5 MSc Research Ideas: 32-Slice CT in Medical Imaging

1. Radiation Dose Optimization in Routine Chest CT Using Automated Exposure Control (AEC) vs. Fixed mAs Protocols

• Uses already-acquired DICOM data from hospital PACS
• No new patient recruitment or radiation exposure needed
• 32-slice CT scanners have AEC capability (e.g., GE SmartmA, Siemens CARE Dose4D)
• Phantom validation can be done with a standard CTDI phantom

2. Assessment of Image Quality and Diagnostic Adequacy of Low-kVp Abdominal CT for Liver Lesion Characterization on a 32-Slice Scanner

• Retrospective PACS-based review
• Liver lesions (cysts, haemangiomas, HCC) are common in most radiology departments
• 32-slice scanners can acquire at 80/100/120/140 kVp
• Radiologist blinded review is a standard methodology

3. Scan Parameter Optimization for CT Pulmonary Angiography (CTPA) on a 32-Slice Scanner: Bolus Timing vs. Bolus Tracking Technique

• CTPA is a high-volume, routine examination
• Both techniques are routinely used in departments with 32-slice scanners
• Retrospective review of scan data and radiology reports is straightforward
• Bolus tracking software is available on most 32-slice platforms (GE SmartPrep, Siemens CARE Bolus)

4. Evaluation of Iterative Reconstruction vs. Filtered Back Projection for Head CT in Trauma Patients on a 32-Slice Scanner

• Head trauma CT is one of the highest-volume studies in most hospitals
• Retrospective DICOM data is readily available
• FBP is the standard on 32-slice; some models have basic IR as an option
• Image quality can be evaluated objectively (HU, noise, CNR) and subjectively (grey-white differentiation, artefact scores)

5. Retrospective Analysis of CT-Derived Bone Mineral Density (BMD) Measurements Using Opportunistic Screening in Routine Abdominal CT Scans

• Uses existing scan data - no additional radiation, no new patients
• HU measurement in vertebral body is a simple ROI tool available on any PACS workstation
• Threshold values (HU < 110 = osteoporosis, HU 110-160 = osteopenia) are established in literature
• 32-slice scanner data is adequate for this measurement - no special protocol needed

Quick Comparison Table

• Ethics approval will be needed but retrospective anonymized DICOM data typically qualifies for expedited/waived consent
• Aim for a minimum of 50-100 scans per group for adequate statistical power
• Register the study protocol before data collection to strengthen the research credibility
• All 5 are publishable in journals like Radiography, Journal of Medical Imaging and Radiation Sciences, or European Journal of Radiology Open

10 MSc Research Ideas: NCCT Brain & Chest CT on 32-Slice Scanner

NCCT BRAIN (Ideas 1-5)

1. Optimizing Window Width and Level Settings for NCCT Brain: Impact on Detection of Early Ischaemic Changes

• No new scanning required; uses existing PACS data
• Window manipulation is done on a PACS workstation - no special software
• ASPECTS scoring is a validated, published tool
• 32-slice NCCT is the frontline tool for acute stroke in most hospitals

2. Radiation Dose Survey and Establishment of Local Diagnostic Reference Levels (LDRLs) for NCCT Brain on 32-Slice CT Scanners

• CTDIvol and DLP are stored automatically in every DICOM header
• No patient follow-up or clinical data needed beyond scan parameters and patient weight/age group
• Well-established methodology; national DRL surveys are a recognized research category
• Can include 200-500 patients easily within one institution over 6 months

3. Correlation of Hyperdense Middle Cerebral Artery Sign (HMCAS) on NCCT with Final Infarct Volume and Clinical Outcome in Ischaemic Stroke

• All data available from PACS and clinical records
• HMCAS is a visible finding on standard NCCT - no contrast or special protocol
• HU measurement is a basic ROI tool on any PACS workstation
• 32-slice NCCT is adequate for this measurement

4. Assessment of Intracranial Calcification Patterns on NCCT Brain: Prevalence and Inter-observer Agreement in a Retrospective Cohort

• Pure NCCT data review; no clinical follow-up needed
• Calcifications are clearly visible on unenhanced CT - no contrast required
• Large numbers easily achievable (300-500 scans in 6 months)
• 32-slice NCCT is standard for this

5. Comparison of Brain Parenchyma Noise Levels at Different Reconstruction Kernels (Soft vs. Standard) on NCCT Brain Using 32-Slice CT

• Many 32-slice scanners reconstruct both soft tissue (H20-H30) and bone (H60-H70) kernels for brain/skull
• ROI noise measurements are available on any PACS
• Phantom measurements can supplement clinical data
• No additional radiation or patients required

CHEST CT (Ideas 6-10)

6. Audit of Radiation Dose and Image Quality in Routine Chest CT: Establishing Local DRLs and Identifying Dose Reduction Opportunities on a 32-Slice Scanner

