XiO, and MONACO - the record-and-verify and planning systems that keep a department running. Early morning duty meant warming up and running QA on every machine before the first patient of the day - a quiet hour that taught me how much happens before a department even opens its doors.

Back to CT Sim - This Time, Leading

My second rotation on CT Sim looked nothing like the first. I learned 4DCT acquisition and CECT, and, for the first time, handled CT Sim alone, leading the room instead of being led through it. That shift, from being observed to being trusted to run a machine independently, is one of the moments I remember most clearly.

Tomotherapy: From H to Radixact

Next came Tomotherapy. On the older Hi-Art (H) unit I learned head & neck case matching and Adaptive RT. When the department moved to Radixact, the case mix expanded further - pelvic ART, TMLI (total marrow/lymphoid irradiation), and CSI (craniospinal irradiation), all run through iDMS.

CyberKnife

CyberKnife was the most technically demanding machine I worked on - LOT, fiducial tracking, and HCC (liver) cases, where sub-millimetre precision and real-time tracking aren't optional. They're the whole point.

The Rest of the Job

None of this happens in isolation. Day to day, the work is as much about the patient in front of you as the machine beside you - checking in on how they're coping with treatment, caregiving, sitting in on MDT (multidisciplinary team) discussions, reviewing images, and adapting plans through Adaptive RT when anatomy shifts mid-course.

Department life added its own rhythm: exam invigilation for students, something that only starts once you've completed three years of clinical duty, patient scheduling, and late-night call-outs whenever a machine faulted unexpectedly.

Mentoring the Next Generation

Teaching became a bigger part of my role over time - training new RTTs, precepting students on the floor, and eventually taking on exam invigilation duties. Watching someone go from a nervous observer to a confident operator, the way I once did, is one of the most satisfying parts of the job.

Presenting & Learning Outside the Department

Outside day-to-day clinical work, I presented posters and attended conferences - chances to step back from the treatment room, engage with the wider radiation oncology community, see what other centres were doing, and bring ideas back.

The Good Moments

Not everything was about machines and protocols. Department trips, festival celebrations, the conferences I got to attend, and the friendships built over five years in the same bunkers and corridors - that's the part of the job no CV line captures, but the part I'll remember longest.

The Last Day

I left Amrita on 2 May 2026 - roughly nine years after I first walked in, counting academic and clinical experience together, and five years clinical, start to finish, across every machine in the department: CT Sim, Linac, Tomotherapy, CyberKnife. And a long list of people who taught me, trusted me, and eventually called me senior.

Why I Moved Towards AI

The pull toward AI didn't start after I left the bunker, it started inside it. My undergraduate thesis had me manually comparing PTV volumes across 3DCT and 4DCT datasets, patient by patient, contour by contour. The CyberKnife motion study that followed meant wrangling 6DOF intrafraction tracking data for 27 patients by hand. Both were, underneath the clinical question, data problems, and I kept noticing how much of the work in a radiotherapy department, contouring, margin calculation, plan review, is repetitive enough to automate but specific enough that it needs someone who has actually done it to build the automation properly.

Five years at the console made that gap concrete: departments stretched thin on contouring time, plans queued behind a bottleneck that had nothing to do with clinical judgement and everything to do with hours in the day. So I went back to learning, this time data science, machine learning and applied AI, alongside the clinical work rather than instead of it. Oncology AI specifically, because that's the domain I actually understand from the inside: what a contour needs to be clinically usable, where an auto-segmentation model is likely to fail, what a radiation therapist actually needs from a tool at 7am with a full patient list. That's the premise VINE Clinical Intelligence is built on, AI for radiation oncology designed by someone who has stood in the bunker, not studied it from the outside.