• DICOM header data is universally available
• No patient follow-up needed
• Standard methodology with published protocols (IAEA, IPEM guidance)
• 32-slice chest CT is the workaround scanner in most non-specialist centres

7. Retrospective Evaluation of CT Findings in COVID-19 Pneumonia and Correlation with Clinical Severity Scores on a 32-Slice Scanner

• Large archive of COVID-19 CT data exists in most hospitals from 2020-2023
• CT severity scoring tools are validated and free to use
• Clinical data from hospital records is routinely available
• 32-slice CT is the scanner most commonly used during the COVID-19 pandemic in district hospitals

8. Assessment of Incidental Coronary Artery Calcification (CAC) on Non-Gated Chest CT and Correlation with Cardiovascular Risk Factors

• Coronary calcification is often visually apparent even on non-gated 32-slice chest CT
• Qualitative visual scoring (not Agatston) is feasible without ECG gating
• Retrospective data from PACS and clinical notes
• Does not require any additional scanning or patient contact

9. Characterization of Solitary Pulmonary Nodules on Chest CT: Size, Density, and Location Analysis in a Retrospective Cohort Using 32-Slice Scanner Data

• SPN is a common incidental finding on chest CT
• All measurements done on PACS using standard tools
• Fleischner 2017 criteria are freely available and widely cited
• 32-slice CT with 5mm slices is adequate for nodules >6mm (the main Fleischner threshold)

10. Evaluation of Image Quality Parameters (Noise, CNR, Artefact) in Chest CT at Varying mAs Levels: A Retrospective Phantom-Supplemented Study

• AEC naturally creates a range of mAs across patients; this variance can be exploited retrospectively
• BMI is available from clinical records or height/weight in notes
• Phantom scanning at defined mAs is straightforward and takes 1-2 hours
• ROI measurements are done on PACS - no special software needed

Summary Table

Practical Tips for All 10

• Ethics: Retrospective anonymized DICOM studies typically qualify for expedited ethics approval. Confirm with your institution's IRB/ethics committee early.
• Sample size: Aim for minimum 80-100 cases per group for comparative studies; 200+ for prevalence/audit studies. Calculate formally using G*Power (free software).
• Journals to target: Radiography (UK), Journal of Medical Imaging and Radiation Sciences, European Journal of Radiology Open, Polish Journal of Radiology, Insights into Imaging - all are MSc-appropriate with open access options.
• No fabricated references: All methods mentioned (ASPECTS, Fleischner 2017, IAEA DRL methodology, HMCAS, CT severity scoring) are well-established published tools you can verify independently before using.
• 32-slice specific: Ideas 2, 3, 6, 8, and 9 specifically address the gap in literature for 32-slice systems vs. higher-slice scanners - this is a genuine and publishable novelty angle.

MSc Research Proposal

Radiation Dose Audit and Establishment of Local Diagnostic Reference Levels (LDRLs) for Routine Chest CT on a 32-Slice Scanner in Jharkhand, India

1. Title

2. Background and Rationale (Why This Study?)

• India published its first national CT DRL survey only in 2026 (Akhilesh et al., Physica Medica, PMID: 42468488), revealing high variability across facilities and significantly higher DLP values than international standards - suggesting use of scan lengths longer than necessary.
• A similar state-level survey from Uttarakhand (Uniyal et al., Applied Radiation and Isotopes, 2025, PMID: 40319845) found proposed thorax DRLs of CTDIvol 10 mGy and DLP 271 mGy·cm - but no such data exists from Jharkhand.
• Jharkhand is a state with a significant burden of pulmonary tuberculosis, coal-mining related lung disease, and post-COVID complications - meaning chest CT volumes are high.
• Most CT scanners in district and teaching hospitals in Jharkhand are 32-slice systems; yet almost all published dose optimization literature comes from 64-slice or higher systems.

3. Aim and Objectives

Aim

Objectives

1. To collect CTDIvol and DLP values from DICOM headers of consecutive chest CT scans.
2. To calculate effective dose using the standard conversion factor (E = k × DLP, where k = 0.014 mSv/mGy·cm for chest).
3. To establish LDRLs as the 75th percentile of CTDIvol and DLP for the study population.
4. To compare institutional LDRLs with national (India 2026) and international reference values (European Commission, UK, IAEA).
5. To assess objective image quality (image noise as SD of HU in ROI in aorta, paraspinal muscle, and lung) across different dose levels.
6. To identify factors contributing to dose variation - patient BMI, clinical indication, scan length, and operator/time of scan.

4. Study Design

5. Inclusion and Exclusion Criteria

Inclusion

• Adult patients (age ≥18 years)
• Chest CT scans (NCCT or contrast-enhanced, to be analyzed separately)
• Scans performed on the institutional 32-slice scanner
• Complete DICOM data with CTDIvol and DLP recorded in the header

Exclusion

• Pediatric patients (age <18 years) - different DRL standards apply
• CT-guided interventional procedures
• Incomplete DICOM header data (missing CTDIvol/DLP)
• Post-operative patients with metallic implants causing heavy artefacts
• Combined chest-abdomen-pelvis scans (different protocol category)

6. Data Collection Methodology

Step 1: DICOM Header Extraction

• Access PACS (Picture Archiving and Communication System) or CT scanner console
• For each scan, extract from DICOM header:
  • CTDIvol (mGy) - automatically recorded
  • DLP (mGy·cm) - automatically recorded
  • Scan date and time
  • kVp (kilovoltage)
  • mAs (effective milliampere-seconds)
  • Slice thickness
  • Scan length (cm)
  • Patient age, sex, weight/height (if recorded)

Step 2: Clinical Indication

• Infection/pneumonia/TB
• Post-COVID assessment
• Malignancy (suspected or follow-up)
• Trauma
• Other/miscellaneous

Step 3: Effective Dose Calculation

E (mSv) = k × DLP where k = 0.014 mSv/mGy·cm for chest (ICRP Publication 103 / NRPB conversion factor)

Step 4: Image Quality Assessment

• Select a random subset of 50 scans from across the dose range
• On the CT console or PACS workstation, place circular ROI (1 cm²) in:
  • Descending aorta (at carina level)
  • Paraspinal muscle (posterior, at carina level)
  • Lung parenchyma (right lower lobe, away from vessels)
• Record mean HU and Standard Deviation (SD) of HU
• SD of HU = image noise (higher SD = more noise = worse image quality)
• Calculate Signal-to-Noise Ratio (SNR) = mean HU / SD HU

Step 5: Data Recording

• Patient ID (anonymized), age, sex, weight
• Indication category
• kVp, mAs, slice thickness, scan length
• CTDIvol, DLP
• Calculated effective dose
• ROI noise measurements (subset)

7. Sample Size

• Minimum required: 200 chest CT scans
• This is in line with IAEA methodology (minimum 20 patients per scanner per examination type; for establishing LDRLs at a single institution, 200 is the recommended minimum)
• If the department does 5-10 chest CTs per day, 200 patients can be collected within 1-2 months of retrospective data
• For subgroup analysis (by indication), aim for at least 50 per major indication category

8. Statistical Analysis

9. Reference DRL Values for Comparison

10. Expected Results and Significance

• Dose variation across indications (trauma scans may use higher mAs; infection may use lower)
• Some protocols may exceed the national DRL - suggesting scope for dose reduction
• Image noise likely increases as CTDIvol decreases (dose-quality tradeoff curve)
• Heavier patients (higher BMI) will receive higher CTDIvol due to AEC

• This will be the first published LDRL data for chest CT from Jharkhand
• It provides your institution with an evidence-based benchmark for protocol review
• If your doses are above national DRL, the data supports a protocol optimization initiative
• If doses are below national DRL, the study demonstrates good local practice - equally publishable
• Contributes to India's national radiation protection effort, which the AERB and BARC are actively promoting

11. Ethical Considerations

• Ethics approval: Apply to your Institutional Ethics Committee (IEC). This is a retrospective, anonymized records-based study with no new radiation exposure and no direct patient involvement - most IECs grant expedited/waived consent for this type of study.
• All patient identifiers will be removed from the dataset before analysis
• Data stored securely on a password-protected institutional computer
• No additional scans, contrast, or procedures required for any patient

12. Timeline (12 Months Total)

13. Budget (Low-Cost Study)

14. Limitations (State These Honestly)

• Single-centre study; results may not represent all of Jharkhand
• BMI/weight may not be recorded for all patients in PACS - this limits dose normalization analysis
• Effective dose calculation using k-factor is an estimate, not a measured value
• Image quality assessment is objective (noise) but does not include radiologist diagnostic confidence scoring (this could be a future extension)
• 32-slice scanner results are not directly comparable to higher-slice systems

15. Target Journals for Publication

Key Verified References to Cite in Your Proposal

1. Akhilesh P et al. (2026). Computed Tomography Diagnostic Reference Levels in India: Results from the First National Survey. Physica Medica. PMID: 42468488 - India national DRL: CTDIvol 13 mGy, DLP 602 mGy·cm for thorax.
2. Uniyal SC et al. (2025). Patient dose survey and determination of diagnostic reference levels for routine CT examinations in Uttarakhand, India. Applied Radiation and Isotopes. PMID: 40319845 - State-level DRL methodology from another Tier-2 Indian state (model for your study).
3. ICRP Publication 103 (2007) - Source of k-conversion factor (0.014 mSv/mGy·cm for chest).
4. European Commission Radiation Protection 185 (2014) - European DRL reference values.

Note: All PMIDs and values cited above are from verified, published peer-reviewed sources and cross-checked in the literature search conducted on 04 August 2026.